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A Study of “Investors’ Behaviour in Financial Market”

93

Chapter-5

Data Analysis

5.1 Introduction

The data, after collection, has to be processed and analyzed in accordance

with the outline laid down for the purpose at the time of developing the research

plan. This is essential for a scientific study and for ensuring that we have all relevant

data for making contemplated comparison and analysis. The term ‘analysis’ refers to

the computation of certain measures along with searching for patterns of

relationship that exist among data groups. Thus, “in the process of analysis,

relationships or differences, supporting or conflicting with original or new

hypotheses should be subjected to statistical tests of significance to determine with

what validity data have some indication or any conclusions.” (Kothari, C.R. “Research

Methodology”, Wishwa Prakashan pp . 151.) Taking this statement as guiding torch,

the primary data have been analyzed and conclusions are drawn.

A growing economy needs investment to sustain its growth process. Such

investments can be quickly and efficiently undertaken if investors have access to a

well-developed financial market. Historically, banks were played the role of

intermediaries matching savers with investors. However, the modern world of

business requires a much more sophisticated level of intermediation. It is no longer

sufficient to have an efficient means of allocating savers’ funds to investors; one also

needs financial markets to allocate risk and to re-allocate capital from inefficient to

more efficient projects.


94

5.2 Demographic Factor-Wise Profile of Investor’s

The influence of investors’ demographics on their investment preferences

has not been established fairly so far. Accordingly, among others the present study is

conducted with the objective of identifying the association between demographics

of individual investors and their investment behaviour. This chapter presents the

results of the primary survey of investors conducted to achieve the above mention

objective. It examines the null hypothesis that the investment preferences of

individual investors are not dependent on their demographic characteristics such as

age, sex, income, occupation, employment status and family size. To begin with we

shall present a brief profile of the sample respondents. The rest of the chapter is talk

about the analysis of the data pertaining to investors preferences across their

demographics.

Gujarati’s are known for their love for bull-bear line or stock market. It is true

that “If others (people from other states) are successful in academics and

professional field, Gujarati’s are successful investors,” Though there is an inherent

risk in stock investment, Gujarati’s do not shy away from the capital market. A

working paper by a faculty of IIMA says one out of every four Gujarati’s invests in

stocks. This is about seven times higher than rest of the country’s average!

The research was an attempt to know the investment pattern of investors in

financial markets in Saurashtra region of Gujarat.

Objective 1

To draw a profile of individual investors to describe their demographic, economic,

financial and equity ownership characteristics.

According to objective 1 of the study detailed analysis is mentioned as follows:


95

Socio-Economic Status of the investors

Table 5.1 Sex, Age, Marital Status, Type of Family, Size of Family and

Number of Earning members in Family

Sl. No. Status Number of

Respondents

Percentage to

Total

Sex

1. Male 212 76.00 2. Female 68 24.00 Total 280 100.00

Age

1 Below 20 Years 07 02.50

2 20-25 Years 132 47.14

3 26-35Years 98 35.00

4 36-45 Years 28 10.00

5 46-55 Years 12 04.28

6 56-60 Years 01 00.36

7 Above 60 Years 02 00.72

Total 280 100.00

Marital Status

1 Single 161 57.50

2 Married 114 40.71

3 Divorcee 03 01.07

4 Widow 02 00.72

Total 280 100.00

Type of Family

1 Joint Family 120 42.85

2 Nuclear Family 142 50.71

3 Hindu Undivided Family (H.U.F.) 03 01.09

4 Single Parent Family 15 05.35

Total 280 100.00

Size of Family

1 1-5 members 201 71.78

2 6-10 members 70 25.00

3 11-20 members 09 03.22

Total 280 100.00

Number of Earning members

1 1 member 89 31.78

2 2 members 150 53.57

3 3 members 26 09.28

4 4 members 12 04.28

5 5 or more members 03 01.09

Total 280 100.00


96

Table 5.1 exhibits the socio-economic status of the investors. It is clear from Table

5.1 that out of 280 investors, 76% were male and the remaining 24% investors were

female. From this result one thing is to be noted that in a present scenario female

are investing in financial markets. From figure 5.1 it can be easily seen that most of

the investors are between age 20-25 years and 26-35 years.

