ANALYSIS AND INTERPRETATION OF DATAshodhganga.inflibnet.ac.in/bitstream/10603/15854/14/14_chapter 4.pdf100 Descriptive statistics Descriptive statistics provides summary information

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Chapter IV

ANALYSIS AND INTERPRETATION OF DATA The purpose of the study was to find the relationship of socio-economic

status with physical fitness, health status, sports performance, proneness to

disorders, Cancer prone, proneness to coronary Heart diseases, Psychopathic

behavior prone, Healthy personality, Depression prone, Addiction prone among

the sports persons of University of Mysore, who had participated in various

sports and games.

To accomplish the purpose of the study, 311 male sports persons who

had participated and qualified for the final selection trials of various sports and

games held to choose the persons to represent University of Mysore in the

inter-university competitions during the year 2003-04 were selected as subjects.

The method of collection of data of the variables under study was explained in

chapter-III, Methodology.

The collected data were tabulated and statistical analysis was carried out

accordingly, and the same have been presented in this chapter.

To achieve the objectives stated and to verify the hypotheses stated

following statistical techniques were applied in the present investigation.

Descriptive statistics

Cross tabs procedure

Pearson’s product moment correlation

Analysis of Variance-2 way

A brief description of nature of each of the statistical method and

applicability is presented in the following paragraphs.

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Descriptive statistics

Descriptive statistics provides summary information about the

distribution, variability, and central tendency of a variable. In the present

investigation, the description of the sample was taken for several variables

using descriptive statistics technique.

Cross-tabs procedure

The Cross-tabs procedure forms two-way and multi-way tables and

provides a variety of tests and measures of association for two-way tables. The

structure of the table and whether categories are ordered determine what test or

measure to use. In the present study contingency coefficient test was applied to

find out the association between type of games and SES status to find out the

association between the two variables.

Pearson’s product moment correlation (Bi-variate correlation)

The Bi-variate Correlations procedure computes Pearson’s correlation

coefficient measure how variables or rank orders are related. Before calculating

a correlation coefficient, one has to screen the data for outliers (which can

cause misleading results) and evidence of a linear relationship. Pearson’s

correlation coefficient is a measure of linear association. In the present study

correlation technique was applied to find out the influence of SES over other

variables like physical fitness, general health status, performance and

proneness to disorders.

Analysis of Variance-2 way (GLM)

The GLM (General Linear Model) uni-variate procedure provides

analysis of variance for one dependent variable by one or more factors and/or

variables. The factor variables divide the population into groups. Using this

General Linear Model procedure, one can test null hypotheses about the effects

of other variables on the means of various groupings of a single dependent

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variable. One can investigate interactions between factors as well as the effects

of individual factors, some of which may be random. In the present study, two-

way ANOVA was employed to find out the significance of difference between

mean scores of SES and games on various dependent variables along with the

interaction effect.

The statistical techniques were done through SPSS for Windows

(Statistical Presentation System Software, SPSS, 1999, SPSS Inc, New York)

All the significance levels obtained through software are presented as it

is in the following analysis tables. As per the standard norm, any significance

value (P Value) below .05 level is considered as significant. Any P value at

.000 level is considered as highly significant.

For the sake of clarity and clear understanding, the analysis was carried

out in three sections. They were;

Section I : Description of the sample

Section II : Relationship between SES and other variables

Section III : Influence of SES and type of games on selected variables

Section I : Description of the sample selected

In this section, descriptive statistics of the sample, for socio-economic

status, physical fitness variables, subscales and total scores of General Health

Questionnaire aspects, sports performance, proneness to disorders were given

separately.

a) Socio-economic status and type of game

A total of three hundred and eleven subjects who pursued different

games and sports were included in the present research. On the basis of the

nature and features of those sporting events they were broadly classified into

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four categories in accordance with the methodology explained earlier. The

following table indicates the number of subjects in each category with their

Socio Economic Status scores.

Table 2

Distribution of the sample according to groups and Socio-economic Status

SES Games (Groups) Low High

Total

Frequency 72 38 110 Ball Games (BG) Percent 36.7% 33.0% 35.4%

Frequency 44 36 80 Racket Games (RG) Percent 22.4% 31.3% 25.7%

Frequency 64 10 74 Human powered/Free Hand Sports & Games

(HP/FH) Percent 32.7% 8.7% 23.8%

Frequency 16 31 47 Bat & Ball/Stick & Ball Sports & Games (BB/SB) Percent 8.2% 27.0% 15.1%

Frequency 196 115 311 Total Percent 100.0% 100.0% 100.0%

Contingency Coefficient=.326; P<.000 (HS)

As presented in table-2, 35.4% of subjects belonged to Ball games Bat

and Ball/Stick and Ball category, game pursuers accounted for 15.1%.

Human powered / Free hand activities category consisting of Track and

Field, Kho-Kho and Kabaddi events and Ball games category which comprises

of Handball, Football, Volleyball and Basketball demand least personal

equipment or no equipment at all. The contingency coefficient revealed a

significant value (CC=.326; P<.000) indicating that those with low SES

preferred to opt more Human powered games/events compared to those with

high SES, who preferred least of Human powered games/events (Figure 7).

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0%

20%

40%

60%

80%

100%

Perc

enta

ge o

f su

bjec

ts

BG RG HP/FH BB/SB

Groups

Low SES High SES

Illustration No.1

Distribution of the sample (%) according to groups (games) and SES

It was natural for the people of low Socio Economic Status to opt for

such activities where they would be required to invest less money on sports

gears/gadgets and equipment. On the other hand, Racket games such as

Badminton, Tennis, Ball Badminton, Table Tennis, and Bat and Ball/ Stick and

Ball games such as Cricket and Hockey demand moderate to expensive sports

gears besides the sports persons had to possess one or several personal

equipment which could be met by the subjects whose Socio Economic Status

was high. A cursory glance of Table-2 suggests that inexpensive sporting

events were preferred by more number of subjects belonging to low Socio

Economic Status and expensive sporting events were preferred by more

number of subjects belonging to high Socio Economic Status, which fact

corroborates with the study of P.Krishnaiah (1988), Vaidya (1986) and S.K.

