(PDF) Data Analysis in Management with SPSS Software

This report is on "data manipulation in SPSS". Several variables have been used in the present report, which is being analyzed by implicating several tools. This project is consisting of information based on operating the SPSS tools in analyzing the outcomes through implicated tests. SPSS data set About the 256 samples have been collected on the various variables coded and labeled to have effective outcomes on the data set. It will be effective and helpful with reference to bringing accurate outcomes through used information.

DATA MANIPULATION
AND STATISTICAL
MANAGEMENT: SPSS

TABLE OF CONTENTS
INTRODUCTION...........................................................................................................................1
1. SPSS data set...........................................................................................................................1
2. Calculated BMI........................................................................................................................1
3. Creation of low activity...........................................................................................................1
4. Producing a single summarized on each patient group...........................................................2
5. Commenting on the results......................................................................................................2
6. Producing a publication quality bar chart of mean activity values..........................................3
7. Justification of chosen Plot......................................................................................................6
8. Testing the variables................................................................................................................6
9. Analysing the relationship between Low-Activity and patient groups:..................................8
10. Regression analysis on Activity and IBM.............................................................................9
11. Description on the used Statistical methods........................................................................11
12. Presenting comments on effective findings.........................................................................12
CONCLUSION..............................................................................................................................12
REFERENCES..............................................................................................................................13
APPENDIX....................................................................................................................................14

INTRODUCTION
Data manipulation is the biggest concern which is required to be considered to have the
accurate and adequate analysis over the data set. However, in the present report there have been
use of several variables which are being analysed through implicating the several tools. there will
be analysis over data set by measuring various statistical tests. It will be effective and helpful
with reference to bring accurate outcomes through used information. Moreover, the justification
on used information had been given by the professionals which is relevant with improving the
operational skills. This project is consisting of information based on operating the SPSS tools in
analysing the outcomes through implicated tests.
1. SPSS data set
In relation with the 256 sample has been collected on the various variables which have
been coded and label to have effective outcomes on the data set. By altering the number of
decimals as well as setting the appropriate measures such as Scale, Ordinal and Nominal to each
variable which have been used and considered in the data set (Okada and et.al., 2018). However,
later the file has been saved as ACTIVITY.sav which is the precise format for SPSS files.
Moreover, in relation with bringing the proper analysis over the data set which in turn have been
impacting on using the data base for the further measurement and calculations.
2. Calculated BMI
To measure the BMI of the data base which has been used by researchers. Therefore, in
relation with calculating BMI of Height and Weight of patients there have been use of formula
with the help of computing variables in transform tool (Sivam, and et.al., 2018). The formula
was implicated by selecting the variables such as Height and Weight as BMI= Weight/ Height2).
However, by this technique there have been creation of a variables label as BMI.
3. Creation of low activity
By considering the activity performed by patients per minute there have been sorting of the
efforts on the basis of more or less with 150 minutes. Thus, in accordance with creating the new
variables with the Low Activity where less than 150 minutes have been coded as 0 while more
than 150 minutes were coded as 1. Therefore, on which researcher have used Classify and
discrimination tool from analyse tool. Moreover, after such analysing the data set have been re-
saved with consisting BMI and Low-activity variables. It can be seen as listed in Appendix.
1

4. Producing a single summarized on each patient group
Descriptive Statistics
N Range Minimu
m
Maximu
m
Mean Std.
Deviation
Variance
GROUP 265 1.00 1.00 2.00 1.5019 .50094 .251
GENDER 265 1.00 1.00 2.00 1.5283 .50014 .250
AGE 265 6.00 21.00 27.00 24.2113 1.33735 1.789
HEIGHT 265 .23 1.62 1.85 1.7291 .04806 .002
WEIGHT 265 81.40 40.13 121.53 74.4038 16.29726 265.601
ACTIVITY 265 190.60 45.90 236.50 142.0596 37.20163 1383.961
BMI 265 20.53 15.29 35.82 24.6831 4.24275 18.001
LOWACTIVIT
Y 265 1 0 1 .42 .494 .244
Valid N
(listwise) 265
Interpretation: On the basis of above listed table on which there have been analysis of
various outcomes by implicating tools into action. It is the most accurate and reliable techniques
on which researcher will be benefited in analysing the mean, mode, median and standard
deviation of data base. It defines the validity of the data set on which further measurement will
be performed by the researchers.
5. Commenting on the results
As per the descriptive analysis conducted over the variables such as Group, Group A,
activity, height, weight, BMI and Low activity. On which it can be said that validity of data set
has been measured through this test. The mean value of group has been analysed as 1.5019,
gender as 1.52, Age as 24.21, height as 2, weight as 1.729, activity as 74.40 BMI as 142.05 and
Low activity as 0.451. However, in analysing outcomes on which measuring such information
will be adequate and effective to have the most reliable and valid information.
2

