SPSS Data Analysis and Correlation

The assignment provided discusses the use of SPSS for analyzing sports data, including calculating correlations to determine relationships between variables. The data reveals that male respondents who played sports in the last four weeks were 1683, while female respondents were 2524. The correlation between male sex and number of respondents who played in the last four weeks was also calculated. A mode value of age of respondents is 64, indicating that people of this age group play sports frequently.

INTRODUCTION TO RESEARCH:
STATISTICS ASSIGNMENT

Table of Contents
INTRODUCTION...........................................................................................................................3
SECTION B.....................................................................................................................................3
1. Strength and Weakness of fact that is used to select people included in dataset....................3
2. Calculation of mean, median and mode..................................................................................4
3. Calculation of cross tabulation, correlation..........................................................................28
CONCLUSION..............................................................................................................................29
REFERENCES..............................................................................................................................30

INTRODUCTION
SPSS statistics is the software which assist in handling large set of statistical data. Present
study will discuss strengths and weaknesses of facts that are used for selecting people that are
included in dataset. Calculation of mean, mode, median in respect to various variables will be
done in this assignment. Correlation, cross tabulation will be calculated in this report.
SECTION B
1. Strength and Weakness of fact that is used to select people included in dataset
Probability sampling is considered as one of the most effective way of selecting samples
for particular study (Brar, Malik and Kaur, 2017). In this technique, each item has equal chance
of getting selected. It is the tool which is used in both qualitative and quantitative type of
investigations. This process is free from biasness thus, scholar can gather relevant and reliable
information by using probability sampling technique. In the Sports Data, scholar has used
probability sampling tool for this project(Fox, Levin and Forde, 2013). Strengths of this method
are as following: Cost effective: Probability sampling such as random sampling is the method in which
scholar can select participants on random basis from mass population. This saves time
and cost in choosing people randomly. Researcher can take any number of samples with
the help of probability sampling tool (Coumans and et.al, 2014). Involves lesser degree of judgement: In this process scholar assign task on random basis
thus, individual can get accurate data which is far from biasness.
 Easy way of sampling: It is quite simple and short process as compare to non-probability
sampling technique. For example, if person wants to collect information about number of
male persons those who have played any sport during last four weeks (Davis, 2015), then
one can easily gather information by using probability sampling technique. Because when
respondents are selected on random basis so there will be no confusion and individual can
get data easily.
Weaknesses:
Shortcomings of probability sampling are discussed as below: Chances of selecting samples which are from specific class: In probability sampling
researcher has to choose samples randomly thus individual can select specific class
3

frequently which also increases chances of biasness. Hence the result may not be
accurate. Monotonous and redundant work: In this method, there are high chances of repetition of
same units. Also this method Is a bit monotonous which can reduce effectiveness of the
system (Coumans and et.al, 2014).
 Time consuming: When researcher has to create large sample then this method takes too
much time. As sports data set is too lengthy thus probability sampling can be time
consuming tool for the present study.
2. Calculation of mean, median and mode
Mean: It can be defined as arithmetic average of all numbers. It is the tool which is generally
used to measure central tendency in available data set. Calculation of mean is good for the
present statistical data because by this way individual can analyse the data effectively. Mean is
the value which can be rigidly defined and it is simple for the researcher to calculate it and to get
correct results (Davis, 2015). Mean is the value which is based on the observations. Mean is the
value in which all data is used by the researcher in order to find answers. But when there is large
sample size then mean might distort the results. Median is the value which does not get changed
whether data set is lengthy or short. But it takes too much time to calculate the median value.
Mode is the third method of central tendency which defines the value which is repeated in the
data set frequently (Brar, Malik and Kaur, 2017). The advantage of calculating mode in the
statics is that when data is not numerical then also researcher can calculate the facts. But if there
are possibilities of presence of more than one mode then it may create confusion in the results.
Statistics
Sex of
respondent
Age of
respondent
Number of
sports
respondent has
played (in last 4
weeks)
N
u
m
b
e
r
o
f
d
a
y
4

s
i
n
l
a
s
t
4
w
e
e
k
s
r
e
s
p
o
n
d
e
n
t
h
a
s
d
o
n
e
a
t
l
e
a
s
t
3
0
m
5

i
n
u
t
e
s
o
f
s
p
o
rt
N Valid 7345 7345 7345 7345
Missing 0 0 0 0
Mean 1.5556 50.3179 1.0436
5
.
1
3
1
0
Median 2.0000 49.0000 1.0000
.
0
0
0
0
Mode 2.00 64.00 .00
.
0
0
Sex of
respondent
Frequency Percent Valid Percent Cu
mu
lati
ve
Pe
rce
nt
6

