Factors Influencing Psychological Adjustment: Statistics Assignment
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Homework Assignment
AI Summary
This statistics assignment analyzes survey data collected from Graduate Diploma in Educational Psychology students in Melbourne, Australia, focusing on factors impacting their psychological adjustment and wellbeing. The study utilized various validated scales, including measures of self-esteem, optimism, perceived control, perceived stress, positive and negative affect, and life satisfaction. A Likert scale was also employed to assess social desirability bias. The assignment presents a case processing summary and an agglomeration schedule derived from the data, likely utilizing cluster analysis to identify patterns and relationships within the survey responses. The analysis provides a detailed breakdown of the statistical procedures and outcomes, offering valuable insights into the psychological profiles of the student population and the factors that contribute to their overall wellbeing. The assignment offers valuable information for students studying statistics or psychology.
Running head: STATISTICS
Statistics
Name of the Student:
Name of the University:
Author’s note:
Statistics
Name of the Student:
Name of the University:
Author’s note:
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1STATISTICS
Table of Contents
Introduction:-...................................................................................................................................3
Question and Answers:-...................................................................................................................3
Answer 1......................................................................................................................................3
Part I.........................................................................................................................................3
Part II.......................................................................................................................................3
Part III......................................................................................................................................3
Answer 2......................................................................................................................................4
Part I.........................................................................................................................................4
Part II.......................................................................................................................................4
Part III......................................................................................................................................4
Answer 3......................................................................................................................................4
Part I.........................................................................................................................................4
Part II.......................................................................................................................................5
Part III......................................................................................................................................5
Answer 4......................................................................................................................................5
Table of Contents
Introduction:-...................................................................................................................................3
Question and Answers:-...................................................................................................................3
Answer 1......................................................................................................................................3
Part I.........................................................................................................................................3
Part II.......................................................................................................................................3
Part III......................................................................................................................................3
Answer 2......................................................................................................................................4
Part I.........................................................................................................................................4
Part II.......................................................................................................................................4
Part III......................................................................................................................................4
Answer 3......................................................................................................................................4
Part I.........................................................................................................................................4
Part II.......................................................................................................................................5
Part III......................................................................................................................................5
Answer 4......................................................................................................................................5
2STATISTICS
3STATISTICS
Introduction:-
The survey data is based on a Graduate Diploma in Educational Psychology students of
Melbourne, Australia and surrounding diatrict. The study was designed to explore the factors that
influence on respondents’ psychological adjustment and wellbeing. In this study, there is a
variety of validated scales measuring constructs. The scale included the measurement of self-
esteem, optimism, perceptions of control, perceived stress, good and bad effect and satisfaction
in lifespan. A “Likert” scale was also involved that measured tendency of people to present
themselves in a favourable or socially desirable manner.
Question and Answers:-
Answer 1
Case Processing Summarya
Cases
Valid Missing Total
N Percent N Percent N Percent
426 97.0% 13 3.0% 439 100.0%
a. Squared Euclidean Distance used
Agglomeration Schedule
Stage Cluster Combined Coefficients Stage Cluster First Appears Next Stage
Cluster 1 Cluster 2 Cluster 1 Cluster 2
1 105 133 .003 0 0 161
2 154 160 .008 0 0 278
3 341 402 .015 0 0 110
4 298 312 .021 0 0 41
5 247 373 .027 0 0 190
6 145 197 .035 0 0 283
Introduction:-
The survey data is based on a Graduate Diploma in Educational Psychology students of
Melbourne, Australia and surrounding diatrict. The study was designed to explore the factors that
influence on respondents’ psychological adjustment and wellbeing. In this study, there is a
variety of validated scales measuring constructs. The scale included the measurement of self-
esteem, optimism, perceptions of control, perceived stress, good and bad effect and satisfaction
in lifespan. A “Likert” scale was also involved that measured tendency of people to present
themselves in a favourable or socially desirable manner.
Question and Answers:-
Answer 1
Case Processing Summarya
Cases
Valid Missing Total
N Percent N Percent N Percent
426 97.0% 13 3.0% 439 100.0%
a. Squared Euclidean Distance used
Agglomeration Schedule
Stage Cluster Combined Coefficients Stage Cluster First Appears Next Stage
Cluster 1 Cluster 2 Cluster 1 Cluster 2
1 105 133 .003 0 0 161
2 154 160 .008 0 0 278
3 341 402 .015 0 0 110
4 298 312 .021 0 0 41
5 247 373 .027 0 0 190
6 145 197 .035 0 0 283
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4STATISTICS
7 424 426 .043 0 0 83
8 152 292 .052 0 0 137
9 225 236 .061 0 0 226
10 211 264 .070 0 0 47
11 162 226 .080 0 0 153
12 127 161 .090 0 0 254
13 86 108 .101 0 0 100
14 55 91 .112 0 0 172
15 396 415 .124 0 0 140
16 358 422 .135 0 0 158
17 301 368 .147 0 0 64
18 260 291 .158 0 0 193
19 241 249 .170 0 0 161
20 70 117 .182 0 0 254
21 114 173 .194 0 0 195
22 289 300 .206 0 0 132
23 231 333 .218 0 0 127
24 360 420 .230 0 0 150
25 248 315 .242 0 0 176
26 314 339 .255 0 0 70
27 394 423 .268 0 0 138
28 153 198 .281 0 0 212
29 336 356 .295 0 0 185
30 253 267 .308 0 0 117
31 224 283 .322 0 0 103
32 166 178 .336 0 0 189
33 407 425 .350 0 0 143
34 332 355 .364 0 0 164
35 240 242 .378 0 0 189
36 295 395 .392 0 0 245
37 217 270 .407 0 0 170
38 54 84 .421 0 0 293
39 257 351 .436 0 0 98
40 131 216 .450 0 0 182
41 230 298 .465 0 4 135
42 232 388 .481 0 0 165
43 282 331 .497 0 0 94
44 293 361 .512 0 0 110
45 320 390 .528 0 0 210
46 271 352 .544 0 0 175
7 424 426 .043 0 0 83
8 152 292 .052 0 0 137
9 225 236 .061 0 0 226
10 211 264 .070 0 0 47
11 162 226 .080 0 0 153
12 127 161 .090 0 0 254
13 86 108 .101 0 0 100
14 55 91 .112 0 0 172
15 396 415 .124 0 0 140
16 358 422 .135 0 0 158
17 301 368 .147 0 0 64
18 260 291 .158 0 0 193
19 241 249 .170 0 0 161
20 70 117 .182 0 0 254
21 114 173 .194 0 0 195
22 289 300 .206 0 0 132
23 231 333 .218 0 0 127
24 360 420 .230 0 0 150
25 248 315 .242 0 0 176
26 314 339 .255 0 0 70
27 394 423 .268 0 0 138
28 153 198 .281 0 0 212
29 336 356 .295 0 0 185
30 253 267 .308 0 0 117
31 224 283 .322 0 0 103
32 166 178 .336 0 0 189
33 407 425 .350 0 0 143
34 332 355 .364 0 0 164
35 240 242 .378 0 0 189
36 295 395 .392 0 0 245
37 217 270 .407 0 0 170
38 54 84 .421 0 0 293
39 257 351 .436 0 0 98
40 131 216 .450 0 0 182
41 230 298 .465 0 4 135
42 232 388 .481 0 0 165