6. Producing a publication quality bar chart of mean activity values
3

2. Quality chart:
4

5

7. Justification of chosen Plot
In relation with analysing the mean activity with group and gender of patients on which the
graphical presentation of variables has been measured. Thus, it has brought the clear observation
through Bar chart.
Along with this, for further examination there have been use of line chart on the used data
base. It has brought the clear ascertainment of data set on which Gender and group of patients
were analysed (Rajendrakumar and et.al., 2018).
8. Testing the variables
To analyse the significance differences in the means of Activity and Group of patients this
test has been analysed such as:
Correlation:
6

This tool has been helpful in terms of analysing the relationship between the two
variables which have been proposed to tested. Thus, the range of correlation analysis is between
-1 to +1. Thus, in analysing the relationship between Groups, activity and BMI has been
analysed as:
Data as:
Group 1: Healthy volunteers
Group 2: Asthmatic patient volunteers
Correlation on the Activity and Groups of patients
Descriptive Statistics
Mean Std.
Deviation
N
GROUP 1.5019 .50094 265
ACTIVI
TY 142.0596 37.20163 265
Correlations
GROUP ACTIVI
TY
GROUP
Pearson
Correlation 1 -.219**
Sig. (2-tailed) .000
N 265 265
ACTIVI
TY
Pearson
Correlation -.219** 1
Sig. (2-tailed) .000
N 265 265
**. Correlation is significant at the 0.01 level (2-
tailed).
Interpretation: By considering the above listed table ion which it can be said that there
have been examination over the correlation among the group and activity. Thus, the mean value
of data set have represented the outcomes as 1.5 which states near to 2. Therefore, there were
7

majority of Asthmatic patient volunteers. Along with this, in analysing their relationship with
activity variable where the Pearson correlation for group is positive while for activity is negative.
Thus, it can be said that, there is negative relationship among the group of patients and activity.
Correlation on BMI and Patient groups:
Descriptive Statistics
Mean Std.
Deviation
N
GROUP 1.5019 .50094 265
BMI 24.6831 4.24275 265
Correlations
GROUP BMI
GROUP
Pearson
Correlation 1 -.176**
Sig. (2-tailed) .004
N 265 265
BMI
Pearson
Correlation -.176** 1
Sig. (2-tailed) .004
N 265 265
**. Correlation is significant at the 0.01 level (2-
tailed).
Interpretation: On the basis of above listed table on which it can be said that there has
been analysis made over the group and BMI variables. Thus, in this case, the Pearson correlation
have been analysed which have presented the outcomes as -0.176. Similarly, there has been
negative relationship among the BMI and groups of patients such as (Healthy volunteer patients
and Asthmatic volunteer patients.
9. Analysing the relationship between Low-Activity and patient groups:
To examine the relationship there have been creation of hypothesis such as:
Hypothesis:
8