Valid
Male 3264 44.4 44.4 44.4
Female 4081 55.6 55.6 100.0
Total 7345 100.0 100.0
Age of
responden
t
Frequency Percent Valid Percent Cu
mul
ativ
e
Per
cen
t
Valid 16.00 68 .9 .9 .9
17.00 75 1.0 1.0 1.9
18.00 72 1.0 1.0 2.9
19.00 75 1.0 1.0 3.9
20.00 70 1.0 1.0 4.9
21.00 85 1.2 1.2 6.1
22.00 73 1.0 1.0 7.1
23.00 93 1.3 1.3 8.3
24.00 77 1.0 1.0 9.4
25.00 87 1.2 1.2 10.6
26.00 106 1.4 1.4 12.0
27.00 96 1.3 1.3 13.3
28.00 108 1.5 1.5 14.8
29.00 133 1.8 1.8 16.6
30.00 116 1.6 1.6 18.2
31.00 116 1.6 1.6 19.7
32.00 131 1.8 1.8 21.5
33.00 110 1.5 1.5 23.0
34.00 117 1.6 1.6 24.6
35.00 127 1.7 1.7 26.3
36.00 114 1.6 1.6 27.9
37.00 105 1.4 1.4 29.3
38.00 107 1.5 1.5 30.8
7

39.00 116 1.6 1.6 32.4
40.00 154 2.1 2.1 34.5
41.00 117 1.6 1.6 36.1
42.00 141 1.9 1.9 38.0
43.00 119 1.6 1.6 39.6
44.00 125 1.7 1.7 41.3
45.00 122 1.7 1.7 43.0
46.00 124 1.7 1.7 44.6
47.00 152 2.1 2.1 46.7
48.00 118 1.6 1.6 48.3
49.00 124 1.7 1.7 50.0
50.00 129 1.8 1.8 51.8
51.00 98 1.3 1.3 53.1
52.00 118 1.6 1.6 54.7
53.00 117 1.6 1.6 56.3
54.00 105 1.4 1.4 57.7
55.00 99 1.3 1.3 59.1
56.00 107 1.5 1.5 60.5
57.00 109 1.5 1.5 62.0
58.00 104 1.4 1.4 63.4
59.00 98 1.3 1.3 64.8
60.00 134 1.8 1.8 66.6
61.00 120 1.6 1.6 68.2
62.00 120 1.6 1.6 69.9
63.00 142 1.9 1.9 71.8
64.00 166 2.3 2.3 74.1
65.00 118 1.6 1.6 75.7
66.00 111 1.5 1.5 77.2
67.00 122 1.7 1.7 78.8
68.00 103 1.4 1.4 80.2
69.00 113 1.5 1.5 81.8
70.00 88 1.2 1.2 83.0
71.00 98 1.3 1.3 84.3
72.00 96 1.3 1.3 85.6
73.00 96 1.3 1.3 86.9
74.00 75 1.0 1.0 87.9
75.00 86 1.2 1.2 89.1
76.00 76 1.0 1.0 90.1
8