43 282 331 .497 0 0 94
44 293 361 .512 0 0 110
45 320 390 .528 0 0 210
46 271 352 .544 0 0 175
5STATISTICS
47 211 228 .560 10 0 152
48 318 340 .576 0 0 58
49 168 201 .592 0 0 160
50 41 112 .608 0 0 97
51 357 387 .624 0 0 171
52 71 90 .641 0 0 333
53 78 169 .657 0 0 154
54 122 155 .673 0 0 248
55 404 408 .690 0 0 180
56 251 400 .707 0 0 78
57 279 286 .724 0 0 124
58 188 318 .741 0 48 186
59 410 421 .759 0 0 164
60 92 100 .776 0 0 307
61 144 174 .794 0 0 173
62 93 342 .812 0 0 236
63 191 370 .830 0 0 156
64 172 301 .847 0 17 230
65 120 147 .865 0 0 123
66 268 350 .883 0 0 82
67 89 187 .901 0 0 218
68 209 354 .920 0 0 89
69 43 135 .938 0 0 272
70 314 366 .957 26 0 113
71 200 398 .975 0 0 106
72 254 280 .994 0 0 116
73 184 206 1.013 0 0 217
74 266 353 1.032 0 0 227
75 196 199 1.052 0 0 253
76 284 345 1.071 0 0 150
77 302 371 1.091 0 0 158
78 251 307 1.110 56 0 309
79 81 148 1.130 0 0 214
80 202 222 1.150 0 0 282
81 391 401 1.170 0 0 163
82 192 268 1.190 0 66 179
83 375 424 1.210 0 7 151
84 313 323 1.230 0 0 147
85 269 329 1.251 0 0 195
86 364 392 1.271 0 0 162
47 211 228 .560 10 0 152
48 318 340 .576 0 0 58
49 168 201 .592 0 0 160
50 41 112 .608 0 0 97
51 357 387 .624 0 0 171
52 71 90 .641 0 0 333
53 78 169 .657 0 0 154
54 122 155 .673 0 0 248
55 404 408 .690 0 0 180
56 251 400 .707 0 0 78
57 279 286 .724 0 0 124
58 188 318 .741 0 48 186
59 410 421 .759 0 0 164
60 92 100 .776 0 0 307
61 144 174 .794 0 0 173
62 93 342 .812 0 0 236
63 191 370 .830 0 0 156
64 172 301 .847 0 17 230
65 120 147 .865 0 0 123
66 268 350 .883 0 0 82
67 89 187 .901 0 0 218
68 209 354 .920 0 0 89
69 43 135 .938 0 0 272
70 314 366 .957 26 0 113
71 200 398 .975 0 0 106
72 254 280 .994 0 0 116
73 184 206 1.013 0 0 217
74 266 353 1.032 0 0 227
75 196 199 1.052 0 0 253
76 284 345 1.071 0 0 150
77 302 371 1.091 0 0 158
78 251 307 1.110 56 0 309
79 81 148 1.130 0 0 214
80 202 222 1.150 0 0 282
81 391 401 1.170 0 0 163
82 192 268 1.190 0 66 179
83 375 424 1.210 0 7 151
84 313 323 1.230 0 0 147
85 269 329 1.251 0 0 195
86 364 392 1.271 0 0 162
6STATISTICS
87 179 372 1.292 0 0 178
88 156 259 1.313 0 0 222
89 209 325 1.334 68 0 125
90 101 159 1.356 0 0 276
91 413 414 1.377 0 0 198
92 235 297 1.398 0 0 216
93 326 389 1.420 0 0 243
94 282 287 1.442 43 0 237
95 204 263 1.464 0 0 269
96 26 99 1.486 0 0 209
97 41 67 1.508 50 0 284
98 257 321 1.530 39 0 272
99 116 243 1.553 0 0 215
100 33 86 1.575 0 13 177
101 139 376 1.598 0 0 190
102 111 233 1.620 0 0 115
103 224 365 1.643 31 0 285
104 195 239 1.666 0 0 221
105 163 310 1.689 0 0 251
106 200 244 1.712 71 0 218
107 37 61 1.736 0 0 321
108 214 285 1.759 0 0 239
109 15 29 1.783 0 0 262
110 293 341 1.807 44 3 187
111 124 337 1.830 0 0 224
112 319 347 1.854 0 0 290
113 299 314 1.878 0 70 293
114 303 379 1.903 0 0 225
115 111 277 1.927 102 0 296
116 223 254 1.952 0 72 230
117 208 253 1.977 0 30 217
118 290 308 2.002 0 0 198
119 203 218 2.027 0 0 191
120 219 272 2.053 0 0 133
121 369 412 2.078 0 0 192
122 250 418 2.104 0 0 276
123 120 129 2.131 65 0 277
124 276 279 2.158 0 57 156
125 209 338 2.184 89 0 258
126 363 382 2.212 0 0 256
87 179 372 1.292 0 0 178
88 156 259 1.313 0 0 222
89 209 325 1.334 68 0 125
90 101 159 1.356 0 0 276
91 413 414 1.377 0 0 198
92 235 297 1.398 0 0 216
93 326 389 1.420 0 0 243
94 282 287 1.442 43 0 237
95 204 263 1.464 0 0 269
96 26 99 1.486 0 0 209
97 41 67 1.508 50 0 284
98 257 321 1.530 39 0 272
99 116 243 1.553 0 0 215
100 33 86 1.575 0 13 177
101 139 376 1.598 0 0 190
102 111 233 1.620 0 0 115
103 224 365 1.643 31 0 285
104 195 239 1.666 0 0 221
105 163 310 1.689 0 0 251
106 200 244 1.712 71 0 218
107 37 61 1.736 0 0 321
108 214 285 1.759 0 0 239
109 15 29 1.783 0 0 262
110 293 341 1.807 44 3 187
111 124 337 1.830 0 0 224
112 319 347 1.854 0 0 290
113 299 314 1.878 0 70 293
114 303 379 1.903 0 0 225
115 111 277 1.927 102 0 296
116 223 254 1.952 0 72 230
117 208 253 1.977 0 30 217
118 290 308 2.002 0 0 198
119 203 218 2.027 0 0 191
120 219 272 2.053 0 0 133
121 369 412 2.078 0 0 192
122 250 418 2.104 0 0 276
123 120 129 2.131 65 0 277
124 276 279 2.158 0 57 156
125 209 338 2.184 89 0 258
126 363 382 2.212 0 0 256
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7STATISTICS
127 231 322 2.239 23 0 211
128 46 56 2.267 0 0 375
129 374 393 2.295 0 0 274
130 215 348 2.322 0 0 251
131 359 419 2.351 0 0 336
132 289 330 2.379 22 0 280
133 219 237 2.408 120 0 248
134 103 121 2.437 0 0 255
135 230 275 2.466 41 0 232
136 80 110 2.495 0 0 252
137 152 288 2.524 8 0 298
138 182 394 2.554 0 27 231
139 150 296 2.583 0 0 213
140 346 396 2.614 0 15 168
141 186 317 2.645 0 0 259
142 256 344 2.676 0 0 264
143 213 407 2.706 0 33 243
144 142 234 2.738 0 0 294
145 36 278 2.769 0 0 314
146 324 380 2.801 0 0 244
147 313 378 2.833 84 0 188
148 238 417 2.865 0 0 260
149 83 220 2.898 0 0 240
150 284 360 2.930 76 24 300
151 274 375 2.963 0 83 240
152 69 211 2.996 0 47 184
153 162 309 3.029 11 0 256
154 39 78 3.062 0 53 228
155 34 113 3.095 0 0 274
156 191 276 3.129 63 124 364
157 349 377 3.163 0 0 226
158 302 358 3.198 77 16 186
159 35 132 3.233 0 0 347
160 164 168 3.268 0 49 253
161 105 241 3.303 1 19 277
162 335 364 3.338 0 86 220
163 343 391 3.374 0 81 168
164 332 410 3.409 34 59 318
165 229 232 3.445 0 42 329
166 123 180 3.481 0 0 270
127 231 322 2.239 23 0 211
128 46 56 2.267 0 0 375
129 374 393 2.295 0 0 274
130 215 348 2.322 0 0 251
131 359 419 2.351 0 0 336
132 289 330 2.379 22 0 280
133 219 237 2.408 120 0 248
134 103 121 2.437 0 0 255
135 230 275 2.466 41 0 232
136 80 110 2.495 0 0 252
137 152 288 2.524 8 0 298
138 182 394 2.554 0 27 231
139 150 296 2.583 0 0 213
140 346 396 2.614 0 15 168
141 186 317 2.645 0 0 259
142 256 344 2.676 0 0 264
143 213 407 2.706 0 33 243
144 142 234 2.738 0 0 294
145 36 278 2.769 0 0 314
146 324 380 2.801 0 0 244
147 313 378 2.833 84 0 188
148 238 417 2.865 0 0 260
149 83 220 2.898 0 0 240
150 284 360 2.930 76 24 300
151 274 375 2.963 0 83 240
152 69 211 2.996 0 47 184
153 162 309 3.029 11 0 256
154 39 78 3.062 0 53 228
155 34 113 3.095 0 0 274
156 191 276 3.129 63 124 364
157 349 377 3.163 0 0 226
158 302 358 3.198 77 16 186
159 35 132 3.233 0 0 347
160 164 168 3.268 0 49 253
161 105 241 3.303 1 19 277
162 335 364 3.338 0 86 220
163 343 391 3.374 0 81 168
164 332 410 3.409 34 59 318
165 229 232 3.445 0 42 329
166 123 180 3.481 0 0 270
8STATISTICS
167 265 311 3.517 0 0 234
168 343 346 3.555 163 140 278
169 126 183 3.592 0 0 292
170 217 328 3.630 37 0 258
171 304 357 3.668 0 51 232
172 55 95 3.707 14 0 284
173 144 175 3.745 61 0 237
174 102 367 3.784 0 0 312
175 128 271 3.823 0 46 200
176 248 383 3.862 25 0 280
177 33 98 3.901 100 0 361
178 179 207 3.940 87 0 299
179 176 192 3.980 0 82 247
180 384 404 4.020 0 55 310
181 205 306 4.060 0 0 311
182 131 134 4.101 40 0 330
183 60 115 4.142 0 0 233
184 69 165 4.184 152 0 340
185 336 406 4.226 29 0 249
186 188 302 4.269 58 158 287
187 181 293 4.311 0 110 326
188 193 313 4.355 0 147 242
189 166 240 4.398 32 35 292
190 139 247 4.442 101 5 331
191 104 203 4.486 0 119 332
192 221 369 4.530 0 121 204
193 260 381 4.575 18 0 212
194 7 9 4.620 0 0 317
195 114 269 4.667 21 85 311
196 87 261 4.713 0 0 299
197 72 177 4.759 0 0 255
198 290 413 4.806 118 91 231
199 16 82 4.853 0 0 348
200 62 128 4.900 0 175 302
201 119 190 4.948 0 0 221
202 149 212 4.996 0 0 290
203 14 47 5.044 0 0 266
204 88 221 5.093 0 192 294
205 252 397 5.142 0 0 265
206 57 281 5.192 0 0 279
167 265 311 3.517 0 0 234
168 343 346 3.555 163 140 278
169 126 183 3.592 0 0 292
170 217 328 3.630 37 0 258
171 304 357 3.668 0 51 232
172 55 95 3.707 14 0 284
173 144 175 3.745 61 0 237
174 102 367 3.784 0 0 312
175 128 271 3.823 0 46 200
176 248 383 3.862 25 0 280
177 33 98 3.901 100 0 361
178 179 207 3.940 87 0 299
179 176 192 3.980 0 82 247
180 384 404 4.020 0 55 310
181 205 306 4.060 0 0 311
182 131 134 4.101 40 0 330
183 60 115 4.142 0 0 233
184 69 165 4.184 152 0 340
185 336 406 4.226 29 0 249
186 188 302 4.269 58 158 287
187 181 293 4.311 0 110 326
188 193 313 4.355 0 147 242
189 166 240 4.398 32 35 292
190 139 247 4.442 101 5 331
191 104 203 4.486 0 119 332
192 221 369 4.530 0 121 204
193 260 381 4.575 18 0 212
194 7 9 4.620 0 0 317
195 114 269 4.667 21 85 311
196 87 261 4.713 0 0 299
197 72 177 4.759 0 0 255
198 290 413 4.806 118 91 231
199 16 82 4.853 0 0 348
200 62 128 4.900 0 175 302
201 119 190 4.948 0 0 221
202 149 212 4.996 0 0 290
203 14 47 5.044 0 0 266
204 88 221 5.093 0 192 294
205 252 397 5.142 0 0 265
206 57 281 5.192 0 0 279
9STATISTICS
207 51 59 5.242 0 0 339
208 49 65 5.293 0 0 303
209 26 305 5.344 96 0 316
210 320 403 5.396 45 0 326
211 96 231 5.449 0 127 320
212 153 260 5.502 28 193 345
213 150 167 5.555 139 0 344
214 66 81 5.610 0 79 295
215 18 116 5.664 0 99 300
216 235 385 5.719 92 0 249
217 184 208 5.774 73 117 316
218 89 200 5.830 67 106 302
219 107 334 5.886 0 0 275
220 118 335 5.942 0 162 335
221 119 195 5.999 201 104 387
222 151 156 6.056 0 88 281
223 185 245 6.114 0 0 298
224 106 124 6.172 0 111 318
225 170 303 6.230 0 114 287
226 225 349 6.288 9 157 344
227 140 266 6.346 0 74 337
228 25 39 6.405 0 154 346
229 194 255 6.464 0 0 267
230 172 223 6.523 64 116 309
231 182 290 6.583 138 198 291
232 230 304 6.643 135 171 368
233 60 130 6.704 183 0 306
234 265 409 6.766 167 0 324
235 262 405 6.828 0 0 310
236 48 93 6.890 0 62 273
237 144 282 6.953 173 94 338
238 136 210 7.016 0 0 324
239 12 214 7.079 0 108 289
240 83 274 7.143 149 151 331
241 4 23 7.208 0 0 315
242 171 193 7.273 0 188 334
243 213 326 7.338 143 93 366
244 324 362 7.403 146 0 332
245 85 295 7.469 0 36 322
246 294 327 7.536 0 0 271
207 51 59 5.242 0 0 339
208 49 65 5.293 0 0 303
209 26 305 5.344 96 0 316
210 320 403 5.396 45 0 326
211 96 231 5.449 0 127 320
212 153 260 5.502 28 193 345
213 150 167 5.555 139 0 344
214 66 81 5.610 0 79 295
215 18 116 5.664 0 99 300