Null Hypothesis: There is no mean significant relationship between Low-activity, Group
and age
Alternative Hypothesis: There is a mean significant relationship between Low-activity,
Group and age
Correlations
Descriptive Statistics
Mean Std. Deviation N
GENDER 1.5283 .50014 265
LOWACTIVITY .42 .494 265
Correlations
GENDER LOWACTIVITY
GENDER
Pearson Correlation 1 -.339**
Sig. (2-tailed) .000
N 265 265
LOWACTIVITY
Pearson Correlation -.339** 1
Sig. (2-tailed) .000
N 265 265
**. Correlation is significant at the 0.01 level (2-tailed).
Interpretation: As per considering the correlation analysis on the used variables on which
there have been use of Low-activity, Group and age. The rage of correlation is between -1 to +1.
Thus, in this case the data set is reflecting positive outcomes. Thus, in this case there is positive
relationship between Low-activity
10. Regression analysis on Activity and IBM
Hypothesis:
Null Hypothesis: There is no mean significant relationship between Activity and BMI
Alternate Hypothesis: There is a mean significant relationship between Activity and BMI
Descriptive Statistics
Mean Std.
Deviation
N
9

ACTIVIT
Y 142.0596 37.20163 265
BMI 24.6831 4.24275 265
Correlations
ACTIVIT
Y
BMI
Pearson Correlation
ACTIVIT
Y 1.000 -.545
BMI -.545 1.000
Sig. (1-tailed)
ACTIVIT
Y . .000
BMI .000 .
N
ACTIVIT
Y 265 265
BMI 265 265
Model Summary
Model R R
Square
Adjusted
R Square
Std. Error
of the
Estimate
Change Statistics
R Square
Change
F
Change
df1 df2 Sig. F
Change
1 .545a .297 .295 31.24437 .297 111.269 1 263 .000
a. Predictors: (Constant), BMI
ANOVAa
Model Sum of
Squares
df Mean Square F Sig.
1
Regression 108622.409 1 108622.409 111.269 .000b
Residual 256743.409 263 976.211
Total 365365.818 264
a. Dependent Variable: ACTIVITY
b. Predictors: (Constant), BMI
10

Coefficientsa
Model Unstandardized
Coefficients
Standardized
Coefficients
t Sig. 95.0% Confidence
Interval for B
B Std. Error Beta Lower
Bound
Upper
Bound
1
(Constant) 260.067 11.351 22.912 .000 237.718 282.417
BMI -4.781 .453 -.545 -
10.548 .000 -5.673 -3.888
a. Dependent Variable: ACTIVITY
Interpretation: In analysing the data base where the R value have been determined as
0.545 and R Square as 0.297 which is 29.7% defining relationship among the variables. Thus, the
significance value of the data set has been determined as 0.000 which is less than 0.050.
therefore, there will be acceptance to the alternative hypothesis as there is a mean significant
relationship between Activity and BMI.
11. Description on the used Statistical methods
To analyse the outcomes by using various variables on which making the adequate analysis
with the help of implicating the SPSS tool (Sivam, and et.al., 2018). There has been analysis
over variables by using descriptive statistics, regressions, T-test, creating charts and equation
which were being used to examine the outcomes.
In order to summarized the data set there have been implication of descriptive statistics for
measuring and analysing the data set. This statistical tool has been effective with reference to
have effective information regarding mean, mode, median and standard deviation of the data set.
However, in this case, there have been use of test over the variables such as Group, gender,
height, weight, activity, BMI, AGE and Low activity (Okada and et.al., 2018).
For testing the variables there have been implications and use of the t-test techniques
which will be effective and adequate in terms of reliability and validity of the data set. It defines
the significant difference between the means of two groups (Putra and et.al., 2019). To analyse
the relationship between variables such as Low activity and Group of individuals on which
ascertaining the differences in the percentage of these variables there have been use of regression
11

analysis. It will be effective techniques in terms of identifying relationship among the used
variables.
12. Presenting comments on effective findings
There have been use of various measurement techniques with the help of SPSS tool which
have brought various outcomes (IBM SPSS Statistics, 2019). Thus, majority of outcomes has
determined the acceptance to the alternative hypothesis. In this case it can be said that, the
changes incurred in the one variable would affect the other.
CONCLUSION
On the basis of above assessment on which it can eb said that use of SPSS tool had helped in
analysing the accurate outcomes. Thus, researcher have examined the variables by implicating
various measures such as descriptive statistics, regression analysing, T-test etc. which has drafted
the clear ascertainment of the data base.
12