77.00 73 1.0 1.0 91.1
78.00 83 1.1 1.1 92.3
79.00 57 .8 .8 93.0
80.00 68 .9 .9 94.0
81.00 65 .9 .9 94.9
82.00 58 .8 .8 95.6
83.00 60 .8 .8 96.5
84.00 49 .7 .7 97.1
85.00 46 .6 .6 97.8
86.00 28 .4 .4 98.1
87.00 36 .5 .5 98.6
88.00 22 .3 .3 98.9
89.00 14 .2 .2 99.1
90.00 21 .3 .3 99.4
91.00 15 .2 .2 99.6
92.00 10 .1 .1 99.7
93.00 2 .0 .0 99.8
94.00 8 .1 .1 99.9
95.00 2 .0 .0 99.9
96.00 2 .0 .0 99.9
97.00 2 .0 .0 100.0
98.00 2 .0 .0 100.0
99.00 1 .0 .0 100.0
Total 7345 100.0 100.0
Number of
sports
respondent
has played
(in last 4
weeks)
9

Frequency Percent Valid Percent C
u
m
ul
ati
ve
P
er
ce
nt
Valid
None 3534 48.1 48.1 48.1
One 1709 23.3 23.3 71.4
Two 971 13.2 13.2 84.6
Three 510 6.9 6.9 91.5
Four or more 621 8.5 8.5 100.0
Total 7345 100.0 100.0
Number of
days in
last 4
weeks
responden
t has done
at least 30
minutes of
sport
Frequency Percent Valid Percent Cu
mul
ativ
e
Per
cen
t
Valid .00 4207 57.3 57.3 57.3
1.00 208 2.8 2.8 60.1
2.00 199 2.7 2.7 62.8
3.00 107 1.5 1.5 64.3
4.00 371 5.1 5.1 69.3
10

5.00 95 1.3 1.3 70.6
6.00 133 1.8 1.8 72.4
7.00 71 1.0 1.0 73.4
8.00 311 4.2 4.2 77.6
9.00 67 .9 .9 78.5
10.00 112 1.5 1.5 80.1
11.00 46 .6 .6 80.7
12.00 209 2.8 2.8 83.5
13.00 50 .7 .7 84.2
14.00 120 1.6 1.6 85.9
15.00 43 .6 .6 86.4
16.00 150 2.0 2.0 88.5
17.00 26 .4 .4 88.8
18.00 50 .7 .7 89.5
19.00 18 .2 .2 89.8
20.00 124 1.7 1.7 91.4
21.00 27 .4 .4 91.8
22.00 33 .4 .4 92.3
23.00 19 .3 .3 92.5
24.00 60 .8 .8 93.3
25.00 19 .3 .3 93.6
26.00 26 .4 .4 94.0
27.00 11 .1 .1 94.1
28.00 433 5.9 5.9 100.0
Total 7345 100.0 100.0
CROSSTABS
/TABLES=age BY numsports4wks
/FORMAT=AVALUE TABLES
/STATISTICS=CORR
/CELLS=COUNT
/COUNT ROUND CELL.
Case
Processing
Summary
11

C
a
s
e
s
Valid Missing T
o
t
a
l
N Percent N Percent N Percent
Age of respondent * Number
of sports respondent has
played (in last 4 weeks)
7345 100.0% 0 0.0% 7345 100.0%
Age of
respondent
* Number
of sports
respondent
has played
(in last 4
weeks)
Crosstabul
ation
Count
Number of sports respondent has played (in last 4 weeks) T
o
t
a
l
None One Two Three Four or more
Age of respondent 16.00 15 11 12 7 23 68
17.00 14 16 18 9 18 75
18.00 19 16 10 9 18 72
19.00 21 18 14 7 15 75
20.00 22 14 11 10 13 70
21.00 25 18 12 12 18 85
22.00 24 19 8 7 15 73
12