Gupta (1986). Thus it became evident that Socio Economic Status and choice

of sporting event were related.

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Table 3

Descriptive statistics for Socio-economic status of the sample

Variable Mean S.D Mode Minimum (0) Maximum(100)

Socio-economic status

43.25 4.05 42.78 33.96 56.43

From Table-3 it was observed that the mean SES scores of the selected

sample was found to be 43.25 with standard deviation of 4.05. The mode of

the sample in SES score was 42.78. The lowest SES score was found to be

33.96 and highest was 56.43. The SES score of the sample was slightly below

50%, which indicates that the SES score of the study group was moderate.

b. Physical Fitness variables

To find out the physical fitness level of the subjects various subtests

were given to them. The detailed descriptive analysis of each of the subtests

and total physical fitness score were presented below.

Table 4

Descriptive statistics for Physical Fitness variables

Variable Mean S.D Mode Minimum Maximum

Weight (in Kgs) 61.92 8.39 65 42 110 Flexibility (in inches) 6.46 5.35 7.00 -20 18 12 min Walk & Run (in meters)

2592.28 311.32 2450.00 1440 3750

Burpee (Squat thrust) (in total numbers)

48.28 11.62 40.00 20 87

Standing Vertical arm thrust test (weight in kgs)

45.74 8.58 45.00 25 95

Bench squat test (weight kgs)

88.80 14.27 80.00 10 125

Total Physical fitness (max 100)

55.04 9.98 57.45 16.09 76.4

Weight: The mean weight of the selected sample was 61.92 kgs with

standard deviation of 8.39. The mode of this variable was 65. The weight of

the selected sample ranged from 42 to 110 kilograms.

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Flexibility: The mean flexibility value of the selected sample was found

to be 6.46 inches and standard deviation was 5.35. The mode value of

flexibility was 7. The flexibility of the selected sample ranged from -20 to +18

inches.

12 minutes walk and run test: The mean distance in meters for the 12

minutes walk and run test of the selected sample was found to be 2592.28

meters with standard deviation was 311.32. The mode value was 2450. The

total distance covered by the selected sample ranged from 1440 to 3750 meters.

Burpee (Squat thrust) test: The selected sample had a mean burpee

value of 48.28 with standard deviation of 11.62. The mode value of burpee

was 40. The number of burpees performed by the selected sample ranged from

20 to 87.

Standing Vertical arm thrust test: The selected sample had a mean

standing vertical arm thrust value of 45.74 kilograms with standard deviation of

8.58. The mode value was 45. The performance in standing vertical arm thrust

of the selected sample ranged from 25 to 95 kilograms.

Bench squat test: The mean value of bench squat test of the selected

sample was found to be 88.80 kilograms and standard deviation was 14.27.

The mode value of bench squat was 80. The performance in bench squat of the

selected sample ranged from 20 to 125 kilograms.

Total physical fitness: The selected sample had a mean total physical

fitness value of 55.04 with standard deviation of 9.98. The mode value was

57.45. The physical fitness scores of the selected sports persons ranged from

16.09 to 76.04. The total physical fitness value of the sample was 55.04

percent out of 100, which indicates that the sample had slightly higher

moderate physical fitness.

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c. General Health Status (Dimensions of symptomatology)

Table 5

Descriptive statistics for total and sub scales of General Health Status


Somatic symptoms 3.75 2.98 4 0 15

Anxiety/Insomnia 4.23 3.42 3 0 17

Social dysfunction 4.76 2.70 3 0 15

Severe depression 4.30 3.29 4 0 16

Total GHQ 17.05 9.53 19 0 49

Somatic symptoms: The mean somatic symptoms scores of the sample

was found to be 3.75 with the standard deviation of 2.98. This indicates that

the sample had very less negative somatic symptoms. The mode was 4 and

scores ranged from 0 to 15. The score was very less in this dimension

indicating that the sample had least somatic symptoms, which clearly reveals

that group had minimum physical complaints.

Anxiety/Insomnia: The mean anxiety/insomnia scores of the sample

was found to be 4.23 with the standard deviation of 3.42. This indicates that

the sample had very less anxiety and insomnia symptoms. The mode was 3

and scores ranged from 0 to 17. Even in this dimension, the group had least

score, further indicating that group had minimum anxiety and insomnia (lack of

sleep) symptoms.

Social dysfunction: The selected sample had the mean social

dysfunction score of 4.76 with the standard deviation of 2.70. This indicates

lower social dysfunction of the sample in this dimension. The mode was 3 and

scores ranged from 0 to 16. In social dysfunction, the study sample had least

scores as much as 2.70, where study sample showed very good in social

functioning.

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Severe depression: The mean scores in this dimension was found to be

4.30 with the standard deviation of 3.29. This indicates that the sample had

very less severe depression symptoms. The mode was 4 and scores ranged

from 0 to 16. As in the cases of other dimensions, in this dimension also the

study group had least severe depression scores, indicating further that the group

had almost no severe depression symptoms, showing very good health status.

Total GHQ scores: The selected sample had the mean total GHQ score

of 17.05 with the standard deviation of 9.53. This indicates better health status

of the sample in all the dimensions of symptomatology. The mode was 19 and

scores ranged from 0 to 49. In other words, the group had very good health

status, having totally symptom free which could be an added factor for physical

fitness.

d. Sports performance

Table 6

Descriptive statistics for sports performance


Sports performance

118.98 11.71 112 92 146

The mean value of sports performance of the selected sample was found

to be 118.98 with standard deviation of 11.71. The mode of the sample was

112. The lowest performance score was 92 and highest was 146 out of 156. A

performance score of 118.98 out of 156 indicates 76.23 percent out of 100,

which is above 75 percentiles, where one can definitely say that the sample

selection after initial screening was a true representation of the universe, where

the sample represents best selection from each college.

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e. Proneness to disorders

The descriptive statistics for various subscales of Proneness to disorders

for selected sample were given below.