REFERENCES
Books and Journals
Okada, T. and et.al., 2018. Science exploration and instrumentation of the OKEANOS mission to
a Jupiter Trojan asteroid using the solar power sail. Planetary and Space Science. 161.
pp.99-106.
Putra, Z. and et.al., 2019. PELATIHAN PENGOLAHAN DATA PENELITIAN DENGAN
SOFTWARE SPSS BAGI MAHASISWA LINTAS PERGURUAN TINGGI DALAM
KABUPATEN ACEH BARAT PROVINSI ACEH. Jurnal Pengabdian Kepada
Masyarakat. 3.
Rajendrakumar, S. and et.al., 2018, October. Multi-attribute decision making parametric
optimization and modelling in friction stir welding through grey relation taguchi analysis
and ANOVA: A case study. In AIP Conference Proceedings (Vol. 2034, No. 1, p.
020005). AIP Publishing.
Sivam, S. S. S. and et.al., 2018. Grey Relational Analysis and Anova to Determine the Optimum
Process Parameters for Friction Stir Welding of Ti and Mg Alloys. Periodica
Polytechnica Mechanical Engineering. 62(4). pp.277-283.
Online
IBM SPSS Statistics. 2019. [Online]. Available through :< https://www.ibm.com/account/reg/us-
en/signup?formid=urx-19774&S_PKG=-&cm_mmc=Search_Google-_-
Hybrid+Cloud_Business+Analytics-_-WW_AS-_-regression+analysis+in+spss_Exact_-
&cm_mmca1=000000OA&cm_mmca2=10001164&cm_mmca7=1007808&cm_mmca8=
kwd-
494916987253&cm_mmca9=_k_EAIaIQobChMIx83NvMC94AIVixiPCh29GQn7EAA
YASAAEgLoXPD_BwE_k_&cm_mmca10=320286219098&cm_mmca11=e&mkwid=_
k_EAIaIQobChMIx83NvMC94AIVixiPCh29GQn7EAAYASAAEgLoXPD_BwE_k_|
479|227630&cvosrc=ppc.google.regression%20analysis%20in
%20spss&cvo_campaign=000000OA&cvo_crid=320286219098&Matchtype=e&gclid=E
AIaIQobChMIx83NvMC94AIVixiPCh29GQn7EAAYASAAEgLoXPD_BwE>.
13

APPENDIX
ID
GROU
P GENDER GROUP HEIGHT WEIGHT ACTIVITY BMI LOW_ACTIVITY
1 2 1 26 1.7 74.99 134.8 25.9481 0
2 1 1 23 1.77 70.81 143.8 22.60206 0
3 2 2 23 1.77 85.09 132.8 27.16014 0
4 2 2 25 1.78 100.15 100.7 31.60901 0
5 1 2 23 1.72 76.62 138.1 25.89913 0
6 2 2 25 1.73 68.53 109.8 22.89752 0
7 2 2 27 1.68 68.1 147.7 24.1284 0
8 1 1 24 1.72 66.25 171.7 22.39386 1
9 2 1 25 1.7 57.6 181.3 19.9308 1
10 1 2 25 1.77 96.41 136.6 30.7734 0
11 2 1 24 1.73 71.31 113.6 23.82639 0
12 1 2 24 1.8 96.26 130.9 29.70988 0
13 1 1 25 1.74 76.15 186.6 25.15194 1
14 1 2 24 1.81 87.11 164.5 26.58954 1
15 1 1 24 1.74 66.66 99.2 22.01744 0
16 2 2 25 1.72 73.13 79.6 24.71944 0
17 2 1 25 1.68 56.85 136.7 20.14243 0
18 2 2 22 1.74 84.33 70.4 27.85375 0
19 2 1 25 1.7 60.07 158.3 20.78547 1
20 2 2 23 1.78 88.87 149.2 28.04886 0
21 1 1 27 1.69 65.42 126.6 22.90536 0
22 2 1 22 1.7 53.07 157.3 18.36332 1
23 1 1 23 1.75 74.35 190.9 24.27755 1
24 2 1 26 1.73 76.98 93 25.72087 0
25 2 1 23 1.78 87 145.3 27.45865 0
26 1 2 23 1.77 84.62 138.1 27.01012 0
27 2 1 26 1.66 54.74 130 19.865 0
28 2 2 26 1.8 80.86 138.1 24.95679 0
29 2 2 24 1.69 66.37 158.3 23.23798 1
30 2 2 27 1.82 85.57 147.2 25.83323 0
31 2 2 25 1.75 74.46 145.3 24.31347 0
32 1 1 26 1.64 45.11 200 16.77201 1
33 2 1 23 1.69 59.76 177 20.92364 1
34 2 2 25 1.74 87.24 121.8 28.8149 0
35 2 2 24 1.69 77.73 142.9 27.21543 0
36 2 2 25 1.7 65.99 76.7 22.83391 0
37 1 1 25 1.74 88.58 129.4 29.2575 0
38 1 1 26 1.67 55.3 165.9 19.82861 1
39 1 2 23 1.74 88.41 117.9 29.20135 0
14