23.00 28 29 14 6 16 93
24.00 27 16 14 10 10 77
25.00 18 23 13 13 20 87
26.00 37 21 22 10 16 106
27.00 37 18 15 12 14 96
28.00 31 32 18 10 17 108
29.00 46 27 23 18 19 133
30.00 35 30 25 9 17 116
31.00 35 33 19 13 16 116
32.00 47 32 22 11 19 131
33.00 39 34 23 7 7 110
34.00 38 30 18 12 19 117
35.00 37 38 26 5 21 127
36.00 36 32 21 9 16 114
37.00 36 28 14 16 11 105
38.00 35 26 24 8 14 107
39.00 38 29 15 17 17 116
40.00 49 44 25 20 16 154
41.00 51 24 22 12 8 117
42.00 53 39 24 10 15 141
43.00 43 27 23 14 12 119
44.00 45 26 30 7 17 125
45.00 53 32 21 5 11 122
46.00 59 28 18 7 12 124
47.00 57 43 21 14 17 152
48.00 40 35 22 8 13 118
49.00 48 34 20 12 10 124
50.00 50 39 21 10 9 129
51.00 47 18 16 12 5 98
52.00 64 26 18 6 4 118
53.00 54 26 21 7 9 117
54.00 57 22 15 7 4 105
55.00 55 32 7 2 3 99
56.00 54 23 14 8 8 107
57.00 67 25 10 5 2 109
58.00 58 25 8 10 3 104
59.00 57 19 12 6 4 98
60.00 68 37 18 5 6 134
13

61.00 69 34 9 3 5 120
62.00 74 19 15 8 4 120
63.00 77 32 23 6 4 142
64.00 104 37 14 6 5 166
65.00 65 30 14 6 3 118
66.00 70 28 6 5 2 111
67.00 73 26 13 6 4 122
68.00 51 32 11 8 1 103
69.00 81 21 7 2 2 113
70.00 56 18 6 3 5 88
71.00 74 8 10 3 3 98
72.00 67 20 6 2 1 96
73.00 56 31 7 2 0 96
74.00 53 15 3 3 1 75
75.00 65 16 2 1 2 86
76.00 45 23 6 2 0 76
77.00 49 21 2 1 0 73
78.00 65 15 3 0 0 83
79.00 42 12 3 0 0 57
80.00 59 5 2 2 0 68
81.00 53 7 3 1 1 65
82.00 51 7 0 0 0 58
83.00 44 10 3 2 1 60
84.00 37 8 2 2 0 49
85.00 39 7 0 0 0 46
86.00 22 4 0 2 0 28
87.00 31 4 1 0 0 36
88.00 21 1 0 0 0 22
89.00 13 1 0 0 0 14
90.00 20 1 0 0 0 21
91.00 15 0 0 0 0 15
92.00 8 2 0 0 0 10
93.00 2 0 0 0 0 2
94.00 6 0 2 0 0 8
95.00 1 0 1 0 0 2
96.00 2 0 0 0 0 2
97.00 2 0 0 0 0 2
98.00 2 0 0 0 0 2
14

99.00 1 0 0 0 0 1
Total 3534 1709 971 510 621
7
3
4
5
Symmetric
Measures
Value Asymp. Std.
Error
Approx. Tb A
p
p
r
o
x
.
S
i
g
.
Interval by Interval Pearson's R -.359 .010 -32.933 .000c
Ordinal by Ordinal Spearman Correlation -.361 .010 -33.217 .000c
N of Valid Cases 7345
a. Not assuming
the null
hypothesis.
b. Using the
asymptotic
standard error
assuming the
null hypothesis.
c. Based on
normal
approximation.
15

Case
Processing
Summary
C
a
s
e
s
Valid Missing T
o
t
a
l
N Percent N Percent N Percent
Sex of respondent * Number
of sports respondent has
played (in last 4 weeks)
7345 100.0% 0 0.0% 7345 100.0%
Sex of
respondent
* Number of
sports
respondent
has played
(in last 4
weeks)
Crosstabul
ation
Count
Number of sports respondent has played (in last 4 weeks) T
o
t
a
l
None One Two Three Four or more
Sex of respondent Male 1345 771 464 271 413 3264
Female 2189 938 507 239 208 4081
16

Total 3534 1709 971 510 621
7
3
4
5
Symmetric
Measures
Value Asymp. Std.
Errora
Approx. Tb A
p
p
r
o
x
.
S
i
g
.
Interval by Interval Pearson's R -.162 .011 -14.035 .000c
Ordinal by Ordinal Spearman Correlation -.151 .012 -13.063 .000c
N of Valid Cases 7345
a. Not assuming
the null
hypothesis.
b. Using the
asymptotic
standard error
assuming the
null hypothesis.
c. Based on
normal
approximation.
CROSSTABS
/TABLES=age BY numdays4wks
/FORMAT=AVALUE TABLES
/STATISTICS=CORR
/CELLS=COUNT
17