216 235 385 5.719 92 0 249
217 184 208 5.774 73 117 316
218 89 200 5.830 67 106 302
219 107 334 5.886 0 0 275
220 118 335 5.942 0 162 335
221 119 195 5.999 201 104 387
222 151 156 6.056 0 88 281
223 185 245 6.114 0 0 298
224 106 124 6.172 0 111 318
225 170 303 6.230 0 114 287
226 225 349 6.288 9 157 344
227 140 266 6.346 0 74 337
228 25 39 6.405 0 154 346
229 194 255 6.464 0 0 267
230 172 223 6.523 64 116 309
231 182 290 6.583 138 198 291
232 230 304 6.643 135 171 368
233 60 130 6.704 183 0 306
234 265 409 6.766 167 0 324
235 262 405 6.828 0 0 310
236 48 93 6.890 0 62 273
237 144 282 6.953 173 94 338
238 136 210 7.016 0 0 324
239 12 214 7.079 0 108 289
240 83 274 7.143 149 151 331
241 4 23 7.208 0 0 315
242 171 193 7.273 0 188 334
243 213 326 7.338 143 93 366
244 324 362 7.403 146 0 332
245 85 295 7.469 0 36 322
246 294 327 7.536 0 0 271
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10STATISTICS
247 146 176 7.602 0 179 369
248 122 219 7.669 54 133 312
249 235 336 7.738 216 185 329
250 189 258 7.806 0 0 285
251 163 215 7.876 105 130 308
252 52 80 7.946 0 136 350
253 164 196 8.017 160 75 333
254 70 127 8.088 20 12 340
255 72 103 8.161 197 134 307
256 162 363 8.234 153 126 355
257 42 273 8.308 0 0 362
258 209 217 8.382 125 170 349
259 125 186 8.456 0 141 351
260 138 238 8.531 0 148 353
261 24 27 8.606 0 0 342
262 15 77 8.681 109 0 321
263 64 158 8.758 0 0 286
264 74 256 8.834 0 142 354
265 252 411 8.914 205 0 365
266 14 19 8.994 203 0 348
267 75 194 9.076 0 229 336
268 28 157 9.158 0 0 288
269 204 227 9.241 95 0 314
270 45 123 9.325 0 166 306
271 294 386 9.410 246 0 354
272 43 257 9.496 69 98 322
273 44 48 9.582 0 236 338
274 34 374 9.669 155 129 341
275 97 107 9.756 0 219 327
276 101 250 9.844 90 122 305
277 105 120 9.934 161 123 343
278 154 343 10.024 2 168 372
279 57 68 10.114 206 0 320
280 248 289 10.206 176 132 341
281 151 316 10.299 222 0 379
282 143 202 10.392 0 80 313
283 21 145 10.485 0 6 362
284 41 55 10.579 97 172 345
285 189 224 10.674 250 103 366
286 31 64 10.772 0 263 327
247 146 176 7.602 0 179 369
248 122 219 7.669 54 133 312
249 235 336 7.738 216 185 329
250 189 258 7.806 0 0 285
251 163 215 7.876 105 130 308
252 52 80 7.946 0 136 350
253 164 196 8.017 160 75 333
254 70 127 8.088 20 12 340
255 72 103 8.161 197 134 307
256 162 363 8.234 153 126 355
257 42 273 8.308 0 0 362
258 209 217 8.382 125 170 349
259 125 186 8.456 0 141 351
260 138 238 8.531 0 148 353
261 24 27 8.606 0 0 342
262 15 77 8.681 109 0 321
263 64 158 8.758 0 0 286
264 74 256 8.834 0 142 354
265 252 411 8.914 205 0 365
266 14 19 8.994 203 0 348
267 75 194 9.076 0 229 336
268 28 157 9.158 0 0 288
269 204 227 9.241 95 0 314
270 45 123 9.325 0 166 306
271 294 386 9.410 246 0 354
272 43 257 9.496 69 98 322
273 44 48 9.582 0 236 338
274 34 374 9.669 155 129 341
275 97 107 9.756 0 219 327
276 101 250 9.844 90 122 305
277 105 120 9.934 161 123 343
278 154 343 10.024 2 168 372
279 57 68 10.114 206 0 320
280 248 289 10.206 176 132 341
281 151 316 10.299 222 0 379
282 143 202 10.392 0 80 313
283 21 145 10.485 0 6 362
284 41 55 10.579 97 172 345
285 189 224 10.674 250 103 366
286 31 64 10.772 0 263 327
11STATISTICS
287 170 188 10.870 225 186 325
288 11 28 10.968 0 268 370
289 12 399 11.068 239 0 296
290 149 319 11.169 202 112 323
291 182 416 11.271 231 0 391
292 126 166 11.376 169 189 350
293 54 299 11.484 38 113 367
294 88 142 11.593 204 144 357
295 2 66 11.703 0 214 346
296 12 111 11.813 289 115 390
297 13 30 11.925 0 0 328
298 152 185 12.037 137 223 339
299 87 179 12.151 196 178 353
300 18 284 12.266 215 150 369
301 17 22 12.382 0 0 376
302 62 89 12.498 200 218 343
303 32 49 12.614 0 208 352
304 3 38 12.731 0 0 380
305 94 101 12.849 0 276 357
306 45 60 12.967 270 233 403
307 72 92 13.084 255 60 388
308 141 163 13.204 0 251 356
309 172 251 13.326 230 78 389
310 262 384 13.449 235 180 373
311 114 205 13.573 195 181 335
312 102 122 13.698 174 248 361
313 137 143 13.824 0 282 351
314 36 204 13.951 145 269 395
315 1 4 14.078 0 241 370
316 26 184 14.206 209 217 349
317 7 10 14.338 194 0 352
318 106 332 14.471 224 164 379
319 50 79 14.604 0 0 377
320 57 96 14.738 279 211 355
321 15 37 14.874 262 107 347
322 43 85 15.011 272 245 373
323 40 149 15.148 0 290 363
324 136 265 15.287 238 234 385
325 58 170 15.432 0 287 374
326 181 320 15.578 187 210 360
287 170 188 10.870 225 186 325
288 11 28 10.968 0 268 370
289 12 399 11.068 239 0 296
290 149 319 11.169 202 112 323
291 182 416 11.271 231 0 391
292 126 166 11.376 169 189 350
293 54 299 11.484 38 113 367
294 88 142 11.593 204 144 357
295 2 66 11.703 0 214 346
296 12 111 11.813 289 115 390
297 13 30 11.925 0 0 328
298 152 185 12.037 137 223 339
299 87 179 12.151 196 178 353
300 18 284 12.266 215 150 369
301 17 22 12.382 0 0 376
302 62 89 12.498 200 218 343
303 32 49 12.614 0 208 352
304 3 38 12.731 0 0 380
305 94 101 12.849 0 276 357
306 45 60 12.967 270 233 403
307 72 92 13.084 255 60 388
308 141 163 13.204 0 251 356
309 172 251 13.326 230 78 389
310 262 384 13.449 235 180 373
311 114 205 13.573 195 181 335
312 102 122 13.698 174 248 361
313 137 143 13.824 0 282 351
314 36 204 13.951 145 269 395
315 1 4 14.078 0 241 370
316 26 184 14.206 209 217 349
317 7 10 14.338 194 0 352
318 106 332 14.471 224 164 379
319 50 79 14.604 0 0 377
320 57 96 14.738 279 211 355
321 15 37 14.874 262 107 347
322 43 85 15.011 272 245 373
323 40 149 15.148 0 290 363
324 136 265 15.287 238 234 385
325 58 170 15.432 0 287 374
326 181 320 15.578 187 210 360
12STATISTICS
327 31 97 15.725 286 275 383
328 13 53 15.875 297 0 371
329 229 235 16.025 165 249 389
330 73 131 16.177 0 182 356
331 83 139 16.328 240 190 360
332 104 324 16.480 191 244 375
333 71 164 16.633 52 253 365
334 171 246 16.787 242 0 394
335 114 118 16.948 311 220 386
336 75 359 17.112 267 131 394
337 109 140 17.280 0 227 364
338 44 144 17.449 273 237 400
339 51 152 17.619 207 298 368
340 69 70 17.791 184 254 367
341 34 248 17.967 274 280 374
342 24 63 18.148 261 0 359
343 62 105 18.337 302 277 384
344 150 225 18.527 213 226 397
345 41 153 18.720 284 212 398
346 2 25 18.914 295 228 393
347 15 35 19.111 321 159 380
348 14 16 19.309 266 199 388
349 26 209 19.511 316 258 396
350 52 126 19.718 252 292 382
351 125 137 19.926 259 313 381
352 7 32 20.138 317 303 376
353 87 138 20.357 299 260 386
354 74 294 20.575 264 271 392
355 57 162 20.799 320 256 384
356 73 141 21.024 330 308 401
357 88 94 21.250 294 305 402
358 5 6 21.478 0 0 371
359 20 24 21.710 0 342 378
360 83 181 21.946 331 326 385
361 33 102 22.183 177 312 398
362 21 42 22.425 283 257 377
363 40 76 22.676 323 0 399
364 109 191 22.928 337 156 396
365 71 252 23.183 333 265 408
366 189 213 23.446 285 243 372
327 31 97 15.725 286 275 383
328 13 53 15.875 297 0 371
329 229 235 16.025 165 249 389
330 73 131 16.177 0 182 356
331 83 139 16.328 240 190 360
332 104 324 16.480 191 244 375
333 71 164 16.633 52 253 365
334 171 246 16.787 242 0 394
335 114 118 16.948 311 220 386
336 75 359 17.112 267 131 394
337 109 140 17.280 0 227 364
338 44 144 17.449 273 237 400
339 51 152 17.619 207 298 368
340 69 70 17.791 184 254 367
341 34 248 17.967 274 280 374
342 24 63 18.148 261 0 359
343 62 105 18.337 302 277 384
344 150 225 18.527 213 226 397
345 41 153 18.720 284 212 398
346 2 25 18.914 295 228 393
347 15 35 19.111 321 159 380
348 14 16 19.309 266 199 388
349 26 209 19.511 316 258 396
350 52 126 19.718 252 292 382
351 125 137 19.926 259 313 381
352 7 32 20.138 317 303 376
353 87 138 20.357 299 260 386
354 74 294 20.575 264 271 392
355 57 162 20.799 320 256 384
356 73 141 21.024 330 308 401
357 88 94 21.250 294 305 402
358 5 6 21.478 0 0 371
359 20 24 21.710 0 342 378
360 83 181 21.946 331 326 385
361 33 102 22.183 177 312 398
362 21 42 22.425 283 257 377
363 40 76 22.676 323 0 399
364 109 191 22.928 337 156 396
365 71 252 23.183 333 265 408
366 189 213 23.446 285 243 372
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13STATISTICS
367 54 69 23.709 293 340 382
368 51 230 23.983 339 232 387
369 18 146 24.269 300 247 381
370 1 11 24.555 315 288 393
371 5 13 24.845 358 328 414
372 154 189 25.139 278 366 390
373 43 262 25.433 322 310 392
374 34 58 25.734 341 325 400
375 46 104 26.038 128 332 383
376 7 17 26.347 352 301 413
377 21 50 26.664 362 319 410
378 8 20 26.990 0 359 404
379 106 151 27.323 318 281 391
380 3 15 27.658 304 347 406
381 18 125 28.003 369 351 399
382 52 54 28.352 350 367 412
383 31 46 28.720 327 375 404
384 57 62 29.097 355 343 395
385 83 136 29.478 360 324 407
386 87 114 29.868 353 335 397
387 51 119 30.261 368 221 411
388 14 72 30.655 348 307 401
389 172 229 31.062 309 329 405
390 12 154 31.473 296 372 407
391 106 182 31.958 379 291 403
392 43 74 32.474 373 354 414
393 1 2 33.039 370 346 402
394 75 171 33.649 336 334 406
395 36 57 34.263 314 384 409
396 26 109 34.885 349 364 405
397 87 150 35.517 386 344 411
398 33 41 36.155 361 345 409
399 18 40 36.823 381 363 416
400 34 44 37.521 374 338 415
401 14 73 38.288 388 356 410
402 1 88 39.086 393 357 416
403 45 106 39.886 306 391 408
404 8 31 40.778 378 383 418
405 26 172 41.687 396 389 417
406 3 75 42.667 380 394 415
367 54 69 23.709 293 340 382
368 51 230 23.983 339 232 387
369 18 146 24.269 300 247 381
370 1 11 24.555 315 288 393
371 5 13 24.845 358 328 414
372 154 189 25.139 278 366 390
373 43 262 25.433 322 310 392
374 34 58 25.734 341 325 400
375 46 104 26.038 128 332 383
376 7 17 26.347 352 301 413
377 21 50 26.664 362 319 410
378 8 20 26.990 0 359 404
379 106 151 27.323 318 281 391
380 3 15 27.658 304 347 406
381 18 125 28.003 369 351 399
382 52 54 28.352 350 367 412
383 31 46 28.720 327 375 404
384 57 62 29.097 355 343 395
385 83 136 29.478 360 324 407
386 87 114 29.868 353 335 397
387 51 119 30.261 368 221 411
388 14 72 30.655 348 307 401
389 172 229 31.062 309 329 405
390 12 154 31.473 296 372 407
391 106 182 31.958 379 291 403