40 2 2 24 1.77 77.4 132.8 24.70554 0
41 1 2 24 1.77 84.44 173.6 26.95266 1
42 1 2 23 1.7 71.36 129.4 24.69204 0
43 1 1 23 1.69 72.52 121.3 25.39127 0
44 1 1 23 1.73 73.2 143.8 24.45788 0
45 2 1 25 1.73 69.94 91.1 23.36864 0
46 1 1 24 1.76 84.62 164 27.31792 1
47 1 2 26 1.76 92.65 159.2 29.91025 1
48 1 2 26 1.71 76.4 93.9 26.1277 0
49 2 1 24 1.72 55.04 184.7 18.60465 1
50 1 2 24 1.82 99.83 132.3 30.13827 0
51 2 2 26 1.8 99.02 94 30.56173 0
52 2 1 24 1.72 64.93 172.2 21.94767 1
53 1 2 25 1.79 94.02 200.5 29.34365 1
54 2 1 25 1.71 63.51 164.5 21.7195 1
55 2 1 23 1.73 81.85 149.6 27.34806 0
56 1 2 26 1.74 67.95 173.6 22.44352 1
57 2 2 25 1.8 101.93 74.3 31.45988 0
58 2 2 24 1.72 73.06 115.1 24.69578 0
59 2 2 23 1.79 89.48 117 27.92672 0
60 2 1 25 1.68 51.51 142.9 18.25043 0
61 1 1 25 1.62 54.92 138.1 20.92669 0
62 1 2 24 1.75 84.91 147.2 27.72571 0
63 2 2 24 1.73 83.02 150.6 27.73898 1
64 1 2 23 1.76 85.85 148.2 27.71501 0
65 1 1 27 1.71 61.04 189 20.8748 1
66 1 1 24 1.7 70.81 201 24.50173 1
67 1 1 22 1.74 65.07 167.8 21.49227 1
68 2 2 26 1.73 69.14 118 23.10134 0
69 1 2 24 1.82 100.56 159.2 30.35865 1
70 1 1 25 1.69 58.85 180.8 20.60502 1
71 2 1 25 1.62 40.13 211.6 15.29111 1
72 2 1 26 1.71 66.83 154.9 22.8549 1
73 2 1 25 1.76 87.23 123.7 28.16051 0
74 1 1 25 1.69 54.77 181.3 19.1765 1
75 1 2 25 1.72 71.09 159.7 24.02988 1
76 1 1 27 1.67 64.32 158.7 23.06286 1
77 1 1 25 1.66 55.47 206.7 20.12992 1
78 2 2 26 1.79 99.65 80 31.10078 0
79 1 2 23 1.72 80.05 109.3 27.05855 0
80 2 2 23 1.78 91.4 133.3 28.84737 0
81 1 1 26 1.72 62.68 121.8 21.18713 0
82 2 1 24 1.71 72.25 137.6 24.70846 0
15