Table 7 Descriptive statistics for Proneness to Disorders

Variable Mean S.D Mode Minimum Maximum Cancer proneness 5.40 1.89 6.00 0 10

CHD proneness 5.72 1.93 6.00 0 10

Psychopathic proneness

5.72 1.92 6.00 1 10

Healthy personality 11.88 2.96 13.00 2 19

Depression proneness

6.61 1.83 6.00 1 10

Addiction proneness

4.99 1.84 4.00 0 10

Cancer proneness: The mean cancer proneness scores of the sample

was found to be 5.40 with the standard deviation of 1.89. This indicates

moderate proneness of the sample in this dimension. The sample is not easily

prone to cancer diseases, as the stress level they may experience is moderate.

The mode was 6 and scores ranged from 0 to 10.

CHD proneness: The mean CHD proneness scores of the sample was

found to be 5.72 with the standard deviation of 1.93. This indicates moderate

proneness of the sample in this dimension. Again in this factor the sample

showed average signs of proneness to CHD, which is really a good feature of

the sample. The mode was 6 and scores ranged from 0 to 10.

Psychopathic behaviour proneness: The selected sample had the mean

psychopathic behaviour proneness score of 5.72 with the standard deviation of

1.92. This indicates moderate proneness of the sample in this dimension. Too

much of psychopathic proneness leads to destructive mentality, which was

absent in the study sample. The mode was 6 and scores ranged from 0 to 10.

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Healthy personality: The sample had mean healthy personality scores

of 11.88 with the standard deviation of 2.96. This indicates that the sample had

moderate healthy personality. The mode was 13 and scores ranged from 2 to

19. The healthy personality always leads to better adjustment to self and the

surroundings, where a Sportsperson maintains such healthy personality can

perform better in his events.

Depression proneness: The selected sample had the mean depression

proneness score of 6.61 with the standard deviation of 1.83. This indicates

slightly higher proneness of the sample in this dimension. The mode was 6 and

scores ranged from 1 to 10. But this is different from severe depression (GHQ)

where in this scale only proneness could be evaluated, not the actual one. The

fear of failure, under performance, not being able to get in to the creamy layer

etc could be attributed for such proneness to depression.

Addiction proneness: The mean addiction proneness scores of the

sample were found to be 4.49 with the standard deviation of 1.84. This

indicates that the sample had moderate addiction proneness. The mode was 4

and scores ranged from 0 to 10. The higher the negative symptoms more

would be the addiction as negative symptoms lead to addiction process.

However, present group showed moderate levels of addiction proneness, which

could be simply situational.

110

Section –II Relationship between Socio-economic Status and other study

variables a) SES and Physical Fitness.

Hypothesis: There is no relationship between SES and Physical Fitness of

Sports students.

To test the above hypothesis, the significance of Pearson product

moment correlation coefficient was calculated for SES and Physical fitness and

presented in table 8.

Table-8

Correlation between games and Physical fitness –Overall and group wise:

SES score and physical fitness were found to be negatively correlated

and statistically significant. Correlation coefficient of -.230 with 309 degrees

of freedom was found to be highly significant (P<.000). It means, the

formulated hypothesis was rejected for overall, ball games & human powered

games/events, and accepted for racket games & Bat & ball/stick & ball games.

On the whole, we can say that as the SES increases physical fitness decreases

linearly and vice-versa.

When ball games were considered separately, SES score and physical

fitness were found to be negatively correlated and significant. Correlation

coefficient of -.206 with 118 degrees of freedom was found to be significant

Games (Groups) Correlation coefficient

df Sig. Interpretation

Overall -.230 309 .000 Significant

Ball games -.206 108 .031 Significant

Racket games -.096 78 .396 Non-Significant

Human powered games/Events

-.517 72 .000 Significant

Bat & Ball/ Stick & Ball -.243 45 .100 Non-Significant

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(P<.031). In other words, we can say that as the SES increases physical fitness

decreases linearly and vice-versa.

SES score and physical fitness (of racket games group) were found to be

not related and independent of each other as the obtained correlation coefficient

failed to reach the significance level criterion.

When human powered games and events were considered separately, the

SES and physical fitness were found to be correlated significantly and

negatively. In other words, as the SES score level increases physical fitness

decreases linearly and vice-versa.

When bat/ball and stick/ball games were considered separately, SES and

physical fitness were found to be independent of each other. No statistical

significance was found between these two variables.

The life style of people belonging to high Socio Economic Status was

characterized by use of motor vehicles, increased use of electrical and

electronic appliances, passive recreational pursuits, people to do strenuous

activities, which substantially jeopardize development and maintenance of

physical fitness. On the other hand people of low Socio Economic Status by

and large depend on their physical prowesses to perform household chores,

commute short and moderately short distances on foot, employ less varieties of

electrical and electronic gadgets, prefer active modes of recreation. PRISTA

and MARUQES who concluded physical activity was more intense among

underprivileged students due to domestic activities and walking time per day,

support the finding of the present study that higher the Socio Economic Status

lower the physical fitness and lower the Socio Economic Status, higher was the

physical fitness.

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The phenomenon was due to the reluctant attitude of high Socio

Economic Status subjects to pursue sports seriously. Since the subjects

belonging to low Socio Economic Status group tend to take part in the training

programme seriously in pursuit of career opportunities their physical fitness

level was better compared to the subjects of high Socio Economic Status.

Under the Racket games the activities included were Ball Badminton,

Badminton (shuttle), Tennis and Table Tennis. As, in the intercollegiate level

the players of these games depend more on their skills and strategies than

physical fitness, no significant relationship was observed between SES and

physical fitness.

Track and field sports, Kabaddi and Kho-Kho - the indigenous games of

India – though encompass varieties of skills, their acquisition and application to

acquit well in serious contests depends upon the physical prowesses of the

sportspersons. It is logical then that human powered game’s sportspersons

possess a reasonably high level of physical fitness. When the association of

physical fitness of these students with SES was investigated, the variables were

found to be related significantly, but negatively, which may be noted. The

phenomenon that higher the SES, lower the physical fitness and vice versa may

be attributed to achievement motivation and perseverance which were seen in

good measure among the sports persons of low SES.