392 43 74 32.474 373 354 414
393 1 2 33.039 370 346 402
394 75 171 33.649 336 334 406
395 36 57 34.263 314 384 409
396 26 109 34.885 349 364 405
397 87 150 35.517 386 344 411
398 33 41 36.155 361 345 409
399 18 40 36.823 381 363 416
400 34 44 37.521 374 338 415
401 14 73 38.288 388 356 410
402 1 88 39.086 393 357 416
403 45 106 39.886 306 391 408
404 8 31 40.778 378 383 418
405 26 172 41.687 396 389 417
406 3 75 42.667 380 394 415
14STATISTICS
407 12 83 43.704 390 385 412
408 45 71 44.756 403 365 420
409 33 36 45.931 398 395 421
410 14 21 47.120 401 377 413
411 51 87 48.477 387 397 419
412 12 52 49.836 407 382 417
413 7 14 51.425 376 410 424
414 5 43 53.163 371 392 420
415 3 34 55.073 406 400 419
416 1 18 57.064 402 399 418
417 12 26 59.068 412 405 421
418 1 8 61.626 416 404 422
419 3 51 64.379 415 411 423
420 5 45 67.820 414 408 422
421 12 33 72.644 417 409 423
422 1 5 78.126 418 420 424
423 3 12 86.907 419 421 425
424 1 7 96.042 422 413 425
425 1 3 134.134 424 423 0
Cluster Membership
Case 3 Clusters
1:Case 1 1
2:Case 2 1
3:Case 3 2
4:Case 4 1
5:Case 5 1
6:Case 6 1
7:Case 7 3
8:Case 8 1
9:Case 9 3
10:Case 10 3
11:Case 11 1
12:Case 12 2
13:Case 13 1
14:Case 14 3
407 12 83 43.704 390 385 412
408 45 71 44.756 403 365 420
409 33 36 45.931 398 395 421
410 14 21 47.120 401 377 413
411 51 87 48.477 387 397 419
412 12 52 49.836 407 382 417
413 7 14 51.425 376 410 424
414 5 43 53.163 371 392 420
415 3 34 55.073 406 400 419
416 1 18 57.064 402 399 418
417 12 26 59.068 412 405 421
418 1 8 61.626 416 404 422
419 3 51 64.379 415 411 423
420 5 45 67.820 414 408 422
421 12 33 72.644 417 409 423
422 1 5 78.126 418 420 424
423 3 12 86.907 419 421 425
424 1 7 96.042 422 413 425
425 1 3 134.134 424 423 0
Cluster Membership
Case 3 Clusters
1:Case 1 1
2:Case 2 1
3:Case 3 2
4:Case 4 1
5:Case 5 1
6:Case 6 1
7:Case 7 3
8:Case 8 1
9:Case 9 3
10:Case 10 3
11:Case 11 1
12:Case 12 2
13:Case 13 1
14:Case 14 3
15STATISTICS
15:Case 15 2
16:Case 16 3
17:Case 17 3
18:Case 18 1
19:Case 19 3
20:Case 20 1
21:Case 21 3
22:Case 22 3
23:Case 23 1
24:Case 24 1
25:Case 25 1
26:Case 26 2
27:Case 27 1
28:Case 28 1
29:Case 29 2
30:Case 30 1
31:Case 31 1
32:Case 32 3
33:Case 33 2
34:Case 34 2
35:Case 35 2
36:Case 36 2
37:Case 37 2
38:Case 38 2
39:Case 39 1
40:Case 41 1
41:Case 42 2
42:Case 43 3
43:Case 44 1
44:Case 45 2
45:Case 46 1
46:Case 47 1
47:Case 48 3
48:Case 49 2
49:Case 50 3
50:Case 51 3
51:Case 52 2
52:Case 53 2
53:Case 54 1
54:Case 55 2
15:Case 15 2
16:Case 16 3
17:Case 17 3
18:Case 18 1
19:Case 19 3
20:Case 20 1
21:Case 21 3
22:Case 22 3
23:Case 23 1
24:Case 24 1
25:Case 25 1
26:Case 26 2
27:Case 27 1
28:Case 28 1
29:Case 29 2
30:Case 30 1
31:Case 31 1
32:Case 32 3
33:Case 33 2
34:Case 34 2
35:Case 35 2
36:Case 36 2
37:Case 37 2
38:Case 38 2
39:Case 39 1
40:Case 41 1
41:Case 42 2
42:Case 43 3
43:Case 44 1
44:Case 45 2
45:Case 46 1
46:Case 47 1
47:Case 48 3
48:Case 49 2
49:Case 50 3
50:Case 51 3
51:Case 52 2
52:Case 53 2
53:Case 54 1
54:Case 55 2
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16STATISTICS
55:Case 56 2
56:Case 57 1
57:Case 59 2
58:Case 60 2
59:Case 61 2
60:Case 62 1
61:Case 63 2
62:Case 64 2
63:Case 65 1
64:Case 66 1
65:Case 67 3
66:Case 68 1
67:Case 69 2
68:Case 70 2
69:Case 71 2
70:Case 72 2
71:Case 73 1
72:Case 74 3
73:Case 75 3
74:Case 76 1
75:Case 77 2
76:Case 78 1
77:Case 79 2
78:Case 80 1
79:Case 81 3
80:Case 82 2
81:Case 83 1
82:Case 84 3
83:Case 85 2
84:Case 86 2
85:Case 87 1
86:Case 88 2
87:Case 89 2
88:Case 90 1
89:Case 91 2
90:Case 92 1
91:Case 93 2
92:Case 94 3
93:Case 95 2
94:Case 96 1
55:Case 56 2
56:Case 57 1
57:Case 59 2
58:Case 60 2
59:Case 61 2
60:Case 62 1
61:Case 63 2
62:Case 64 2
63:Case 65 1
64:Case 66 1
65:Case 67 3
66:Case 68 1
67:Case 69 2
68:Case 70 2
69:Case 71 2
70:Case 72 2
71:Case 73 1
72:Case 74 3
73:Case 75 3
74:Case 76 1
75:Case 77 2
76:Case 78 1
77:Case 79 2
78:Case 80 1
79:Case 81 3
80:Case 82 2
81:Case 83 1
82:Case 84 3
83:Case 85 2
84:Case 86 2
85:Case 87 1
86:Case 88 2
87:Case 89 2
88:Case 90 1
89:Case 91 2
90:Case 92 1
91:Case 93 2
92:Case 94 3
93:Case 95 2
94:Case 96 1
17STATISTICS
95:Case 97 2
96:Case 98 2
97:Case 99 1
98:Case 100 2
99:Case 101 2
100:Case 102 3
101:Case 103 1
102:Case 104 2
103:Case 105 3
104:Case 106 1
105:Case 107 2
106:Case 108 1
107:Case 109 1
108:Case 110 2
109:Case 111 2
110:Case 112 2
111:Case 113 2
112:Case 114 2
113:Case 115 2
114:Case 116 2
115:Case 117 1
116:Case 118 1
117:Case 119 2
118:Case 120 2
119:Case 121 2
120:Case 122 2
121:Case 123 3
122:Case 124 2
123:Case 125 1
124:Case 126 1
125:Case 127 1
126:Case 128 2
127:Case 129 2
128:Case 130 2
129:Case 131 2
130:Case 132 1
131:Case 133 3
132:Case 134 2
133:Case 135 2
134:Case 136 3
95:Case 97 2
96:Case 98 2
97:Case 99 1
98:Case 100 2
99:Case 101 2
100:Case 102 3
101:Case 103 1
102:Case 104 2
103:Case 105 3
104:Case 106 1
105:Case 107 2
106:Case 108 1
107:Case 109 1
108:Case 110 2
109:Case 111 2
110:Case 112 2
111:Case 113 2
112:Case 114 2
113:Case 115 2
114:Case 116 2
115:Case 117 1
116:Case 118 1
117:Case 119 2
118:Case 120 2
119:Case 121 2
120:Case 122 2
121:Case 123 3
122:Case 124 2
123:Case 125 1
124:Case 126 1
125:Case 127 1
126:Case 128 2
127:Case 129 2
128:Case 130 2
129:Case 131 2
130:Case 132 1
131:Case 133 3
132:Case 134 2
133:Case 135 2
134:Case 136 3
18STATISTICS
135:Case 137 1
136:Case 138 2
137:Case 139 1
138:Case 140 2
139:Case 141 2
140:Case 142 2
141:Case 143 3
142:Case 144 1
143:Case 145 1
144:Case 146 2
145:Case 147 3
146:Case 148 1
147:Case 149 2
148:Case 150 1
149:Case 151 1
150:Case 152 2
151:Case 153 1
152:Case 154 2
153:Case 155 2
154:Case 156 2
155:Case 157 2
156:Case 158 1
157:Case 159 1
158:Case 160 1
159:Case 161 1
160:Case 162 2
161:Case 163 2
162:Case 164 2
163:Case 165 3
164:Case 166 1
165:Case 167 2
166:Case 168 2
167:Case 169 2
168:Case 170 1
169:Case 171 1
170:Case 172 2
171:Case 173 2
172:Case 174 2
173:Case 175 2
174:Case 177 2
135:Case 137 1
136:Case 138 2
137:Case 139 1
138:Case 140 2
139:Case 141 2
140:Case 142 2
141:Case 143 3
142:Case 144 1
143:Case 145 1
144:Case 146 2
145:Case 147 3
146:Case 148 1
147:Case 149 2
148:Case 150 1
149:Case 151 1
150:Case 152 2
151:Case 153 1
152:Case 154 2
153:Case 155 2
154:Case 156 2
155:Case 157 2
156:Case 158 1
157:Case 159 1
158:Case 160 1
159:Case 161 1
160:Case 162 2
161:Case 163 2
162:Case 164 2
163:Case 165 3
164:Case 166 1
165:Case 167 2
166:Case 168 2
167:Case 169 2
168:Case 170 1
169:Case 171 1
170:Case 172 2
171:Case 173 2
172:Case 174 2
173:Case 175 2
174:Case 177 2
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19STATISTICS
175:Case 178 2
176:Case 179 1
177:Case 180 3
178:Case 181 2
179:Case 182 2
180:Case 183 1
181:Case 184 2
182:Case 185 1
183:Case 186 2
184:Case 187 2
185:Case 188 2
186:Case 189 1
187:Case 190 2
188:Case 191 2
189:Case 192 2
190:Case 193 2
191:Case 194 2
192:Case 195 1
193:Case 196 2
194:Case 197 2
195:Case 198 2
196:Case 199 1
197:Case 200 3
198:Case 201 2
199:Case 202 1
200:Case 203 2
201:Case 204 1
202:Case 205 1
203:Case 206 1
204:Case 207 2
205:Case 208 2
206:Case 209 2
207:Case 210 2
208:Case 211 2
209:Case 212 2
210:Case 213 2
211:Case 214 2
212:Case 215 1
213:Case 216 2
214:Case 217 2
175:Case 178 2
176:Case 179 1
177:Case 180 3
178:Case 181 2
179:Case 182 2
180:Case 183 1
181:Case 184 2
182:Case 185 1
183:Case 186 2
184:Case 187 2
185:Case 188 2
186:Case 189 1
187:Case 190 2
188:Case 191 2
189:Case 192 2
190:Case 193 2
191:Case 194 2
192:Case 195 1
193:Case 196 2
194:Case 197 2
195:Case 198 2
196:Case 199 1
197:Case 200 3
198:Case 201 2
199:Case 202 1
200:Case 203 2
201:Case 204 1
202:Case 205 1
203:Case 206 1
204:Case 207 2
205:Case 208 2
206:Case 209 2
207:Case 210 2
208:Case 211 2
209:Case 212 2
210:Case 213 2
211:Case 214 2
212:Case 215 1
213:Case 216 2
214:Case 217 2
20STATISTICS
215:Case 218 3
216:Case 219 3
217:Case 220 2
218:Case 221 1
219:Case 222 2
220:Case 223 2
221:Case 224 1
222:Case 225 1
223:Case 226 2
224:Case 227 2
225:Case 228 2
226:Case 229 2
227:Case 230 2
228:Case 231 2
229:Case 232 2
230:Case 233 2
231:Case 234 2
232:Case 235 2
233:Case 236 2
234:Case 237 1
235:Case 238 2
236:Case 239 2
237:Case 240 2
238:Case 241 2
239:Case 242 2
240:Case 243 2
241:Case 244 2
242:Case 245 2
243:Case 246 1
244:Case 247 2
245:Case 248 2
246:Case 249 2
247:Case 250 2
248:Case 251 2
249:Case 252 2
250:Case 253 1
251:Case 254 2
252:Case 255 1
253:Case 256 2
254:Case 257 2
215:Case 218 3
216:Case 219 3
217:Case 220 2
218:Case 221 1
219:Case 222 2
220:Case 223 2
221:Case 224 1
222:Case 225 1
223:Case 226 2
224:Case 227 2
225:Case 228 2
226:Case 229 2
227:Case 230 2
228:Case 231 2
229:Case 232 2
230:Case 233 2
231:Case 234 2
232:Case 235 2
233:Case 236 2
234:Case 237 1
235:Case 238 2
236:Case 239 2
237:Case 240 2
238:Case 241 2
239:Case 242 2
240:Case 243 2
241:Case 244 2
242:Case 245 2
243:Case 246 1
244:Case 247 2
245:Case 248 2
246:Case 249 2
247:Case 250 2
248:Case 251 2
249:Case 252 2
250:Case 253 1
251:Case 254 2
252:Case 255 1
253:Case 256 2
254:Case 257 2
21STATISTICS
255:Case 258 2
256:Case 259 1
257:Case 260 1
258:Case 261 2
259:Case 262 1
260:Case 263 2
261:Case 264 2
262:Case 265 1
263:Case 266 2
264:Case 267 2
265:Case 268 2
266:Case 269 2
267:Case 270 2
268:Case 271 1
269:Case 272 2
270:Case 273 2
271:Case 274 2
272:Case 275 2
273:Case 276 3
274:Case 277 2
275:Case 279 2
276:Case 280 2
277:Case 281 2
278:Case 282 2
279:Case 283 2
280:Case 284 2
281:Case 285 2
282:Case 286 2
283:Case 287 2
284:Case 288 1
285:Case 289 2
286:Case 290 2
287:Case 291 2
288:Case 292 2
289:Case 293 2
290:Case 294 1
291:Case 295 2
292:Case 296 2
293:Case 297 2
294:Case 299 1
255:Case 258 2
256:Case 259 1
257:Case 260 1
258:Case 261 2
259:Case 262 1
260:Case 263 2
261:Case 264 2
262:Case 265 1
263:Case 266 2
264:Case 267 2
265:Case 268 2
266:Case 269 2
267:Case 270 2
268:Case 271 1
269:Case 272 2