83 1 1 26 1.73 64.02 148.2 21.39062 0
84 2 1 26 1.83 103.22 105.5 30.82206 0
85 1 2 25 1.75 77.87 167.8 25.42694 1
86 2 2 24 1.78 95.68 103.6 30.19821 0
87 2 1 25 1.66 49.72 141 18.04326 0
88 2 1 25 1.69 64.94 94.4 22.7373 0
89 1 1 22 1.66 54.24 203.4 19.68355 1
90 1 1 24 1.73 67.04 147.2 22.39968 0
91 2 1 24 1.68 54.2 213 19.20351 1
92 1 2 25 1.79 108.3 102.6 33.80044 0
93 2 1 22 1.69 72.48 129 25.37726 0
94 2 2 26 1.79 98.65 118.9 30.78868 0
95 1 2 24 1.75 86.4 117.9 28.21224 0
96 2 1 24 1.65 43.97 182.8 16.1506 1
97 1 1 25 1.66 58.36 193.3 21.17869 1
98 2 2 22 1.7 66.38 90.6 22.96886 0
99 1 1 24 1.71 75.43 170.7 25.79597 1
100 1 2 25 1.8 103.62 121.8 31.98148 0
101 2 2 26 1.79 88.23 151.6 27.53659 1
102 1 2 23 1.75 81.35 157.3 26.56327 1
103 1 1 25 1.74 75.98 188.5 25.09579 1
104 2 2 22 1.72 63.27 148.2 21.38656 0
105 2 1 25 1.76 68.97 126.6 22.26563 0
106 1 2 23 1.77 97.04 153 30.9745 1
107 2 1 25 1.77 75.52 128 24.10546 0
108 2 1 23 1.72 74.13 160.2 25.05746 1
109 2 1 26 1.78 76.31 107.9 24.08471 0
110 2 1 26 1.67 54.39 151.6 19.50231 1
111 1 1 22 1.65 57.77 163 21.21947 1
112 1 1 24 1.75 89.26 144.3 29.14612 0
113 1 2 25 1.76 85.53 135.2 27.6117 0
114 2 1 24 1.71 59.04 158.8 20.19083 1
115 2 2 23 1.74 76.18 91.6 25.16184 0
116 2 1 23 1.71 63.18 133.8 21.60665 0
117 2 2 26 1.7 74.36 63.7 25.7301 0
118 2 2 22 1.74 83.95 145.3 27.72823 0
119 2 2 24 1.74 78.59 138.1 25.95785 0
120 2 1 22 1.74 57.84 178 19.10424 1
121 1 1 24 1.69 52.22 137.6 18.28367 0
122 1 1 23 1.65 65.94 180.8 24.22039 1
123 1 1 24 1.76 73.96 151.5 23.87655 1
124 2 2 23 1.75 87.41 68.5 28.54204 0
125 1 2 21 1.73 72.97 131.4 24.38104 0
16