The games Cricket and Hockey were included under the Bat and Ball /

Stick and Ball games. The subjects’ economic status was not related to

physical fitness. A cursory glance of Table-8 indicates that about 66% of these

subjects hail from high Socio-economic group and 34% belong to low SES

group. The high SES of majority of the subjects and increased dependence on

skills and strategies in these games may be the reason behind this phenomenon.

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Toddomico(1982), Dennis(1981), Parks (1980), Grewal (1986),

Ekblom(2005), Prista and Marques (1998) and Sack and Thiel (1979) in their

studies stated that SES yield greater influence on the involvement of individual

selection of physical activity and their physical fitness.

b. SES and Dimensions of Symptomatology (General Health Status)

Hypothesis: There is no relationship between SES and Dimensions of

Symptomatology (General health Status) of sports students.

To test the above hypothesis the significance of Pearson’s product

moment correlation coefficient was calculated for SES and dimensions of

Symptomatology (General health Status) of sports students of University of

Mysore were presented in Table-9.

When Socio-economic status (SES score) was correlated with subscales

and total dimensions of symptomatalogy, it was found that SES was found to

be negatively correlated and statistically significant with all of the subscales,

except for social dysfunction. As the SES score level increases somatic

symptoms, anxiety/insomnia, severe depression and total score decreases

linearly and vice-versa. In other words higher SES score leads to better health

status. From table-9 it is revealed that the formulated hypothesis was rejected.

It means that there is a significant relationship between SES and GHS of

students of University of Mysore. Sub-scales of GHS is also significantly

related with SES except social dysfunction.

When only ball games were considered, all the dimensions of general

health questionnaire including total scores were not significantly related to SES

as all the obtained correlation coefficients were found to be non-significant.

Hence, the hypothesis formulated for the above is accepted.

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Table 9.

Correlation coefficients between Symptomatology of GHQ with SES: Overall and group-wise

Groups

Overall Ball Games Racket games Human Powered/Events

Bat & Ball / Stick & Ball

Symptomatology (GHQ)

Cor Sig Cor Sig Cor Sig Cor Sig Cor Sig Somatic symptoms.

-.183 .001 (S) -.067 .487 (NS) -.255 .023 (S) -.077 .516 (NS) .044 .770 (NS)

Anxiety/Insomnia -.119 .001 (S) -.029 .764 (NS) -.133 .240 (NS) .070 .556 (NS) -.184 .216 (NS)

Social dysfunction -.091 .110 (NS) -.111 .248 (NS) -.041 .719 (NS) .067 .570 (NS) -.115 .440 (NS)

Severe depression -.248 .000 (S) -.082 .395 (NS) -.497 .000 (S) .017 .885 (NS) -.086 .567 (NS)

Total GHQ -.211 .000 (S) -.083 .387 (NS) -.323 .003 (S) -.024 .839 (NS) -.116 .437 (NS)

Degrees of freedom

309 118 78 72 45

Note: S-Significant:: NS-Non-significant:: Cor- Correlation coefficient:: Sig- Significance (P)

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Except for anxiety/insomnia and social dysfunction, all other factors

including total GHQ score were found to be significant and negatively related.

As the SES levels increased somatic symptoms, severe depression and total

scores decreased linearly and vice-versa. In other words higher SES leads to

better health status in the above-mentioned dimensions. However,

anxiety/insomnia and social dysfunction were found to be independent of SES.

From the Table-9 it is revealed that the formulated hypothesis was rejected. It

means that there is a significant relationship between SES and general health

status of students of University of Mysore. Sub scales GHS were also

significantly related with SES except social dysfunction. Hypothesis

formulated in this regard is accepted for anxiety/insomnia & social

dysfunction, and rejected for the rest of the dimensions.

All the dimensions of general health questionnaire including total scores

were not significantly correlated to SES scores as all the obtained correlation

coefficients were found to be not significant when only Ball games were

considered. The hypothesis is accepted for the dimensions of general health

questionnaire.


were not significantly correlated to SES score as all the obtained correlation

coefficients were found to be not significant, when only human powered games

were considered. The hypothesis is accepted for the dimensions of general

health questionnaire.


were not significantly related to SES as all the obtained correlation coefficients

were found to be not significant, when only Bat and ball/ stick and ball games

were considered. The hypothesis is accepted for the dimensions of general

health questionnaire.

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Persons of high Socio Economic Status were likely to be stable and

hence did not show much of somatic symptoms and anxiety, did not confront

high degree of insomnia and depression. Hence, the study suggests that high

Socio Economic Status group enjoyed better general health status as compared

to low Socio Economic Status group of sports persons. It may be noted that

general health questionnaire helped to know how the subjects felt about their

health, and it did not make a comprehensive assessment of health of the

subjects. Waltham’s study had indicated that social conditions lead to

depriving children of material care that leads to low central nervous system

serotonin function, which underlines depression and hostility, which contribute

to ill health. It would be hazardous then to conclude Socio Economic Status

and overall health status (when estimated with the help of GHQ) were

positively correlated.

Bucher (1974), Koebel Swank and Shelburne (1992), William and

Curtis (1990), Spink (2003), Spreitzer E (1992), Adegoke (1986) and Brekke

(1986) suggest that fitness for effective living implies freedom from diseases

enough strength agility and skill to meet the demands of daily living. They

found a positive relationship between levels of physical activity and effect of

SES on feeling of well being.

c) SES and Sports performance

Hypothesis: There is no relationship between SES and Sports performance of

sports students.


moment correlation coefficient was calculated for SES and Sports performance

of sports students of University of Mysore, and the same were presented in

Table-10.

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Table-10 Correlation coefficients between SES games and Sports

performance – Overall and group wise Games Correlation

coefficient Df Significance Interpretation

Overall .130 309 .022 Significant

Ball games .043 118 .655 Non-Significant

Racket games .160 78 .155 Non-Significant

Human powered games/Events

.326 72 .000 Significant

Bat & Ball/ Stick & Ball .161 45 .279 Non-Significant

SES score and sports performance were found to be positively correlated

and statistically significant. Correlation coefficient of .130 with 309 degrees of

freedom was found to be significant (P<.022). The formulated hypothesis was

rejected as the product moment correlation coefficient between SES and sports

performance is 0.130, which is significant at 0.005 level. It means there is a

significant relationship between SES and sports performance of students of

University of Mysore. In other words, we can say that as the SES score

increases sports performance also increases linearly. The hypothesis

formulated for the above is rejected for overall and Human powered

games/events and accepted for rest of the factors. A careful observation further

reveled that the overall relationship between SES and sports performance was

contributed maximum by human powered games/events.