3%

47%

35%

10%4% 0%1%

Below 20 Years 20-25 Years 26-35Years

36-45 Years 46-55 Years 56-60 Years

Above 60 Years

Fig. 5.1 Age-wise investors profile

Out of 280 investors 57.5% are single, while 40.71% are married. There are

only 3 investors who are divorced, while 2 investors are widow. Types of family play

very important in investing in financial market. Figure 5.2 represents the investor’s

family profile.

43%

51%

1%5%

Joint Nuclear H.U.F. Single Parent

Fig. 5.2 Family profile of investors


97

In India size of family and number of earners plays a very crucial role in

Economic saving pattern, because if size of family is large and number of earners are

less then investors invest less and he invest mostly in safe assets. In our study,

71.78% investors have family members in between 1 to 5, while there are 25%

investors who family size is in between 6 to 10, very few investors are there who’s

size of family is 11-20 members. Fig 5.3 represents the profile of number of earning

member in a family. Fig 5.4 represents the occupation of respondents.

31.78

53.57

9.284.28

1.09

1 2 3 4 5

number of earning members

Fig. 5.3 Profile of earning members per Family

5%12%

57%

7%

17%

1%1%

19%

Agriculture

Govt. Service

Private Service

Self employed

(Professional)

Own business

House wife

Fig 5.4 Occupation of respondents


98

Table 5.2 Occupations, Profession, Place of Residence and Educational

Qualification

Sl. No. Status Number of

Respondents

Percentage to

Total

Occupation

1 Agriculture 14 05.00

2 Govt. Service 34 12.14

3 Private Service 159 56.78

4 Self employed (Professional) 21 07.50

5 Own business 47 16.77

6 House wife 02 00.72

7 Retired 03 01.09

Total 280 100.00

Profession

1 Architect/Engineer 01 00.36

2 Banker 33 11.78

3 Businessman 42 15.00

4 C. A. 02 00.72

5 Consultant 13 04.64

6 Executive 49 17.50

7 Lawyer 13 04.64

8 Educator 70 25.00

9 Others 57 20.36

Total 280 100.00

Place of Residence

1 Rural 30 10.71

2 Semi Urban(Town) 115 41.07

3 Urban 135 48.22

Total 280 100.00

Educational Qualification

1 Up to S.S.C. 09 03.21

2 Up to H.S.C. 28 10.00

3 Graduation 83 29.64

4 Post Graduate 105 37.50

5 Professional 55 19.65

Total 280 100.00


99

Rural

11%

Semi

Urban(Tow

n)

41%

Urban

48%

Fig. 5.5 Residence Area of respondent investors

Fig 5.5 shows that most of the respondent investors are from urban and Semi-Urban

areas. Education Qualification is also one of the most influencing factors in financial

market. The Educational Qualification of respondents is shown in figure 5.6. Chart

shows that most of the respondents are highly educated.

3.21

10

29.64

37.5

19.65

Fig. 5.6 Educational Qualification of investors


100

Table 5.3 Annual incomes of respondents

Sl. No. Annual Income Number of

Respondents

Percentage to

Total

1 Up to 1,00,000 37 13.21

2 1,00,000-3,00,000 147 52.50

3 3,00,000-5,00,000 74 26.44

4 5,00,000-7,00,000 21 07.50

5 7,00,000-10,00,000 01 00.35

Total 280 100.00

0 20 40 60

Up to 1 lac

1-3 lacs

3-5 lacs

5-7 lacs

7-10 lacs

13.21

52.5

26.44

7.5

0.35

Fig 5.7 Annual Incomes of Respondents

Table 5.4 Annual Saving of the Respondents

Sl. No. Annual Saving Number of

Respondents

Percentage to

Total

1 Below 10,000 27 09.64

2 10,000-20,000 67 23.93

3 20,000-50,000 78 27.86

4 50,000-1,00,000 65 23.21

5 1,00,000-2,00,000 35 12.50

6 More than 2,00,000 08 02.86

Total 280 100.00


101

In order to study the relationship between Age and Saving Chi-Square Test has been

used.