270:Case 273 2
271:Case 274 2
272:Case 275 2
273:Case 276 3
274:Case 277 2
275:Case 279 2
276:Case 280 2
277:Case 281 2
278:Case 282 2
279:Case 283 2
280:Case 284 2
281:Case 285 2
282:Case 286 2
283:Case 287 2
284:Case 288 1
285:Case 289 2
286:Case 290 2
287:Case 291 2
288:Case 292 2
289:Case 293 2
290:Case 294 1
291:Case 295 2
292:Case 296 2
293:Case 297 2
294:Case 299 1
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22STATISTICS
295:Case 300 1
296:Case 301 2
297:Case 302 2
298:Case 303 2
299:Case 304 2
300:Case 305 2
301:Case 306 2
302:Case 307 2
303:Case 308 2
304:Case 309 2
305:Case 310 2
306:Case 311 2
307:Case 312 2
308:Case 313 1
309:Case 314 2
310:Case 315 3
311:Case 316 2
312:Case 317 2
313:Case 318 2
314:Case 319 2
315:Case 320 2
316:Case 321 1
317:Case 322 1
318:Case 323 2
319:Case 324 1
320:Case 325 2
321:Case 326 1
322:Case 327 2
323:Case 328 2
324:Case 329 1
325:Case 330 2
326:Case 331 2
327:Case 332 1
328:Case 333 2
329:Case 334 2
330:Case 335 2
331:Case 336 2
332:Case 337 1
333:Case 338 2
334:Case 339 1
295:Case 300 1
296:Case 301 2
297:Case 302 2
298:Case 303 2
299:Case 304 2
300:Case 305 2
301:Case 306 2
302:Case 307 2
303:Case 308 2
304:Case 309 2
305:Case 310 2
306:Case 311 2
307:Case 312 2
308:Case 313 1
309:Case 314 2
310:Case 315 3
311:Case 316 2
312:Case 317 2
313:Case 318 2
314:Case 319 2
315:Case 320 2
316:Case 321 1
317:Case 322 1
318:Case 323 2
319:Case 324 1
320:Case 325 2
321:Case 326 1
322:Case 327 2
323:Case 328 2
324:Case 329 1
325:Case 330 2
326:Case 331 2
327:Case 332 1
328:Case 333 2
329:Case 334 2
330:Case 335 2
331:Case 336 2
332:Case 337 1
333:Case 338 2
334:Case 339 1
23STATISTICS
335:Case 340 2
336:Case 341 2
337:Case 342 1
338:Case 343 2
339:Case 344 2
340:Case 345 2
341:Case 346 2
342:Case 347 2
343:Case 348 2
344:Case 349 1
345:Case 350 1
346:Case 351 2
347:Case 352 1
348:Case 353 3
349:Case 354 2
350:Case 355 1
351:Case 356 1
352:Case 357 2
353:Case 358 2
354:Case 359 2
355:Case 360 1
356:Case 361 2
357:Case 362 2
358:Case 363 2
359:Case 364 2
360:Case 365 1
361:Case 366 2
362:Case 367 1
363:Case 368 2
364:Case 369 2
365:Case 370 2
366:Case 371 2
367:Case 372 2
368:Case 373 2
369:Case 374 1
370:Case 375 2
371:Case 376 2
372:Case 377 2
373:Case 378 2
374:Case 379 2
335:Case 340 2
336:Case 341 2
337:Case 342 1
338:Case 343 2
339:Case 344 2
340:Case 345 2
341:Case 346 2
342:Case 347 2
343:Case 348 2
344:Case 349 1
345:Case 350 1
346:Case 351 2
347:Case 352 1
348:Case 353 3
349:Case 354 2
350:Case 355 1
351:Case 356 1
352:Case 357 2
353:Case 358 2
354:Case 359 2
355:Case 360 1
356:Case 361 2
357:Case 362 2
358:Case 363 2
359:Case 364 2
360:Case 365 1
361:Case 366 2
362:Case 367 1
363:Case 368 2
364:Case 369 2
365:Case 370 2
366:Case 371 2
367:Case 372 2
368:Case 373 2
369:Case 374 1
370:Case 375 2
371:Case 376 2
372:Case 377 2
373:Case 378 2
374:Case 379 2
24STATISTICS
375:Case 380 2
376:Case 381 2
377:Case 382 2
378:Case 383 2
379:Case 384 2
380:Case 385 1
381:Case 386 2
382:Case 387 2
383:Case 388 2
384:Case 389 1
385:Case 390 2
386:Case 391 1
387:Case 392 2
388:Case 394 2
389:Case 395 2
390:Case 396 2
391:Case 397 2
392:Case 398 2
393:Case 399 2
394:Case 400 1
395:Case 401 1
396:Case 402 2
397:Case 403 1
398:Case 404 2
399:Case 405 2
400:Case 406 2
401:Case 407 2
402:Case 408 2
403:Case 409 2
404:Case 410 1
405:Case 411 1
406:Case 412 2
407:Case 413 2
408:Case 414 1
409:Case 415 2
410:Case 416 1
411:Case 417 1
412:Case 418 1
413:Case 419 1
414:Case 420 1
375:Case 380 2
376:Case 381 2
377:Case 382 2
378:Case 383 2
379:Case 384 2
380:Case 385 1
381:Case 386 2
382:Case 387 2
383:Case 388 2
384:Case 389 1
385:Case 390 2
386:Case 391 1
387:Case 392 2
388:Case 394 2
389:Case 395 2
390:Case 396 2
391:Case 397 2
392:Case 398 2
393:Case 399 2
394:Case 400 1
395:Case 401 1
396:Case 402 2
397:Case 403 1
398:Case 404 2
399:Case 405 2
400:Case 406 2
401:Case 407 2
402:Case 408 2
403:Case 409 2
404:Case 410 1
405:Case 411 1
406:Case 412 2
407:Case 413 2
408:Case 414 1
409:Case 415 2
410:Case 416 1
411:Case 417 1
412:Case 418 1
413:Case 419 1
414:Case 420 1
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25STATISTICS
415:Case 421 2
416:Case 422 1
417:Case 423 2
418:Case 424 1
419:Case 425 2
420:Case 426 1
421:Case 427 1
422:Case 428 2
423:Case 429 1
424:Case 430 2
425:Case 431 2
426:Case 432 2
415:Case 421 2
416:Case 422 1
417:Case 423 2
418:Case 424 1
419:Case 425 2
420:Case 426 1
421:Case 427 1
422:Case 428 2
423:Case 429 1
424:Case 430 2
425:Case 431 2
426:Case 432 2
26STATISTICS
27STATISTICS
Ward Method
Frequency Percent Valid Percent Cumulative
Percent
Valid
1 128 29.2 30.0 30.0
2 263 59.9 61.7 91.8
3 35 8.0 8.2 100.0
Total 426 97.0 100.0
Missing System 13 3.0
Total 439 100.0
Cluster 1 Cluster 2 Cluster 3
1:Case 1 102:Case 104 10:Case 10
101:Case 103 105:Case 107 100:Case 102
104:Case 106 108:Case 110 103:Case 105
106:Case 108 109:Case 111 121:Case 123
107:Case 109 110:Case 112 131:Case 133
11:Case 11 111:Case 113 134:Case 136
115:Case 117 112:Case 114 14:Case 14
116:Case 118 113:Case 115 141:Case 143
123:Case 125 114:Case 116 145:Case 147
124:Case 126 117:Case 119 16:Case 16
125:Case 127 118:Case 120 163:Case 165
13:Case 13 119:Case 121 17:Case 17
130:Case 132 12:Case 12 177:Case 180
135:Case 137 120:Case 122 19:Case 19
137:Case 139 122:Case 124 197:Case 200
142:Case 144 126:Case 128 21:Case 21
143:Case 145 127:Case 129 215:Case 218
146:Case 148 128:Case 130 216:Case 219
148:Case 150 129:Case 131 22:Case 22
149:Case 151 132:Case 134 273:Case 276
151:Case 153 133:Case 135 310:Case 315
156:Case 158 136:Case 138 32:Case 32
157:Case 159 138:Case 140 348:Case 353
158:Case 160 139:Case 141 42:Case 43
159:Case 161 140:Case 142 47:Case 48
164:Case 166 144:Case 146 49:Case 50
Ward Method
Frequency Percent Valid Percent Cumulative
Percent
Valid
1 128 29.2 30.0 30.0
2 263 59.9 61.7 91.8
3 35 8.0 8.2 100.0
Total 426 97.0 100.0
Missing System 13 3.0
Total 439 100.0
Cluster 1 Cluster 2 Cluster 3
1:Case 1 102:Case 104 10:Case 10
101:Case 103 105:Case 107 100:Case 102
104:Case 106 108:Case 110 103:Case 105
106:Case 108 109:Case 111 121:Case 123
107:Case 109 110:Case 112 131:Case 133
11:Case 11 111:Case 113 134:Case 136
115:Case 117 112:Case 114 14:Case 14
116:Case 118 113:Case 115 141:Case 143
123:Case 125 114:Case 116 145:Case 147
124:Case 126 117:Case 119 16:Case 16
125:Case 127 118:Case 120 163:Case 165
13:Case 13 119:Case 121 17:Case 17
130:Case 132 12:Case 12 177:Case 180
135:Case 137 120:Case 122 19:Case 19
137:Case 139 122:Case 124 197:Case 200
142:Case 144 126:Case 128 21:Case 21
143:Case 145 127:Case 129 215:Case 218
146:Case 148 128:Case 130 216:Case 219
148:Case 150 129:Case 131 22:Case 22
149:Case 151 132:Case 134 273:Case 276
151:Case 153 133:Case 135 310:Case 315
156:Case 158 136:Case 138 32:Case 32
157:Case 159 138:Case 140 348:Case 353
158:Case 160 139:Case 141 42:Case 43
159:Case 161 140:Case 142 47:Case 48
164:Case 166 144:Case 146 49:Case 50
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28STATISTICS
168:Case 170 147:Case 149 50:Case 51
169:Case 171 15:Case 15 65:Case 67
176:Case 179 150:Case 152 7:Case 7
18:Case 18 152:Case 154 72:Case 74
180:Case 183 153:Case 155 73:Case 75
182:Case 185 154:Case 156 79:Case 81
186:Case 189 155:Case 157 82:Case 84
192:Case 195 160:Case 162 9:Case 9
196:Case 199 161:Case 163 92:Case 94
199:Case 202 162:Case 164
2:Case 2 165:Case 167
20:Case 20 166:Case 168
201:Case 204 167:Case 169
202:Case 205 170:Case 172
203:Case 206 171:Case 173
212:Case 215 172:Case 174
218:Case 221 173:Case 175
221:Case 224 174:Case 177
222:Case 225 175:Case 178
23:Case 23 178:Case 181
234:Case 237 179:Case 182
24:Case 24 181:Case 184
243:Case 246 183:Case 186
25:Case 25 184:Case 187
250:Case 253 185:Case 188
252:Case 255 187:Case 190
256:Case 259 188:Case 191
257:Case 260 189:Case 192
259:Case 262 190:Case 193
262:Case 265 191:Case 194
268:Case 271 193:Case 196
27:Case 27 194:Case 197
28:Case 28 195:Case 198
284:Case 288 198:Case 201
290:Case 294 200:Case 203
294:Case 299 204:Case 207
295:Case 300 205:Case 208
30:Case 30 206:Case 209
308:Case 313 207:Case 210
31:Case 31 208:Case 211
316:Case 321 209:Case 212
317:Case 322 210:Case 213
319:Case 324 211:Case 214
168:Case 170 147:Case 149 50:Case 51
169:Case 171 15:Case 15 65:Case 67
176:Case 179 150:Case 152 7:Case 7
18:Case 18 152:Case 154 72:Case 74
180:Case 183 153:Case 155 73:Case 75
182:Case 185 154:Case 156 79:Case 81
186:Case 189 155:Case 157 82:Case 84
192:Case 195 160:Case 162 9:Case 9
196:Case 199 161:Case 163 92:Case 94
199:Case 202 162:Case 164
2:Case 2 165:Case 167
20:Case 20 166:Case 168
201:Case 204 167:Case 169
202:Case 205 170:Case 172
203:Case 206 171:Case 173
212:Case 215 172:Case 174
218:Case 221 173:Case 175
221:Case 224 174:Case 177
222:Case 225 175:Case 178
23:Case 23 178:Case 181
234:Case 237 179:Case 182
24:Case 24 181:Case 184
243:Case 246 183:Case 186
25:Case 25 184:Case 187
250:Case 253 185:Case 188
252:Case 255 187:Case 190
256:Case 259 188:Case 191
257:Case 260 189:Case 192
259:Case 262 190:Case 193
262:Case 265 191:Case 194
268:Case 271 193:Case 196
27:Case 27 194:Case 197
28:Case 28 195:Case 198
284:Case 288 198:Case 201
290:Case 294 200:Case 203
294:Case 299 204:Case 207
295:Case 300 205:Case 208
30:Case 30 206:Case 209
308:Case 313 207:Case 210
31:Case 31 208:Case 211
316:Case 321 209:Case 212
317:Case 322 210:Case 213
319:Case 324 211:Case 214
29STATISTICS
321:Case 326 213:Case 216
324:Case 329 214:Case 217
327:Case 332 217:Case 220
332:Case 337 219:Case 222
334:Case 339 220:Case 223
337:Case 342 223:Case 226
344:Case 349 224:Case 227
345:Case 350 225:Case 228
347:Case 352 226:Case 229
350:Case 355 227:Case 230
351:Case 356 228:Case 231
355:Case 360 229:Case 232
360:Case 365 230:Case 233
362:Case 367 231:Case 234
369:Case 374 232:Case 235