Sports performance and SES score were found to be not related and

independent of each other as the obtained correlation coefficient failed to reach

the significance level criterion, in case of Ball games, Racket games and Bat

and Ball or Stick and Ball games.

The relationship between SES and Sports performance, in case of

Human powered games/events were found to be positively correlated and

statistically significant as correlation coefficient of -0.326 with 72 degrees of

freedom was found to be significant. (P<.841).

118

Sports performance was dependent upon a number of factors such as

indulgence in a coaching regimen, availability of a competent coach and

trainer, nutritious food, availability of necessary gadgets or equipment and

competition experience. However, importance of possession of appropriate

level of physical fitness, proficiency over skills, adaptability, favourable

attitude towards training and competition, discipline and psychological

depositions were of no less importance. Most of these were developed and

acquired with substantial spending of time, energy and money. Thus, the

finding, higher Socio Economic Status group students show better performance

in sports was justified.

Under the Ball games category, the games such as Handball, Football,

Volleyball and Basketball were included. For the pursuance of these games,

there was hardly any financial constraint on the part of students at the

collegiate level, since the colleges or University provided almost every

equipment. Even training and coaching were freely available in the University

of Mysore. It may be due to these reasons no significant relationship was

obtained between Socio Economic Status and sports performance in ball games

category.

Although Racket games demand a host of supplies and the players have to

incur substantial amount of money to procure the needed materials and expend on

travel and avail the services of trainers, which the well-to-do can only afford, in

the present study no significant relationship was observed between sports

performance and SES among Racket game players category. Analysis of

situations suggests that professional sport coaching has not crept in a big way at

the area chosen for the study. University and the colleges were also standing by

the side of the subjects by providing equipment, and facilities were mostly

provided free of charges. These benefits had to arrive at the conclusion that ‘SES

and sports performance were found to be not related and independent of each

other’ despite a couple of earlier studies suggested otherwise.

119

The argument put forth about the non-significant relationship between

physical fitness and SES was vindicated on observing the relationship between

SES and sports performance. It evidently proves that Bat and Ball / Stick and

Ball games of this study were related more with skill and strategy.

Singh (1984), pate (1984), Johnson and Buskirk (1974), Schoolarnder

(2003), Grupe’s (1972), Sidentop (1984), Sharma (1984) and Singh (2003)

were of the different views that it was not physical, physiological,

environmental and socio-economic factors alone that influence sports

performance. Psychological factors were also playing dominant role besides

physique, body composition, technique and tactics level of motor and physical

abilities, personality make up of a sportsmen etc, which influence sports

performance.

d) SES and Proneness to disorders

Hypothesis: There is no relationship between SES and Proneness to

disorders of sports students.


moment correlation coefficient was calculated for SES and Proneness to

disorders of sports students of University of Mysore and the same were

presented in Table-11.

120

Table 11

Correlation coefficients between SES and Proneness to Disorders –Overall and Group-wise

Groups

Overall Ball Games Racket games Human Powered/Events

Bat & Ball / Stick & Ball Proneness

Cor Sig Cor Sig Cor Sig Cor Sig Cor Sig Cancer proneness -.087 .125

(NS) .061 .526

(NS) -.113 .319

(NS) -.179 .127

(NS) -.119 .425

(NS) CHD proneness -.069 .225

(NS) -.124 .198

(NS) -.037 .743

(NS) .055 .640

(NS) -.131 .380

(NS) Psychopathic proneness

-.071 .211 (NS)

-.023 .815 (NS)

-.193 .086 (NS)

-.112 .341 (NS)

.028 .850 (NS)

Healthy personality -.027 .635 (NS)

-.014 .884 (NS)

-.065 .570 (NS)

.059 .615 (NS)

-.063 .675 (NS)

Depression proneness -.064 .264 (NS)

.029 .766 (NS)

-.167 .138 (NS)

.170 147 (NS)

-.239 .105 (NS)

Addiction proneness -.150 .008 (S) .040 .681 (NS)

-.313 .005 (S) -.119 .311 (NS)

-.117 .433 (NS)

Degrees of freedom 309 118 78 72 45

Note: S-Significant: NS-Non-significant: Cor-Correlation coefficient : Sig- Significance (P)

121

Socio-economic status (SES) was found to be negatively correlated with

addiction proneness (r=-.150; P<.008) and rest of the proneness subscales were

found to be independent of SES. As the SES increases addiction proneness

decreases and vice versa. The formulated hypothesis was rejected with

reference SES and overall groups and racket games group. On the whole, since

most of relationships were found to be non-significant, the hypothesis

formulated for proneness to disorders is accepted.

The Ball games chosen for the study call upon the players to perform

under substantial amount of physical strain. Since active involvement in

strenuous physical activity fosters health, the subjects of Ball games category

enjoyed good health. This may be the reason behind Socio Economic Status

not showing significant relationship with proneness to disorders in this

category.

Socio-economic status (SES) was found to be negatively correlated with

addiction proneness (r=-.313; P<.005) and rest of the proneness subscales were

found to be independent of SES. As the SES increased addiction proneness

decreased linearly and vice versa. Even though there was negative

directionality in the correlation coefficients, they failed to reach the

significance level criterion.

All the subscales of proneness to disorders were not significantly related

to SES as all the obtained correlation coefficients were found to be non-

significant, when only ball games, Human powered games, Bat & Ball/Stick &

Ball games are considered separately.

Solomna (1984), WHO (2004), Ader and Cohen (1975), Sklar and

Anishman (1981), Gilmore (1983), Dun et.al. (2001), Porch and Schullen

122

(1998) and Tuinstra et.al (1998) studies strongly revealed that there was varied

relations-ship between SES and health risk behaviours. Analysis indicated that

the relationship between SES and health risk behaviour is not as linear as is

often found in adulthood. Overall there was an absence in relationship SES

and health risk behaviour. The only exception applies to sports which is

linearly related to SES.