126 1 1 23 1.65 44.73 223 16.42975 1
127 2 2 23 1.69 61.16 176 21.41382 1
128 1 2 25 1.69 61.04 156.3 21.3718 1
129 1 2 27 1.72 88.73 154.9 29.99256 1
130 1 2 24 1.77 84.83 158.2 27.07715 1
131 2 1 27 1.71 64.41 119.4 22.02729 0
132 1 2 25 1.78 79.03 116 24.94319 0
133 1 1 24 1.71 69.2 142.4 23.6654 0
134 1 2 24 1.7 70.45 127 24.37716 0
135 1 1 23 1.7 66.47 158.7 23 1
136 2 2 23 1.77 82.54 154 26.3462 1
137 1 2 24 1.79 97.68 136.6 30.48594 0
138 2 2 23 1.75 81.82 82.9 26.71673 0
139 1 1 23 1.73 67.06 177 22.40636 1
140 1 1 23 1.7 65.09 163.5 22.52249 1
141 2 1 25 1.62 50.8 181.3 19.35681 1
142 2 2 22 1.72 67.16 195.7 22.70146 1
143 2 1 23 1.71 65.99 142 22.56763 0
144 1 2 23 1.77 71.46 171.2 22.80954 1
145 1 1 22 1.74 64.35 144.8 21.25446 0
146 1 1 22 1.68 63.26 172.2 22.41355 1
147 1 2 24 1.78 94.27 114.6 29.75319 0
148 1 2 23 1.79 89.48 164 27.92672 1
149 2 1 25 1.7 54.44 214.9 18.83737 1
150 1 1 22 1.74 78.04 101.1 25.77619 0
151 1 1 23 1.73 69.42 141.4 23.19489 0
152 2 2 23 1.7 69.91 63.7 24.19031 0
153 1 1 26 1.76 66.4 156.3 21.43595 1
154 1 2 26 1.72 80.71 156.3 27.28164 1
155 1 1 21 1.7 68.8 196.2 23.80623 1
156 1 2 25 1.85 116 45.9 33.89335 0
157 2 1 23 1.66 44.95 175.1 16.31224 1
158 1 1 23 1.75 71.1 181.3 23.21633 1
159 2 2 25 1.73 80.69 145.8 26.96047 0
160 2 2 23 1.74 87.32 82.9 28.84133 0
161 1 2 24 1.78 93.7 145.3 29.57329 0
162 2 2 24 1.69 72.78 196.2 25.4823 1
163 1 2 23 1.72 65.9 186.1 22.27555 1
164 2 1 23 1.74 61.24 207.2 20.22724 1
165 1 1 23 1.68 68.05 104 24.11069 0
166 1 1 25 1.69 56.42 205.8 19.75421 1
167 2 1 24 1.68 58.1 113.6 20.58532 0
168 2 2 24 1.76 92.71 83.9 29.92962 0
17

169 1 2 25 1.72 82.39 83.8 27.84951 0
170 1 2 25 1.85 121.53 93.4 35.50913 0
171 2 2 24 1.74 73.05 102.1 24.12802 0
172 2 2 26 1.74 71.71 174.1 23.68543 1
173 1 2 27 1.84 100.13 116 29.57526 0
174 1 1 23 1.67 61.31 156.3 21.98358 1
175 1 2 22 1.73 83.58 132.8 27.92609 0
176 2 1 27 1.64 58.31 131.9 21.6798 0
177 2 1 23 1.68 54.19 154.4 19.19997 1
178 2 1 26 1.7 68.13 128 23.57439 0
179 2 1 23 1.69 61.53 139.1 21.54336 0
180 1 2 26 1.82 112.72 131.4 34.02971 0
181 2 2 23 1.74 79.01 104 26.09658 0
182 2 2 23 1.82 118.65 180.3 35.81995 1
183 1 2 24 1.64 44 199 16.35931 1
184 2 1 24 1.66 49.6 182.3 17.99971 1
185 2 2 24 1.78 87.21 121.3 27.52493 0
186 2 1 22 1.67 42.81 201 15.35014 1
187 1 1 24 1.69 61.73 155.8 21.61339 1
188 1 2 24 1.75 80.36 111.7 26.24 0
189 1 1 23 1.75 75.1 175.5 24.52245 1
190 2 2 23 1.75 80.33 150.6 26.2302 1
191 2 1 24 1.63 46.93 134.3 17.66344 0
192 1 2 25 1.74 82.97 76.6 27.40454 0
193 1 2 26 1.71 82.35 128 28.16251 0
194 1 2 24 1.75 74.4 204.3 24.29388 1
195 2 2 21 1.76 70.57 107.4 22.78215 0
196 1 1 25 1.72 60.37 169.8 20.4063 1
197 1 2 24 1.65 55.76 157.3 20.48118 1
198 2 2 23 1.63 58.23 113.6 21.91652 0
199 1 2 27 1.81 114.86 97.8 35.05998 0
200 2 1 22 1.7 69.62 112.7 24.08997 0
201 1 1 23 1.67 50.7 206.2 18.17921 1
202 2 2 24 1.71 77.93 110.8 26.65094 0
203 2 2 25 1.73 61.96 146.3 20.70233 0
204 2 1 25 1.64 51.62 153.5 19.19244 1
205 2 2 25 1.68 68.21 110.8 24.16738 0
206 1 2 23 1.8 94.9 186.1 29.29012 1
207 2 2 24 1.78 82.43 83.4 26.01629 0
208 2 2 24 1.74 66.37 107.9 21.92165 0
209 1 2 27 1.68 76.47 112.6 27.09396 0
210 1 2 26 1.72 88.98 96.3 30.07707 0
211 1 2 24 1.75 88.22 155.8 28.80653 1
18