/COUNT ROUND CELL.
Case
Processing
Summary
C
a
s
e
s
Valid Missing T
o
t
a
l
N Percent N Percent N Percent
Age of respondent * Number
of days in last 4 weeks
respondent has done at least
30 minutes of sport
7345 100.0% 0 0.0% 7345 100.0%
Age of
responde
nt *
Number
of days in
last 4
weeks
responde
nt has
done at
least 30
minutes
of sport
Crosstab
ulation
Count
18

Number of days in last
4 weeks respondent
has done at least 30
minutes of sport
Total
.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00
Age of respondent 1
6
.
0
0
17 2 0 6 4 2 1 0
1
7
.
0
0
22 2 5 2 3 4 2 0
1
8
.
0
0
22 7 4 5 3 2 2 0
1
9
.
0
0
30 5 3 1 5 0 1 0
2
0
.
0
0
28 3 2 0 4 2 3 1
2
1
.
0
0
36 3 4 1 3 3 3 1
19

2
2
.
0
0
32 2 4 2 3 3 0 1
2
3
.
0
0
34 7 2 4 4 3 2 3
2
4
.
0
0
35 3 4 1 4 0 0 1
2
5
.
0
0
28 5 3 1 10 1 2 2
2
6
.
0
0
48 3 3 2 5 2 0 0
2
7
.
0
0
46 1 3 1 3 2 3 3
2
8
.
0
0
39 3 5 3 10 3 4 4
2
9
.
0
0
60 4 4 0 5 2 3 0
20

3
0
.
0
0
45 5 2 4 5 4 3 1
3
1
.
0
0
52 5 3 1 8 4 3 0
3
2
.
0
0
57 5 6 4 5 3 3 2
3
3
.
0
0
50 6 2 1 8 2 1 2
3
4
.
0
0
50 6 2 4 8 2 4 2
3
5
.
0
0
47 6 6 2 9 5 1 0
3
6
.
0
0
45 5 5 3 7 1 1 1
3
7
.
0
0
47 4 4 2 11 2 1 1
21

3
8
.
0
0
44 3 3 2 10 4 3 1
3
9
.
0
0
47 4 2 5 8 1 5 3
4
0
.
0
0
63 10 4 3 8 0 4 2
4
1
.
0
0
60 5 5 0 8 1 4 1
4
2
.
0
0
67 5 6 2 9 4 2 1
4
3
.
0
0
58 2 3 1 4 0 6 0
4
4
.
0
0
56 3 6 3 7 4 6 1
4
5
.
0
0
69 8 4 0 10 0 3 1
22

4
6
.
0
0
68 3 2 2 3 3 1 3
4
7
.
0
0
69 4 9 3 9 2 2 4
4
8
.
0
0
53 4 2 0 9 0 4 4
4
9
.
0
0
60 4 4 1 5 1 5 0
5
0
.
0
0
73 1 6 2 3 1 4 2
5
1
.
0
0
56 1 4 2 5 0 2 0
5
2
.
0
0
72 3 6 0 8 0 1 1
5
3
.
0
0
64 4 3 2 6 0 2 0
23

5
4
.
0
0
66 4 2 1 5 3 3 0
5
5
.
0
0
65 4 3 1 6 1 2 2
5
6
.
0
0
64 3 4 1 4 1 1 2
5
7
.
0
0
77 1 2 3 5 0 0 1
5
8
.
0
0
66 2 4 0 6 1 2 1
5
9
.
0
0
64 4 1 0 5 1 1 3
6
0
.
0
0
84 2 1 2 6 0 0 2
6
1
.
0
0
81 2 1 3 2 1 4 1
24

6
2
.
0
0
79 3 2 0 3 2 4 1
6
3
.
0
0
96 1 3 2 7 3 4 0
6
4
.
0
0
120 1 4 1 7 1 1 0
6
5
.
0
0
80 2 2 2 6 1 0 0
6
6
.
0
0
76 1 1 4 5 1 1 2
6
7
.
0
0
82 2 4 1 2 3 0 0
6
8
.
0
0
59 5 3 0 8 1 3 1
6
9
.
0
0
90 0 4 1 8 1 0 0
25