123

Section-III

Influence of Socio-economic Status and type of

games on selected variables

In this section results of 2-way ANOVA for various parameters taking

SES and type of games as Independent variables are presented to find out effect

of SES (low and High) and type of games (ball games, racket games, Human

Powered/ Free hand and Bat & Ball and Stick & Ball) on parameters selected

along with the interaction effects.

a) Physical fitness

Hypothesis : There is no significant interaction between SES and games on

physical fitness of sports students.

Table 12 Mean scores of physical fitness for sports students playing different

games having different SES Games (Groups)

SES Ball Racket

Human Powered / Free hand

Bat & Ball Stick &

Ball

Overall

Mean S.D Mean S.D Mean S.D Mean S.D Mean S.D Low 57.07 8.76 46.98 10.50 60.87 6.86 56.46 7.31 55.83 9.67

High 57.86 8.52 44.58 7.74 61.53 6.85 55.21 6.74 53.68 10.39

Total 57.26 8.67 45.72 9.18 61.15 6.82 56.06 7.08 55.04 9.98

124

Table 13 ANOVA table for Mean scores of physical fitness of sports students

playing different games having different SES

Source of variation Sum of Squares Df Mean Square F value P value

Between Games (A) 10077.557 3 3359.186 49.900 .000

Between SES (B) 19.127 1 19.127 0.284 .594

Interaction (A x B) 135.361 3 45.120 0.670 .571

Error 20397.493 303 67.318

Total 972837.183 311

Corrected Total 30856.592 310

A significant difference existed in the mean physical fitness scores of

subjects playing different games (F=49.90; P<.000). Further mean values

revealed that those who were playing human powered/free hand games had

significantly higher physical fitness compared to other subjects playing ball

games, bat and ball/ stick and ball and those subjects who were playing racket

games had significantly lesser physical fitness, which is clearly depicted in

figure 8. However, students belonging to low and high SES did not differ

significantly in their physical fitness scores. The interaction effect between

games and SES levels was also found to be non-significant. Hence the

formulated hypothesis is accepted. There is no significant interaction between

SES and games on physical fitness of sports students.

125

Note: BG-Ball games: RG-racket games: HP/FH-Human powered/Freehand: BB/SB-Bat/ball & Stick/Ball

Illustration No.2 Mean scores of physical fitness of sports students playing different games having different SES

35

40

45

50

55

60

65

Mea

n Ph

ysic

al fi

tnes

s sc

ores

BG RG HP/FH BB/SB TotalGames

Low-SES High-SES Total

126 b) Dimensions of symptomatology (General Health Status)

Hypothesis :There is no significant interaction between SES and games on

Somatic Symptoms (GHS) of Sports students.

Table 14

Mean scores of Somatic Symptoms (GHS) for sports students playing Different games having different SES

Games (Groups)

Ball Racket Human

Powered/ Free hand

Bat & Ball Stick & Ball

Overall SES


High 3.76 3.22 2.39 2.52 4.60 2.17 2.90 2.81 3.17 2.88

Total 3.95 3.25 2.82 2.35 5.12 2.85 2.70 2.58 3.75 2.98

Table 15 ANOVA table for Mean scores of Somatic Symptoms (GHS) of sports

students playing different games having different SES


Between Games (A) 2680.336 3 52.859 6.509 .000

Between SES (B) 4.002 1 4.002 .493 .483

Interaction (A x B) 13.858 3 4.619 .569 .636

Error 2460.654 303 8.121

Total 7125.000 311


A significant difference existed in the mean somatic symptoms scores of

subjects playing different games (F=6.509; P<.000). Further mean values

revealed that those who were playing human powered/free Hand Games had

significantly higher somatic symptom scores compared to other subjects

127

playing ball games, and racket games and lastly subjects playing bat and ball/

Stick and Ball Games had significantly lesser somatic symptom scores, which

is clearly depicted in figure 9. However, students belonging to low and high

SES did not differ significantly in their somatic symptom scores. The

interaction effect between games and SES levels was also found to be non-

significant. Hence the formulated hypothesis is accepted. There is no

significant interaction between SES and games on Somatic Symptoms (GHS)

of Sports students.


Illustation No.3 Mean scores of Somatic Symptoms (GHS) of sports students playing

different games having different SES.

1

2

3

4

5

6

Mea

n So

mat

ic

scor

es



128

Hypothesis :There is no significant interaction between SES and games on

Social dysfunction (GHS) of Sports students

Table 16

Mean scores of social dysfunction (GHS) for sports students playing different games having different SES

Games (Groups)

Ball Racket Human

Powered/ Free hand


Overall SES

Mean S.D Mean S.D Mean S.D Mean S.D Mean S.D Low 4.89 2.72 4.34 2.22 5.37 2.71 4.38 1.86 4.88 2.57 High 4.18 2.39 4.58 3.02 6.20 4.21 4.42 2.86 4.55 2.91 Total 4.65 2.63 4.45 2.59 5.49 2.93 4.40 2.54 4.76 2.70

Table 17

ANOVA table for Mean scores of Social dysfunction (GHS) of sports students playing different games having different SES


Between Games (A) 51.512 3 17.171 2.379 .070

Between SES (B) 0.550 1 0.550 0.076 .783

Interaction (A x B) 19.011 3 6.337 0.878 .453

Error 2187.356 303 7.219

Total 9304.000 311


Neither the subjects playing different games nor the subjects belonging

to different SES levels differ significantly in their mean social dysfunction

scores. Even the interaction effect between games and SES was found to be

significant indicating that pattern of social dysfunction scores was same for

subjects with different SES levels irrespective of the game they play. Hence,

the formulated hypothesis is accepted that there is no significant interaction

between SES and games on Social dysfunction.

129

Hypothesis: There is no significant interaction between SES and games on Anxiety/Insomnia (GHS) for Sports students.