380:Case 385 233:Case 236
384:Case 389 235:Case 238
386:Case 391 236:Case 239
39:Case 39 237:Case 240
394:Case 400 238:Case 241
395:Case 401 239:Case 242
397:Case 403 240:Case 243
4:Case 4 241:Case 244
40:Case 41 242:Case 245
404:Case 410 244:Case 247
405:Case 411 245:Case 248
408:Case 414 246:Case 249
410:Case 416 247:Case 250
411:Case 417 248:Case 251
412:Case 418 249:Case 252
413:Case 419 251:Case 254
414:Case 420 253:Case 256
416:Case 422 254:Case 257
418:Case 424 255:Case 258
420:Case 426 258:Case 261
421:Case 427 26:Case 26
423:Case 429 260:Case 263
43:Case 44 261:Case 264
45:Case 46 263:Case 266
46:Case 47 264:Case 267
5:Case 5 265:Case 268
53:Case 54 266:Case 269
56:Case 57 267:Case 270
321:Case 326 213:Case 216
324:Case 329 214:Case 217
327:Case 332 217:Case 220
332:Case 337 219:Case 222
334:Case 339 220:Case 223
337:Case 342 223:Case 226
344:Case 349 224:Case 227
345:Case 350 225:Case 228
347:Case 352 226:Case 229
350:Case 355 227:Case 230
351:Case 356 228:Case 231
355:Case 360 229:Case 232
360:Case 365 230:Case 233
362:Case 367 231:Case 234
369:Case 374 232:Case 235
380:Case 385 233:Case 236
384:Case 389 235:Case 238
386:Case 391 236:Case 239
39:Case 39 237:Case 240
394:Case 400 238:Case 241
395:Case 401 239:Case 242
397:Case 403 240:Case 243
4:Case 4 241:Case 244
40:Case 41 242:Case 245
404:Case 410 244:Case 247
405:Case 411 245:Case 248
408:Case 414 246:Case 249
410:Case 416 247:Case 250
411:Case 417 248:Case 251
412:Case 418 249:Case 252
413:Case 419 251:Case 254
414:Case 420 253:Case 256
416:Case 422 254:Case 257
418:Case 424 255:Case 258
420:Case 426 258:Case 261
421:Case 427 26:Case 26
423:Case 429 260:Case 263
43:Case 44 261:Case 264
45:Case 46 263:Case 266
46:Case 47 264:Case 267
5:Case 5 265:Case 268
53:Case 54 266:Case 269
56:Case 57 267:Case 270
30STATISTICS
6:Case 6 269:Case 272
60:Case 62 270:Case 273
63:Case 65 271:Case 274
64:Case 66 272:Case 275
66:Case 68 274:Case 277
71:Case 73 275:Case 279
74:Case 76 276:Case 280
76:Case 78 277:Case 281
78:Case 80 278:Case 282
8:Case 8 279:Case 283
81:Case 83 280:Case 284
85:Case 87 281:Case 285
88:Case 90 282:Case 286
90:Case 92 283:Case 287
94:Case 96 285:Case 289
97:Case 99 286:Case 290
287:Case 291
288:Case 292
289:Case 293
29:Case 29
291:Case 295
292:Case 296
293:Case 297
296:Case 301
297:Case 302
298:Case 303
299:Case 304
3:Case 3
300:Case 305
301:Case 306
302:Case 307
303:Case 308
304:Case 309
305:Case 310
306:Case 311
307:Case 312
309:Case 314
311:Case 316
312:Case 317
313:Case 318
314:Case 319
315:Case 320
318:Case 323
6:Case 6 269:Case 272
60:Case 62 270:Case 273
63:Case 65 271:Case 274
64:Case 66 272:Case 275
66:Case 68 274:Case 277
71:Case 73 275:Case 279
74:Case 76 276:Case 280
76:Case 78 277:Case 281
78:Case 80 278:Case 282
8:Case 8 279:Case 283
81:Case 83 280:Case 284
85:Case 87 281:Case 285
88:Case 90 282:Case 286
90:Case 92 283:Case 287
94:Case 96 285:Case 289
97:Case 99 286:Case 290
287:Case 291
288:Case 292
289:Case 293
29:Case 29
291:Case 295
292:Case 296
293:Case 297
296:Case 301
297:Case 302
298:Case 303
299:Case 304
3:Case 3
300:Case 305
301:Case 306
302:Case 307
303:Case 308
304:Case 309
305:Case 310
306:Case 311
307:Case 312
309:Case 314
311:Case 316
312:Case 317
313:Case 318
314:Case 319
315:Case 320
318:Case 323
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31STATISTICS
320:Case 325
322:Case 327
323:Case 328
325:Case 330
326:Case 331
328:Case 333
329:Case 334
33:Case 33
330:Case 335
331:Case 336
333:Case 338
335:Case 340
336:Case 341
338:Case 343
339:Case 344
34:Case 34
340:Case 345
341:Case 346
342:Case 347
343:Case 348
346:Case 351
349:Case 354
35:Case 35
352:Case 357
353:Case 358
354:Case 359
356:Case 361
357:Case 362
358:Case 363
359:Case 364
36:Case 36
361:Case 366
363:Case 368
364:Case 369
365:Case 370
366:Case 371
367:Case 372
368:Case 373
37:Case 37
370:Case 375
371:Case 376
372:Case 377
373:Case 378
320:Case 325
322:Case 327
323:Case 328
325:Case 330
326:Case 331
328:Case 333
329:Case 334
33:Case 33
330:Case 335
331:Case 336
333:Case 338
335:Case 340
336:Case 341
338:Case 343
339:Case 344
34:Case 34
340:Case 345
341:Case 346
342:Case 347
343:Case 348
346:Case 351
349:Case 354
35:Case 35
352:Case 357
353:Case 358
354:Case 359
356:Case 361
357:Case 362
358:Case 363
359:Case 364
36:Case 36
361:Case 366
363:Case 368
364:Case 369
365:Case 370
366:Case 371
367:Case 372
368:Case 373
37:Case 37
370:Case 375
371:Case 376
372:Case 377
373:Case 378
32STATISTICS
374:Case 379
375:Case 380
376:Case 381
377:Case 382
378:Case 383
379:Case 384
38:Case 38
381:Case 386
382:Case 387
383:Case 388
385:Case 390
387:Case 392
388:Case 394
389:Case 395
390:Case 396
391:Case 397
392:Case 398
393:Case 399
396:Case 402
398:Case 404
399:Case 405
400:Case 406
401:Case 407
402:Case 408
403:Case 409
406:Case 412
407:Case 413
409:Case 415
41:Case 42
415:Case 421
417:Case 423
419:Case 425
422:Case 428
424:Case 430
425:Case 431
426:Case 432
44:Case 45
48:Case 49
51:Case 52
52:Case 53
54:Case 55
55:Case 56
57:Case 59
374:Case 379
375:Case 380
376:Case 381
377:Case 382
378:Case 383
379:Case 384
38:Case 38
381:Case 386
382:Case 387
383:Case 388
385:Case 390
387:Case 392
388:Case 394
389:Case 395
390:Case 396
391:Case 397
392:Case 398
393:Case 399
396:Case 402
398:Case 404
399:Case 405
400:Case 406
401:Case 407
402:Case 408
403:Case 409
406:Case 412
407:Case 413
409:Case 415
41:Case 42
415:Case 421
417:Case 423
419:Case 425
422:Case 428
424:Case 430
425:Case 431
426:Case 432
44:Case 45
48:Case 49
51:Case 52
52:Case 53
54:Case 55
55:Case 56
57:Case 59
33STATISTICS
58:Case 60
59:Case 61
61:Case 63
62:Case 64
67:Case 69
68:Case 70
69:Case 71
70:Case 72
75:Case 77
77:Case 79
80:Case 82
83:Case 85
84:Case 86
86:Case 88
87:Case 89
89:Case 91
91:Case 93
93:Case 95
95:Case 97
96:Case 98
98:Case 100
99:Case 101
58:Case 60
59:Case 61
61:Case 63
62:Case 64
67:Case 69
68:Case 70
69:Case 71
70:Case 72
75:Case 77
77:Case 79
80:Case 82
83:Case 85
84:Case 86
86:Case 88
87:Case 89
89:Case 91
91:Case 93
93:Case 95
95:Case 97
96:Case 98
98:Case 100
99:Case 101
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34STATISTICS
ANOVA
Sum of Squares df Mean Square F Sig.
Total Optimism
Between Groups 2219.527 2 1109.763 75.561 .000
Within Groups 6212.576 423 14.687
Total 8432.103 425
Total positive affect
Between Groups 4177.210 2 2088.605 49.427 .000
Within Groups 17874.276 423 42.256
Total 22051.486 425
Total negative affect
Between Groups 10522.060 2 5261.030 204.051 .000
Within Groups 10906.184 423 25.783
Total 21428.244 425
Total life satisfaction
Between Groups 4763.542 2 2381.771 67.450 .000
Within Groups 14936.787 423 35.312
Total 19700.329 425
Total perceived stress
Between Groups 7224.305 2 3612.153 204.774 .000
Within Groups 7461.601 423 17.640
Total 14685.906 425
Total Self esteem
Between Groups 7034.253 2 3517.127 286.143 .000
Within Groups 5199.308 423 12.292
Total 12233.561 425
Total social desirability
Between Groups 155.207 2 77.604 20.487 .000
Within Groups 1602.279 423 3.788
Total 1757.486 425
Part I
1. a) According to the hierarchical clustering, in dissimilarity matrix, we calculated the one-
to-one distances between the 426 samples among 439 samples.
ANOVA
Sum of Squares df Mean Square F Sig.
Total Optimism
Between Groups 2219.527 2 1109.763 75.561 .000
Within Groups 6212.576 423 14.687
Total 8432.103 425
Total positive affect
Between Groups 4177.210 2 2088.605 49.427 .000
Within Groups 17874.276 423 42.256
Total 22051.486 425
Total negative affect
Between Groups 10522.060 2 5261.030 204.051 .000
Within Groups 10906.184 423 25.783
Total 21428.244 425
Total life satisfaction
Between Groups 4763.542 2 2381.771 67.450 .000
Within Groups 14936.787 423 35.312
Total 19700.329 425
Total perceived stress
Between Groups 7224.305 2 3612.153 204.774 .000
Within Groups 7461.601 423 17.640
Total 14685.906 425
Total Self esteem
Between Groups 7034.253 2 3517.127 286.143 .000
Within Groups 5199.308 423 12.292
Total 12233.561 425
Total social desirability
Between Groups 155.207 2 77.604 20.487 .000
Within Groups 1602.279 423 3.788
Total 1757.486 425
Part I
1. a) According to the hierarchical clustering, in dissimilarity matrix, we calculated the one-
to-one distances between the 426 samples among 439 samples.
35STATISTICS
The number of cases in Cluster 1 is 128 (29.2%), Cluster 2 is 263 (59.9%) and Cluster 3
is 35 (8.0%).
Part II
1. b) We have considered three clusters and calculated the Ward linkage. Here also the total
number of cases is 426. The Ward linkage dendogram is also executed in the analysis.
The cases in each cluster have been provided in a new table.
Part III
1. c) The Ward linkage is single hierarchical linkage. This kind of agglomerative
hierarchical clustering created the dendogram diagram. Most of the samples are located
in cluster 2.
There are statistically significant differences between the variables used to study outdoor
lifestyle and the cluster means at 0.05 level of significance (p-value < 0.000).
Answer 2
Initial Cluster Centers
Cluster
1 2 3
Total Optimism 26 9 19
Total Self esteem 40 23 31
Total positive affect 49 20 15
Total negative affect 36 39 14
Total life satisfaction 33 5 33
Total perceived stress 31 46 19
Total social desirability 3 2 8
Iteration Historya
Iteration Change in Cluster Centers
The number of cases in Cluster 1 is 128 (29.2%), Cluster 2 is 263 (59.9%) and Cluster 3
is 35 (8.0%).
Part II
1. b) We have considered three clusters and calculated the Ward linkage. Here also the total
number of cases is 426. The Ward linkage dendogram is also executed in the analysis.
The cases in each cluster have been provided in a new table.
Part III
1. c) The Ward linkage is single hierarchical linkage. This kind of agglomerative
hierarchical clustering created the dendogram diagram. Most of the samples are located
in cluster 2.