7
0
.
0
0
64 1 0 1 8 0 0 1
7
1
.
0
0
79 1 1 0 3 0 3 0
7
2
.
0
0
77 1 0 0 3 0 0 0
7
3
.
0
0
70 1 3 1 3 1 2 1
7
4
.
0
0
60 0 0 0 6 0 1 2
7
5
.
0
0
70 1 1 2 2 0 1 0
7
6
.
0
0
54 4 3 1 4 0 1 0
7
7
.
0
0
55 0 1 0 1 0 0 0
26

7
8
.
0
0
71 1 0 2 4 0 0 0
7
9
.
0
0
45 0 0 0 4 0 2 1
8
0
.
0
0
63 0 0 0 1 0 0 0
8
1
.
0
0
57 1 0 0 3 0 0 0
8
2
.
0
0
54 0 1 0 0 0 0 0
8
3
.
0
0
51 1 2 0 2 0 0 1
8
4
.
0
0
43 1 0 0 1 0 0 0
8
5
.
0
0
42 0 1 0 1 0 0 0
27

8
6
.
0
0
24 1 0 0 0 0 0 0
8
7
.
0
0
34 1 0 0 0 0 0 0
8
8
.
0
0
22 0 0 0 0 0 0 0
8
9
.
0
0
13 0 0 0 0 0 0 0
9
0
.
0
0
20 0 0 0 0 0 0 0
9
1
.
0
0
15 0 0 0 0 0 0 0
9
2
.
0
0
10 0 0 0 0 0 0 0
9
3
.
0
0
2 0 0 0 0 0 0 0
28

9
4
.
0
0
6 0 0 0 0 0 0 0
9
5
.
0
0
1 0 0 0 1 0 0 0
9
6
.
0
0
2 0 0 0 0 0 0 0
9
7
.
0
0
2 0 0 0 0 0 0 0
9
8
.
0
0
2 0 0 0 0 0 0 0
9
9
.
0
0
1 0 0 0 0 0 0 0
Total
4
2
0
7
2
0
8
199 107 371 95 133 71 311
Symmetric
Measures
29

Value Asymp. Std.
Errora
Approx. Tb A
p
p
r
o
x
.
S
i
g
.
Interval by Interval Pearson's R -.249 .010 -22.052 .000c
Ordinal by Ordinal Spearman Correlation -.310 .010 -27.929 .000c
N of Valid Cases 7345
a. Not assuming
the null
hypothesis.
b. Using the
asymptotic
standard error
assuming the
null hypothesis.
c. Based on
normal
approximation.
Case
Processing
Summary
C
a
s
e
s
30

Valid Missing T
o
t
a
l
N Percent N Percent N Percent
Sex of respondent * Number
of days in last 4 weeks
respondent has done at least
30 minutes of sport
7345 100.0% 0 0.0% 7345 100.0%
Sex of
responde
nt *
Number
of days in
last 4
weeks
responde
nt has
done at
least 30
minutes
of sport
Crosstab
ulation
Count
Number of days in last
4 weeks respondent
has done at least 30
minutes of sport
Total
.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00
31