Table 18

Mean scores of Anxiety/insomnia (GHS) scores for sports students playing different games having different SES

Games (Groups)

Ball Racket Human Powered/ Free hand


Overall SES


High 4.76 4.74 3.36 2.57 4.10 2.73 3.26 2.50 3.86 3.47

Total 4.48 3.94 3.85 3.07 4.76 3.31 3.47 2.65 4.23 3.42

Table 19 ANOVA table for Mean scores of Anxiety/Insomnia (GHS) for sports

students playing different games having different SES


Between Games (A) 43.304 3 14.435 1.238 .296

Between SES (B) 11.188 1 11.188 0.960 .328

Interaction (A x B) 22.989 3 7.663 0.657 .579

Error 3531.744 303 11.656

Total 9196.000 311


In all the individual factors as well as interaction factors, the obtained F

values failed to reach significance levels. In other words, subjects playing

different games did not differ significantly in their mean anxiety/insomnia

scores as well as subjects with different SES levels. Also, the interaction effect

between games and SES was found to be non-significant indicating that pattern

of anxiety/insomnia scores was same for subjects with different SES levels

130

irrespective of the game they play. Hence the formulated hypothesis is accepted

that there is no significant interaction between SES and games on

Anxiety/Insomnia of sports students.

Hypothesis: There is no significant interaction between SES and games

on Severe Depression (GHS) for Sports students.

Table 20 Mean scores of Severe depression (GHS) for sports students playing

different games having different SES

Games (Groups)

Ball Racket Human

Powered/ Free hand


Overall SES


High 4.26 3.73 2.08 2.82 4.90 2.85 2.94 3.59 3.28 3.47

Total 4.40 3.26 3.76 3.26 5.57 3.10 3.00 3.11 4.30 3.29

Table 21

ANOVA table for Mean scores of Severe Depression (GHS) for sports students playing different games having different SES


Between Games (A) 122.078 3 40.693 4.177 .006

Between SES (B) 59.244 1 59.244 6.081 .014

Interaction (A x B) 104.688 3 34.896 3.582 .014

Error 2951.875 303 9.742

Total 9122.000 311


Subjects playing different games differed significantly in their mean severe

depression scores (F=4.177; P<.006). Further, mean values revealed that those who

were playing human powered/free Hand Games had significantly higher severe

depression scores compared to other subjects playing ball games, and racket games

131

and lastly subjects playing bat and ball/ stick and ball had significantly lesser severe

depression scores, which is clearly depicted in figure 10. Students belonging to low

SES had significantly (F=6.081; P<.014) higher severe depression scores compared to

students with high SES. Also, the interaction effect between games and SES levels

was found to be significant (F=3.582; P<.014) where subjects with high SES playing

racket games had significantly lesser scores compared to subjects with low SES

involved in racket games, which is very much illustrated in the figure 10. Hence, the

formulated hypothesis is rejected. In other words, there is a significant interaction

between SES and games in severe depression.

Note: BG-Ball games: RG-racket games: HP/FH-Human powered/Freehand: BB/SB-

Bat/ball & Stick/Ball

Illustration No.4 Mean scores of Severe depression (GHS) for sports students playing

different games having different SES.

1

2

3

4

5

6

Mea

n Ps

y se

v sc

ores



132

Hypothesis: There is no significant interaction between SES and games on General Health (GHS total scores) of Sports students.

Table 22 Mean scores of GHS -total scores for sports students playing

different games having different SES

Games (Groups)



Overall SES


Table 23

ANOVA table for Mean scores of GHS-total scores for sports students playing different games having different SES

Source of variation Sum of Squares Df Mean

Square F value P value

Between Games (A) 1228.783 3 409.594 4.840 .003

Between SES (B) 151.301 1 151.301 1.788 .182

Interaction (A x B) 199.027 3 66.342 0.784 .504

Error 25639.874 303 84.620

Total 118503.000 311


A significant difference existed in the mean total GHQ scores of

subjects playing different games (F=4.840; P<.003). Further, mean values

revealed that those who were playing human powered/free Hand Games had

significantly higher GHQ scores compared to other subjects playing ball

games, and racket games and bat and ball/ stick and ball games which is shown

in figure 11. However, students belonging to low and high SES did not differ

133

significantly in their total GHQ scores. The interaction effect between games

and SES levels was also found to be non-significant. Hence the formulated

hypothesis is accepted that there is no interaction effect between games and

SES levels on GHS of Sports students.


Illustration No.5

Mean scores of GHS for sports students playing different games having different SES

8

12

16

20

24

Mea

n G

HQ

sco

res



134

Hypothesis : There is no significant interaction between SES and games on sports performance of sports students

Table 24

Mean scores of sports performance for sports students playing different

games having different SES

Games (Groups)

Ball Racket Human

Powered/ Free hand


Overall SES


Table 25

ANOVA table for Mean scores of sports performance for sports students



Between Games (A) 2004.130 3 668.043 5.782 .001

Between SES (B) 2.292 1 2.292 0.020 .888

Interaction (A x B) 104.202 3 34.734 0.301 .825

Error 35005.996 303 115.531

Total 4418894.000 311


Subjects playing different games differed significantly in their mean sports

performance scores (F=5.391; P<.001). Further mean values revealed that those who

were playing racket games and ball games had higher sports performance compared to

other subjects playing human powered/free hand games and those who were involved

in bat/ball and stick/ball games had significantly lesser sports performance, which is

clearly depicted in figure 12. Students belonging to high SES had significantly

(F=4.403; P<.037) higher sports performance scores compared to students with lower

135

SES. The interaction effect between games and SES was found to be non-significant.

Hence the formulated hypothesis is accepted that there is no significant interaction

between SES and Games on sports performance of sports students.

Note: BG-Ball games: RG-racket games: HP/FH-Human powered/Freehand: BB/SB-

Bat/ball & Stick/Ball

Illustration No.6 Mean scores of sports performance for sports students playing different

games having different SES

105

110

115

120

125

Mea

n Pe

rfor

man

ce

scor

es



136


Cancer proneness of sports students.