There are statistically significant differences between the variables used to study outdoor
lifestyle and the cluster means at 0.05 level of significance (p-value < 0.000).
Answer 2
Initial Cluster Centers
Cluster
1 2 3
Total Optimism 26 9 19
Total Self esteem 40 23 31
Total positive affect 49 20 15
Total negative affect 36 39 14
Total life satisfaction 33 5 33
Total perceived stress 31 46 19
Total social desirability 3 2 8
Iteration Historya
Iteration Change in Cluster Centers
36STATISTICS
1 2 3
1 21.701 22.738 20.581
2 2.347 .725 3.255
3 .011 .009 .025
4 5.030E-005 .000 .000
5 2.329E-007 1.181E-006 1.552E-006
6 1.078E-009 1.389E-008 1.213E-008
7 5.000E-012 1.634E-010 9.475E-011
8 2.436E-014 1.921E-012 7.363E-013
9 .000 2.119E-014 1.020E-014
10 .000 .000 .000
a. Convergence achieved due to no or small change in
cluster centers. The maximum absolute coordinate
change for any center is .000. The current iteration is 10.
The minimum distance between initial centers is 44.034.
Final Cluster Centers
Cluster
1 2 3
Total Optimism 24 19 21
Total Self esteem 36 28 34
Total positive affect 39 28 30
Total negative affect 17 28 16
Total life satisfaction 27 16 20
Total perceived stress 24 34 26
Total social desirability 5 5 6
1 2 3
1 21.701 22.738 20.581
2 2.347 .725 3.255
3 .011 .009 .025
4 5.030E-005 .000 .000
5 2.329E-007 1.181E-006 1.552E-006
6 1.078E-009 1.389E-008 1.213E-008
7 5.000E-012 1.634E-010 9.475E-011
8 2.436E-014 1.921E-012 7.363E-013
9 .000 2.119E-014 1.020E-014
10 .000 .000 .000
a. Convergence achieved due to no or small change in
cluster centers. The maximum absolute coordinate
change for any center is .000. The current iteration is 10.
The minimum distance between initial centers is 44.034.
Final Cluster Centers
Cluster
1 2 3
Total Optimism 24 19 21
Total Self esteem 36 28 34
Total positive affect 39 28 30
Total negative affect 17 28 16
Total life satisfaction 27 16 20
Total perceived stress 24 34 26
Total social desirability 5 5 6
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37STATISTICS
Cluster Membership
Case Number Cluster Distance
1 1 23.688
2 1 18.579
3 3 20.534
4 1 22.973
5 3 23.389
6 3 23.150
7 2 24.854
8 2 23.251
9 2 22.970
10 2 23.080
11 1 16.504
12 1 12.799
13 2 20.732
Cluster Membership
Case Number Cluster Distance
1 1 23.688
2 1 18.579
3 3 20.534
4 1 22.973
5 3 23.389
6 3 23.150
7 2 24.854
8 2 23.251
9 2 22.970
10 2 23.080
11 1 16.504
12 1 12.799
13 2 20.732
38STATISTICS
14 2 19.281
15 3 14.206
16 2 14.403
17 2 17.638
18 2 13.826
19 2 16.501
20 2 17.938
21 2 12.194
22 2 18.507
23 1 17.226
24 2 14.168
25 2 16.685
26 1 11.956
27 2 14.660
28 2 20.688
29 3 11.743
30 2 20.198
31 2 18.507
32 2 16.310
33 3 11.705
34 3 11.979
35 3 13.405
36 1 14.153
37 3 12.281
38 3 19.107
39 2 16.057
40 . .
41 2 24.166
42 1 17.872
43 2 20.039
44 2 11.920
45 1 17.454
46 1 17.057
47 1 19.714
48 2 10.909
49 3 13.721
50 2 14.916
51 2 15.740
52 3 8.763
53 1 15.801
14 2 19.281
15 3 14.206
16 2 14.403
17 2 17.638
18 2 13.826
19 2 16.501
20 2 17.938
21 2 12.194
22 2 18.507
23 1 17.226
24 2 14.168
25 2 16.685
26 1 11.956
27 2 14.660
28 2 20.688
29 3 11.743
30 2 20.198
31 2 18.507
32 2 16.310
33 3 11.705
34 3 11.979
35 3 13.405
36 1 14.153
37 3 12.281
38 3 19.107
39 2 16.057
40 . .
41 2 24.166
42 1 17.872
43 2 20.039
44 2 11.920
45 1 17.454
46 1 17.057
47 1 19.714
48 2 10.909
49 3 13.721
50 2 14.916
51 2 15.740
52 3 8.763
53 1 15.801
39STATISTICS
54 2 14.348
55 3 14.056
56 1 16.455
57 1 17.735
58 . .
59 1 13.765
60 3 11.296
61 3 13.324
62 1 16.705
63 3 10.544
64 1 12.829
65 2 12.219
66 2 15.102
67 2 16.245
68 2 14.080
69 1 18.580
70 1 11.859
71 1 11.105
72 1 10.674
73 3 12.870
74 2 10.068
75 2 10.990
76 3 14.578
77 1 15.539
78 2 15.417
79 3 9.689
80 2 12.845
81 2 13.601
82 1 16.690
83 1 12.676
84 2 11.172
85 1 9.267
86 1 11.351
87 3 12.271
88 3 11.799
89 1 16.616
90 2 17.628
91 1 8.449
92 1 12.467
93 1 15.755
54 2 14.348
55 3 14.056
56 1 16.455
57 1 17.735
58 . .
59 1 13.765
60 3 11.296
61 3 13.324
62 1 16.705
63 3 10.544
64 1 12.829
65 2 12.219
66 2 15.102
67 2 16.245
68 2 14.080
69 1 18.580
70 1 11.859
71 1 11.105
72 1 10.674
73 3 12.870
74 2 10.068
75 2 10.990
76 3 14.578
77 1 15.539
78 2 15.417
79 3 9.689
80 2 12.845
81 2 13.601
82 1 16.690
83 1 12.676
84 2 11.172
85 1 9.267
86 1 11.351
87 3 12.271
88 3 11.799
89 1 16.616
90 2 17.628
91 1 8.449
92 1 12.467
93 1 15.755
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40STATISTICS
94 2 8.652
95 1 14.356
96 1 15.195
97 1 16.270
98 1 10.369
99 2 10.184
100 3 14.446
101 1 7.253
102 2 8.307
103 1 8.984
104 3 14.478
105 2 6.680
106 2 13.651
107 1 11.842
108 3 10.834
109 2 12.101
110 3 10.982
111 1 18.247
112 1 15.334
113 1 7.807
114 1 15.917
115 3 11.844
116 3 9.787
117 1 11.650
118 2 10.276
119 1 11.394
120 3 12.661
121 2 16.156
122 1 10.862
123 2 7.734
124 3 14.497
125 1 16.247
126 3 11.562
127 2 14.143
128 1 12.101
129 1 13.023
130 1 9.722
131 1 12.680
132 1 13.396
133 2 5.934
94 2 8.652
95 1 14.356
96 1 15.195
97 1 16.270
98 1 10.369
99 2 10.184
100 3 14.446
101 1 7.253
102 2 8.307
103 1 8.984
104 3 14.478
105 2 6.680
106 2 13.651
107 1 11.842
108 3 10.834
109 2 12.101
110 3 10.982
111 1 18.247
112 1 15.334
113 1 7.807
114 1 15.917
115 3 11.844
116 3 9.787
117 1 11.650
118 2 10.276
119 1 11.394
120 3 12.661
121 2 16.156
122 1 10.862
123 2 7.734
124 3 14.497
125 1 16.247
126 3 11.562
127 2 14.143
128 1 12.101
129 1 13.023
130 1 9.722
131 1 12.680
132 1 13.396
133 2 5.934
41STATISTICS
134 3 14.340
135 1 10.870
136 2 7.350
137 3 10.294
138 1 13.803
139 2 15.897
140 1 14.323
141 1 9.254
142 1 8.236
143 2 9.020
144 1 13.854
145 2 12.415
146 1 8.635
147 2 8.401
148 2 12.934
149 1 10.718
150 1 12.430
151 1 13.680
152 3 13.311
153 2 9.576
154 3 7.739
155 1 14.158
156 3 9.239
157 1 13.788
158 2 11.023
159 1 12.313
160 2 11.933
161 1 8.683
162 3 10.275
163 1 11.570
164 1 8.941
165 2 8.067
166 3 13.157
167 1 9.458
168 1 9.606
169 3 11.925
170 3 7.944
171 2 11.137
172 3 8.508
173 3 9.764
134 3 14.340
135 1 10.870
136 2 7.350
137 3 10.294
138 1 13.803
139 2 15.897
140 1 14.323
141 1 9.254
142 1 8.236
143 2 9.020
144 1 13.854
145 2 12.415
146 1 8.635
147 2 8.401
148 2 12.934
149 1 10.718
150 1 12.430
151 1 13.680
152 3 13.311
153 2 9.576
154 3 7.739
155 1 14.158
156 3 9.239
157 1 13.788
158 2 11.023
159 1 12.313
160 2 11.933
161 1 8.683
162 3 10.275
163 1 11.570
164 1 8.941
165 2 8.067
166 3 13.157
167 1 9.458
168 1 9.606
169 3 11.925
170 3 7.944
171 2 11.137
172 3 8.508
173 3 9.764
42STATISTICS
174 3 8.509
175 3 9.084
176 . .
177 1 10.415
178 1 11.557
179 2 8.204
180 2 7.644
181 1 11.314
182 1 12.539
183 1 11.382
184 1 6.490
185 1 9.792
186 1 14.839
187 1 8.445
188 3 9.823
189 2 9.981
190 1 8.755
191 3 7.505
192 1 12.476
193 2 10.873
194 1 8.247
195 2 10.753
196 3 8.710
197 1 12.411
198 2 11.592
199 3 10.716
200 2 9.589
201 1 13.682
202 3 10.850
203 1 8.449
204 3 8.198
205 2 15.231
206 2 13.912
207 1 10.478
208 3 12.425
209 1 8.832
210 3 16.353
211 1 6.609
212 1 5.799
213 1 12.710
174 3 8.509
175 3 9.084
176 . .
177 1 10.415
178 1 11.557
179 2 8.204
180 2 7.644
181 1 11.314
182 1 12.539
183 1 11.382
184 1 6.490
185 1 9.792
186 1 14.839
187 1 8.445
188 3 9.823
189 2 9.981
190 1 8.755
191 3 7.505
192 1 12.476
193 2 10.873
194 1 8.247
195 2 10.753
196 3 8.710
197 1 12.411
198 2 11.592
199 3 10.716
200 2 9.589
201 1 13.682
202 3 10.850
203 1 8.449
204 3 8.198
205 2 15.231
206 2 13.912
207 1 10.478
208 3 12.425
209 1 8.832
210 3 16.353
211 1 6.609
212 1 5.799
213 1 12.710
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43STATISTICS
214 1 8.504
215 1 16.032
216 1 6.614
217 1 10.197
218 2 9.572
219 2 5.210
220 1 8.124
221 2 12.563
222 1 14.060
223 1 9.982
224 3 12.354
225 2 13.632
226 3 10.329
227 1 8.069
228 3 12.248
229 1 8.414
230 1 13.318
231 1 9.540
232 3 6.484
233 3 7.948
234 1 6.759
235 3 5.987
236 1 9.067
237 1 15.726
238 3 9.034
239 3 11.088
240 1 13.505
241 1 8.149
242 2 12.077
243 1 13.629
244 1 8.473
245 1 11.066
246 2 5.747
247 1 9.579
248 3 12.578
249 2 15.070
250 1 6.070
251 3 7.439
252 1 9.460
253 3 9.682
214 1 8.504
215 1 16.032
216 1 6.614
217 1 10.197
218 2 9.572
219 2 5.210
220 1 8.124
221 2 12.563
222 1 14.060
223 1 9.982
224 3 12.354
225 2 13.632
226 3 10.329
227 1 8.069
228 3 12.248
229 1 8.414
230 1 13.318
231 1 9.540
232 3 6.484
233 3 7.948
234 1 6.759
235 3 5.987
236 1 9.067
237 1 15.726
238 3 9.034
239 3 11.088
240 1 13.505
241 1 8.149
242 2 12.077
243 1 13.629
244 1 8.473
245 1 11.066
246 2 5.747
247 1 9.579
248 3 12.578
249 2 15.070
250 1 6.070
251 3 7.439
252 1 9.460
253 3 9.682
44STATISTICS
254 3 7.542
255 3 16.823
256 1 8.192
257 3 7.945
258 1 8.856
259 2 13.636
260 2 9.586
261 1 12.589
262 2 10.669
263 1 10.020
264 3 13.026
265 1 11.171
266 1 8.479
267 1 9.821
268 1 7.674
269 1 10.620
270 1 6.436
271 2 6.619
272 3 10.060
273 1 8.079
274 1 7.807
275 1 9.769
276 2 15.182
277 1 8.333
278 . .