Sex of respondent
M
a
l
e
1683 98 92 50 156 53 60 33
F
e
m
a
l
e
2524 110 107 57 215 42 73 38
Total
4
2
0
7
2
0
8
199 107 371 95 133 71 311 6
Symmetric
Measures
Value Asymp. Std.
Errora
Approx. Tb A
p
p
r
o
x
.
S
i
g
.
Interval by Interval Pearson's R -.114 .012 -9.818 .000c
Ordinal by Ordinal Spearman Correlation -.116 .012 -9.994 .000c
N of Valid Cases 7345
a. Not assuming
the null
hypothesis.
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b. Using the
asymptotic
standard error
assuming the
null hypothesis.
c. Based on
normal
approximation.
From the calculation of mean it is found that mean value of variable sex is 1.5, age is
50.3, average number of sports respondents has played in last four weeks corresponds to 1.04. It
can be interpreted that average value of sex is 1.5 that means maximum respondents are female.
They have great knowledge about sports thus, researcher has involved female into this research.
Average value of age variable is 50.3 that shows that average value of participants is 50.3. In
addition to this, mean value of respondents those have done 30 mints of sports is 5.13.
Median value of sex variable is 2. Age is another variable whose median value is 49.
Median of number of respondents who have played sports in last 4 weeks is 1 and median value
of respondents of 30 mints of sports is .00. On other hand mode value of age of respondents is
64. Mode shows the value which continuously repeat in the available data set.
3. Calculation of cross tabulation, correlation
Cross tabulation is the tool which is used in statistical analysis that supports in analysing
the categorical data. That is the most effective way through which individual can analyse
relationship between two or more variables (De Vaus, 2013). It is the effective method through
which researcher can compare the results of one variable with another variable. Correlations
supports the scholar in collecting in-depth information and experiment the information to get
optimistic results.
Correlation is another statical tool that supports in identifying the relationship between
two random variables. It is useful technique because with the help of this tool predictive
relationship between two variables can be exploited (Barradas, 2017). It has been analysed that
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there is strong relationship between age and sports played by respondents. There is 100% cross
tabulation result found.
Correlation can be defined as extent to which two valuables are interrelated with one
another. If there is situation in which changes in one variable brings changes in other then it is
called positive correlation. For example, if value of one variable gets increased then other also
gets increased then it will be defined as positive relationship between both variables. On other
hand if one is decreasing upon increase in other, then it is defined as negative correlation. On
other hand if there is no relationship between two different variables then it is called zero
correlation. The major benefit of using this tool is that by determining correlation individual can
make predications easily (De Vaus, 2013). With the help of this tool researcher can get to know
inter relationship. These results are valid and reliable. Consistency and reliability can also be
known through this tool.
The given data is on sports, thus by calculating the correlations scholar can get to know
naturally occurring variables. With the help of this tool individual can display results in graphical
form and can interpret results in effectively (Franco, Malhotra and Simonovits, 2014).
From the data received it can be interpreted that male respondents those who have played
sport in last four weeks were 1683. On other hand female respondents were 2524. Number of
male respondents, who have played at least 30 mins, were 143, in the same criteria female were
168. Co-relation between male sex and number of respondents who have played in last 4 weeks
were 1345 in the none field and female respondents were 2189. Male candidates those who have
played one time in last four weeks were 774 and female in this section were 938. Male
participants those who have played the sport in the last four weeks two times were 464 in
number. On other hand, female candidates were 507. There were 2 respondents who have played
in last four weeks who were of age 16.
CONCLUSION
From the discussion, it can be interpreted that SPSS is the effective statistical tool that
can support in analysing the data in effective manner and in getting optimistic outcome.
Probability sampling is the great tool that supports in minimizing biasness and collecting
information about the subject matter. From the above calculations, it can be articulated that mode
value of age of respondents is 64 that means this age group people plays sports frequently.
34

REFERENCES
Books and Journals
Barradas, G., 2017. A Cross-Cultural Approach to Psychological Mechanisms Underlying
Emotional Reactions to Music (Doctoral dissertation, Acta Universitatis Upsaliensis).
Brar, S. S., Malik, S. C. and Kaur, J., 2017. Estimation of Median and Mode Using Ranked Set
Sampling. International Journal of Statistics and Systems. 12(3). pp.525-533.
Coumans, F. A. and et.al., 2014. Reproducible extracellular vesicle size and concentration
determination with tunable resistive pulse sensing. Journal of extracellular vesicles, 3(1),
p.25922.
Davis, J., 2015. Know your median from your mean and mode. Primary Teacher
Update. 2015(43). pp.35-36.
De Vaus, D., 2013. Surveys in social research. Routledge.
Fox, J. A., Levin, J. A. and Forde, D., 2013. Elementary statistics in criminal justice research.
Pearson Higher Ed.
Franco, A., Malhotra, N. and Simonovits, G., 2014. Publication bias in the social sciences:
Unlocking the file drawer. Science. 345(6203). pp.1502-1505.
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