Table 26 Mean scores of Cancer Proneness for sports students playing different


Ball Racket Human

Powered/ Free hand


Overall SES


High 5.71 1.61 5.44 1.89 5.00 1.41 5.06 2.05 5.39 1.81

Total 5.44 1.84 5.48 1.92 5.49 1.74 5.02 2.20 5.40 1.89

Table 27

ANOVA table for Mean scores of Cancer Proneness for sports students playing different games having different SES


Between Games (A) 8.533 3 2.844 0.788 .501

Between SES (B) 0.017 1 0.017 0.005 .945

Interaction (A x B) 6.806 3 2.269 0.629 .597

Error 1093.138 303 3.608

Total 10162.000 311



to different SES levels differ significantly in their mean cancer proneness


non-significant indicating that pattern of cancer proneness scores was same for


the formulated hypothesis is accepted. That means there is no significant

interaction between SES and games on Cancer Proneness of Sports students.

137

Hypothesis : There is no significant interaction between SES and games on Coronary Heart Diseases Proneness of sports students.

Table 28

Mean scores of Coronary Heart Diseases proneness for sports students playing different games having different SES

Games (Groups)



Overall SES


Table 29 ANOVA table for Mean scores of Coronary Heart Diseases Proneness for

sports students playing different games having different SES Source of variation Sum of Squares df Mean Square F value P value

Between Games (A) 4.504 3 1.501 0.399 .754

Between SES (B) 0.223 1 .223 0.059 .808

Interaction (A x B) 2.490 3 .830 0.221 .882

Error 1139.878 303 3.762

Total 11314.000 311




different games did not differ significantly in their mean CHD proneness scores

as well as subjects with different SES levels. Also, the interaction effect


of CHD proneness was same for subjects with different SES levels irrespective

138

of the game they play. Hence, the formulated hypothesis is accepted. That

means there is no significant interaction between SES and Games on Coronary

Heart Diseases Proneness of sports students.

Hypothesis : There is no significant interaction between SES and games on Psychopathic Personality proneness of sports students.

Table 30 Mean scores of Psychopathic Personality Proneness for sports students


Games (Groups)

Ball Racket Human

Powered/ Free hand


Overall SES


Table 31

ANOVA table for Mean scores of Psychopathic Proneness for sports students playing different games having different SES


Between Games (A) 14.907 3 4.969 1.352 .258

Between SES (B) 12.581 1 12.581 3.424 .065

Interaction (A x B) 8.865 3 2.955 0.804 .492

Error 1113.334 303 3.674

Total 11308.000 311



to different SES levels differ significantly in their mean psychopathic

139

personality scores. Even the interaction effect between games and SES was

found to be non-significant indicating that pattern of psychopathic personality

scores was same for subjects with different SES levels irrespective of the game

they play. Hence, the formulated hypothesis is accepted and there is no

significant interaction between SES and Games on Psychopathic Personality

Proneness of sports students.

Hypothesis : There is no significant interaction between SES and games on Healthy Personality of sports students.

Table 32 Mean scores Healthy Personality scores for sports students playing

different games having different SES. Games (Groups)

Ball Racket Human

Powered/ Free hand


Overall SES


Table 33

ANOVA table for Mean scores of Healthy Personality for sports students playing different games having different SES

Source of variation Sum of Squares df Mean Square F value P value

Between Games (A) 12.799 3 4.266 0.482 .695

Between SES (B) 0.745 1 0.745 0.084 .772

Interaction (A x B) 4.110 3 1.370 0.155 .926

Error 2680.248 303 8.846

Total 46586.000 311


140



different games did not differ significantly in their mean healthy personality

scores as well as subjects with different SES levels. Also, the interaction effect


of healthy personality was same for subjects with different SES levels

irrespective of the game they play. Hence, the formulated hypothesis is

accepted and there is no significant interaction between SES and games on

Healthy Personality of sports students.


Depression proneness of sports students.

Table 34

Mean scores of Depression Proneness for sports students playing different games having different SES

Games (Groups)

Ball Racket Human

Powered/ Free hand


Overall SES


141

Table 35 ANOVA table for Mean scores of Depression Proneness for sports students

playing different games having different SES Source of variation Sum of Squares df Mean Square F value P value

Between Games (A) 6.997 3 2.332 0.708 .548

Between SES (B) 10.499 1 10.499 3.186 .075

Interaction (A x B) 11.475 3 3.825 1.161 .325

Error 998.478 303 3.295

Total 14613.000 311



to different SES levels differ significantly in their mean depression proneness


non-significant indicating that pattern of depression proneness was same for


the formulated hypothesis is accepted and there is no significant interaction

between SES and Games on Depression Proneness of sports students.


Addiction proneness of sports students.

Table 36 Mean scores of Addiction proneness for sports students playing different


Ball Racket Human

Powered/ Free hand


Overall SES


142

Table 37 ANOVA table for Mean scores of Addiction Proneness for sports students

playing different games having different SES Source of variation Sum of Squares Df Mean Square F value P value

Between Games (A) 8.392 3 2.797 0.831 .478

Between SES (B) 1.878 1 1.878 0.558 .456

Interaction (A x B) 3.038 3 1.013 0.301 .825

Error 1020.074 303 3.367

Total 8801.000 311




different games did not differ significantly in their mean addiction proneness

scores as well as subjects with different SES levels. The interaction effect


of addiction proneness was same for subjects with different SES levels

irrespective of the game they play. Hence, the formulated hypothesis is

accepted, as there is no significant interaction between SES and Games on

Addiction Proneness of sports students.

A starting revolution of the study is that, there were no interaction

effects in all but one area, that is, there is interaction between socio-economic

status and human powered / free hand games on severe depression. The

possible causes for this kind of phenomena area (i) majority of the subjects

belong to low socio-economic status groups. Severe depression prevalent

among the subjects of this sports category may be due to their low SES than

pursuance of particular sports, (ii) The human powered / free hand games

sports persons do not participate in competitions in special attire or use

attractive gadgets. They have low social esteem, with abysmally low social

recognition and patronage.

Documents

ANALYSIS AND INTERPRETATION OF DATAshodhganga.inflibnet.ac.in/bitstream/10603/15854/14/14_chapter 4.pdf100 Descriptive statistics Descriptive statistics provides summary information