279 3 8.820
280 1 8.229
281 1 7.976
282 1 10.624
283 1 7.661
284 3 6.768
285 1 11.673
286 1 9.671
287 1 7.455
288 3 9.272
289 1 10.910
290 1 6.566
291 1 6.725
292 3 8.147
293 3 6.927
254 3 7.542
255 3 16.823
256 1 8.192
257 3 7.945
258 1 8.856
259 2 13.636
260 2 9.586
261 1 12.589
262 2 10.669
263 1 10.020
264 3 13.026
265 1 11.171
266 1 8.479
267 1 9.821
268 1 7.674
269 1 10.620
270 1 6.436
271 2 6.619
272 3 10.060
273 1 8.079
274 1 7.807
275 1 9.769
276 2 15.182
277 1 8.333
278 . .
279 3 8.820
280 1 8.229
281 1 7.976
282 1 10.624
283 1 7.661
284 3 6.768
285 1 11.673
286 1 9.671
287 1 7.455
288 3 9.272
289 1 10.910
290 1 6.566
291 1 6.725
292 3 8.147
293 3 6.927
45STATISTICS
294 3 9.971
295 1 9.297
296 3 6.389
297 1 6.592
298 . .
299 2 14.008
300 3 11.246
301 3 15.036
302 3 5.954
303 3 6.158
304 1 9.151
305 1 8.593
306 3 5.103
307 3 3.411
308 3 7.183
309 3 11.922
310 1 9.129
311 3 11.211
312 3 10.954
313 1 9.325
314 1 7.854
315 2 6.536
316 1 8.322
317 3 5.325
318 3 8.593
319 1 9.722
320 3 8.135
321 2 11.197
322 2 10.680
323 3 7.668
324 2 12.975
325 1 7.183
326 3 9.111
327 1 4.987
328 3 9.096
329 1 13.838
330 1 5.964
331 1 4.302
332 2 9.479
333 1 10.972
294 3 9.971
295 1 9.297
296 3 6.389
297 1 6.592
298 . .
299 2 14.008
300 3 11.246
301 3 15.036
302 3 5.954
303 3 6.158
304 1 9.151
305 1 8.593
306 3 5.103
307 3 3.411
308 3 7.183
309 3 11.922
310 1 9.129
311 3 11.211
312 3 10.954
313 1 9.325
314 1 7.854
315 2 6.536
316 1 8.322
317 3 5.325
318 3 8.593
319 1 9.722
320 3 8.135
321 2 11.197
322 2 10.680
323 3 7.668
324 2 12.975
325 1 7.183
326 3 9.111
327 1 4.987
328 3 9.096
329 1 13.838
330 1 5.964
331 1 4.302
332 2 9.479
333 1 10.972
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46STATISTICS
334 3 7.906
335 3 6.738
336 1 9.185
337 1 12.424
338 1 5.171
339 2 14.046
340 3 13.986
341 3 4.016
342 3 9.596
343 1 6.362
344 1 7.420
345 3 5.192
346 1 4.756
347 1 10.089
348 1 8.420
349 2 15.759
350 2 9.820
351 3 9.016
352 2 13.549
353 2 9.748
354 3 13.116
355 2 8.778
356 3 9.679
357 1 6.246
358 3 12.127
359 1 7.041
360 3 13.387
361 3 4.928
362 3 7.654
363 3 5.600
364 1 10.597
365 3 7.777
366 1 6.869
367 3 12.294
368 1 9.423
369 3 11.187
370 1 6.716
371 1 7.182
372 1 13.535
373 3 5.749
334 3 7.906
335 3 6.738
336 1 9.185
337 1 12.424
338 1 5.171
339 2 14.046
340 3 13.986
341 3 4.016
342 3 9.596
343 1 6.362
344 1 7.420
345 3 5.192
346 1 4.756
347 1 10.089
348 1 8.420
349 2 15.759
350 2 9.820
351 3 9.016
352 2 13.549
353 2 9.748
354 3 13.116
355 2 8.778
356 3 9.679
357 1 6.246
358 3 12.127
359 1 7.041
360 3 13.387
361 3 4.928
362 3 7.654
363 3 5.600
364 1 10.597
365 3 7.777
366 1 6.869
367 3 12.294
368 1 9.423
369 3 11.187
370 1 6.716
371 1 7.182
372 1 13.535
373 3 5.749
47STATISTICS
374 1 12.082
375 1 7.410
376 3 6.206
377 3 12.957
378 1 4.756
379 3 8.129
380 1 5.588
381 1 6.979
382 3 8.684
383 3 11.451
384 3 6.001
385 2 14.869
386 1 11.058
387 1 9.634
388 1 7.030
389 3 6.745
390 3 7.441
391 2 16.220
392 3 8.196
393 . .
394 3 6.217
395 1 3.481
396 1 8.190
397 1 7.931
398 3 8.397
399 1 7.759
400 1 7.997
401 3 8.567
402 1 8.017
403 3 12.229
404 1 7.668
405 1 12.894
406 3 5.771
407 1 4.758
408 1 5.506
409 3 6.446
410 3 5.775
411 1 12.606
412 3 9.684
413 1 3.954
374 1 12.082
375 1 7.410
376 3 6.206
377 3 12.957
378 1 4.756
379 3 8.129
380 1 5.588
381 1 6.979
382 3 8.684
383 3 11.451
384 3 6.001
385 2 14.869
386 1 11.058
387 1 9.634
388 1 7.030
389 3 6.745
390 3 7.441
391 2 16.220
392 3 8.196
393 . .
394 3 6.217
395 1 3.481
396 1 8.190
397 1 7.931
398 3 8.397
399 1 7.759
400 1 7.997
401 3 8.567
402 1 8.017
403 3 12.229
404 1 7.668
405 1 12.894
406 3 5.771
407 1 4.758
408 1 5.506
409 3 6.446
410 3 5.775
411 1 12.606
412 3 9.684
413 1 3.954
48STATISTICS
414 3 10.555
415 1 10.348
416 3 8.945
417 2 13.605
418 1 10.898
419 1 9.283
420 3 9.646
421 1 7.803
422 3 14.389
423 3 9.174
424 1 8.572
425 1 9.539
426 3 6.906
427 2 10.174
428 3 7.191
429 1 9.118
430 1 4.713
431 1 7.114
432 1 6.311
433 . .
434 . .
435 . .
436 . .
437 . .
438 . .
439 . .
Distances between Final Cluster Centers
Cluster 1 2 3
1 23.722 12.005
2 23.722 16.726
3 12.005 16.726
ANOVA
Cluster Error F Sig.
Mean Square df Mean Square df
414 3 10.555
415 1 10.348
416 3 8.945
417 2 13.605
418 1 10.898
419 1 9.283
420 3 9.646
421 1 7.803
422 3 14.389
423 3 9.174
424 1 8.572
425 1 9.539
426 3 6.906
427 2 10.174
428 3 7.191
429 1 9.118
430 1 4.713
431 1 7.114
432 1 6.311
433 . .
434 . .
435 . .
436 . .
437 . .
438 . .
439 . .
Distances between Final Cluster Centers
Cluster 1 2 3
1 23.722 12.005
2 23.722 16.726
3 12.005 16.726
ANOVA
Cluster Error F Sig.
Mean Square df Mean Square df
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49STATISTICS
Total Optimism 1142.863 2 14.530 423 78.653 .000
Total Self esteem 2544.653 2 16.889 423 150.665 .000
Total positive affect 5603.862 2 25.635 423 218.599 .000
Total negative affect 4770.436 2 28.103 423 169.751 .000
Total life satisfaction 3954.891 2 27.874 423 141.886 .000
Total perceived stress 3267.305 2 19.270 423 169.552 .000
Total social desirability 26.178 2 4.031 423 6.494 .002
The F tests should be used only for descriptive purposes because the clusters have been chosen to maximize
the differences among cases in different clusters. The observed significance levels are not corrected for this
and thus cannot be interpreted as tests of the hypothesis that the cluster means are equal.
Number of Cases in each
Cluster
Cluster
1 196.000
2 98.000
3 132.000
Valid 426.000
Missing 13.000
Part I
2. a) The k-means clustering for three different clusters indicate that most of the samples are
located in cluster 1 (196) whereas the least number of samples are located in cluster 2
(98). The number of samples is 426 for k-mean clustering.
Part II
2. b) There are three clusters calculated for seven variables over 426 samples.
Part III
2.c) The Distances between cluster 1 and cluster 2 is maximum (23.722) and the distances
between cluster 1 and cluster 3 is minimum (12.005).
Total Optimism 1142.863 2 14.530 423 78.653 .000
Total Self esteem 2544.653 2 16.889 423 150.665 .000
Total positive affect 5603.862 2 25.635 423 218.599 .000
Total negative affect 4770.436 2 28.103 423 169.751 .000
Total life satisfaction 3954.891 2 27.874 423 141.886 .000
Total perceived stress 3267.305 2 19.270 423 169.552 .000
Total social desirability 26.178 2 4.031 423 6.494 .002
The F tests should be used only for descriptive purposes because the clusters have been chosen to maximize
the differences among cases in different clusters. The observed significance levels are not corrected for this
and thus cannot be interpreted as tests of the hypothesis that the cluster means are equal.
Number of Cases in each
Cluster
Cluster
1 196.000
2 98.000
3 132.000
Valid 426.000
Missing 13.000
Part I
2. a) The k-means clustering for three different clusters indicate that most of the samples are
located in cluster 1 (196) whereas the least number of samples are located in cluster 2
(98). The number of samples is 426 for k-mean clustering.
Part II
2. b) There are three clusters calculated for seven variables over 426 samples.
Part III
2.c) The Distances between cluster 1 and cluster 2 is maximum (23.722) and the distances
between cluster 1 and cluster 3 is minimum (12.005).
50STATISTICS
The mean-square error is higher in case of positive effect and negative effect. The life
satisfaction is higher than total optimism, total life satisfaction and total perceived stress in this
case. The significant p-values all are less than 0.05 when F-test in handled. The F-test is used for
descriptive purposes as the clusters have been chosen to optimize the differences among cases in
different clusters. The hypothesis of equal cluster means is rejected at 95% confidence level.
Answer 3
The mean-square error is higher in case of positive effect and negative effect. The life
satisfaction is higher than total optimism, total life satisfaction and total perceived stress in this
case. The significant p-values all are less than 0.05 when F-test in handled. The F-test is used for
descriptive purposes as the clusters have been chosen to optimize the differences among cases in
different clusters. The hypothesis of equal cluster means is rejected at 95% confidence level.
Answer 3
51STATISTICS
Part I
3. a) In two-step cluster analysis, samples in cluster 2 (187, 43.9%) is highest followed by
samples in cluster 1 (164, 38.5%). The Lowest number of samples in cluster 3 is 75 and
17.6% in percentage.
Part II
3.b) The sharing percentages of seven variables of 426 samples are clustered in the output
table.
Part III
3. c) Both total perceived stress and total negative effect is highest in cluster 3 and lowest in
cluster 1. Conversely, the total self-esteem, total optimism, total positive effect, total
social desirability and total life satisfaction is highest in cluster 1 and lowest in cluster 3.
Answer 4
4. For k-means and two-step clustering, most of the samples lie in cluster 2. However, in
hierarchical clustering, most of the samples lie in cluster 1. In all the clusters, the minimum
numbers of samples lie in cluster 3. The clusters took into account the 426 samples in each case.
All the clustering methods were incorporated with the division of three clusters.
Part I
3. a) In two-step cluster analysis, samples in cluster 2 (187, 43.9%) is highest followed by
samples in cluster 1 (164, 38.5%). The Lowest number of samples in cluster 3 is 75 and
17.6% in percentage.
Part II
3.b) The sharing percentages of seven variables of 426 samples are clustered in the output
table.
Part III
3. c) Both total perceived stress and total negative effect is highest in cluster 3 and lowest in
cluster 1. Conversely, the total self-esteem, total optimism, total positive effect, total
social desirability and total life satisfaction is highest in cluster 1 and lowest in cluster 3.
Answer 4
4. For k-means and two-step clustering, most of the samples lie in cluster 2. However, in
hierarchical clustering, most of the samples lie in cluster 1. In all the clusters, the minimum
numbers of samples lie in cluster 3. The clusters took into account the 426 samples in each case.
All the clustering methods were incorporated with the division of three clusters.
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