212 2 2 24 1.78 83.2 88.7 26.25931 0
213 1 1 26 1.75 81.24 114.1 26.52735 0
214 1 2 25 1.77 90.81 136.6 28.98592 0
215 1 2 24 1.84 120.86 97.3 35.69825 0
216 2 2 26 1.71 79.08 176 27.04422 1
217 2 2 25 1.8 96.76 121.3 29.8642 0
218 2 2 25 1.78 86.84 81 27.40816 0
219 2 2 24 1.74 69.42 126.6 22.92905 0
220 2 1 25 1.71 62.86 175.6 21.49721 1
221 1 2 23 1.74 84.25 190.4 27.82732 1
222 2 1 26 1.72 71.56 101.6 24.18875 0
223 1 2 23 1.73 94.45 110.2 31.55802 0
224 2 2 23 1.74 80.63 83.9 26.63166 0
225 2 2 23 1.83 106.39 69.5 31.76864 0
226 1 2 25 1.74 79.47 150.6 26.24851 1
227 2 1 27 1.7 56.35 168.4 19.49827 1
228 1 2 24 1.7 76.18 125.6 26.35986 0
229 2 2 25 1.72 74.8 147.7 25.28394 0
230 1 1 22 1.69 65.19 195.7 22.82483 1
231 1 1 26 1.66 55.2 193.3 20.03193 1
232 1 2 26 1.84 120.04 133.8 35.45605 0
233 2 2 25 1.75 80.76 111.7 26.37061 0
234 2 2 24 1.81 101.72 58.9 31.04911 0
235 2 2 24 1.75 71.26 131.4 23.26857 0
236 2 1 22 1.71 70.72 133.8 24.18522 0
237 2 2 25 1.69 65.44 113.6 22.91236 0
238 1 2 24 1.8 99.73 105.9 30.78086 0
239 1 1 23 1.67 55.38 198.1 19.85729 1
240 1 1 23 1.72 55.1 210.1 18.62493 1
241 1 1 23 1.72 67.05 183.2 22.66428 1
242 2 2 26 1.77 85.22 94.9 27.20163 0
243 2 2 25 1.69 82.08 79.6 28.73849 0
244 2 1 25 1.62 42.26 214.9 16.10273 1
245 1 2 25 1.79 97.15 104.5 30.32053 0
246 2 1 24 1.64 45.39 224.5 16.87612 1
247 1 2 25 1.77 75.87 167.8 24.21718 1
248 1 1 24 1.7 73.5 157.3 25.43253 1
249 2 2 23 1.74 76.57 106.4 25.29066 0
250 1 1 23 1.71 59.37 181.8 20.30368 1
251 1 2 25 1.79 91.06 134.7 28.41984 0
252 2 1 25 1.7 52.86 188.5 18.29066 1
253 2 1 22 1.71 58.63 166.4 20.05061 1
254 1 2 24 1.83 110.06 117.4 32.86452 0
19

255 2 2 25 1.7 64.65 123.2 22.37024 0
256 2 1 24 1.63 42.21 236.5 15.88694 1
257 2 2 24 1.74 79.79 99.7 26.35421 0
258 1 1 24 1.7 80.19 67.5 27.7474 0
259 2 1 25 1.71 64.18 161.6 21.94863 1
260 2 1 23 1.72 62.95 118.4 21.27839 0
261 1 1 25 1.73 74.27 123.7 24.8154 0
262 1 1 22 1.7 64.48 189.4 22.31142 1
263 1 1 25 1.73 58.15 209.6 19.42932 1
264 1 1 24 1.71 68.09 137.6 23.2858 0
265 1 2 23 1.79 106.91 131.8 33.36662 0
20