H0: There is no association between Age and Saving of Respondents

H1: There is significant association between Age and Saving of Respondents

Chi-Square Tests

Value df

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 168.696 12 .000

Likelihood Ratio 157.792 12 .000

N of Valid Cases 280

The value of 696.1682=χ with p<0.001, which predicts significant relationship

between Age and Saving. Since Cramer’s statistic is 0.448, which shows medium

association between age and saving of respondent. This value is highly significant

(p<0.001) indicating that a value of the test statistic that is this big is unlikely to have

happened by chance, therefore the strength of the relationship is significant.

Symmetric Measures

Value

Approx.

Sig.

Phi .776 .000

Cramer's V .448 .000

Nominal by

Nominal

Contingency

Coefficient .613 .000



102

0102030405060

Be

low

Rs.

10

10

.-2

0

20

-50

50

-10

0

10

0-2

00

Mo

re t

ha

n 2

00

Saving (in thousand)

Up to 1 lac

1-3 lacs

3-5 lacs

5-7 lacs

7-10 lacs

Fig 5.8 Income and Saving of Respondents

Figure 5.8 represents income and saving pattern of respondent investors. In order to

study the relationship between the income and savings of the respondents, the Chi-

Square Test has been applied.

H0: There is no association between Income and Saving of Respondents

H1: There is significant association between Income and Saving of Respondents

Chi-Square Tests

Value df

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 999.039 45 .000

Likelihood Ratio 628.042 45 .000


\

The value of chi-square statistic is 999.039. This value is highly significant (p<0.001),

indicating a significant relationship between income and saving of respondents.


103

Symmetric Measures

Value

Approx.

Sig.

Nominal by

Nominal

Phi 1.889 .000

Cramer's V .845 .000

Contingency

Coefficient .884 .000


For these data, Cramer’s statistic is 0.845 out of a possible maximum value of 1. This

represents a strong association between the income and saving of respondent. Also,

this value is highly significant (p<0.001) indicating the strength of the relationship is

significant.

Objective 2

To analyze the reasons for investing or not investing in different instruments.

To analyze the objective, researcher has mentioned the following details.

Table 5.5 Choice of various investment instruments of respondent investors

Sl. No. Type of Saving Instrument Number of

Respondents

Percentage to

Total

1 In cash 60 21.43

2 In Bank Saving A/c 116 41.43

3 Post Office Monthly Scheme 80 28.57

4 Mutual Funds 75 26.79

5 Fixed Deposits 46 16.43

6 Recurring Deposits 39 13.93

7 Insurance 111 39.64

8 P.P.F. 94 33.57

9 Equity Markets 29 10.36

10 Other’s 15 5.36


104

60

116

80

75

46

39

111

94

29

15

21.43

41.43

28.57

26.79

16.43

13.93

39.64

33.57

10.36

5.36

In cash

In Bank Saving A/c

Post Office Monthly Scheme

Mutual Funds

Fixed Deposits

Recurring Deposits

Insurance

P.P.F.

Equity Markets

Other’s

Percentage to Total Number of Respondents

Fig. 5.9 Choice of investment tool by respondent investor’s.

As shown in the Figure 5.9 the highest choice of investment tool is for bank saving

account 41.43 % with Insurance at second place, P.P.F. at third place. Investment in

Mutual Fund is higher than that of Equity Markets which shows that investors in

saurashtra are investing in risky assets with calculative risk. The percentage of

investor investing in Post Office Monthly Scheme is also higher than those investing

in Recurring Deposits and Fixed Deposits.

Table 5.6 Ranking of reasons for savings of Respondents

Rank Sl.

No.

Reasons for Savings

1 2 3 4 5 6 7

1 Emergency 81 37 33 14 34 14 25

2 For living expenses and bills 28 54 54 36 31 18 16

3 Education 58 41 50 31 35 20 08

4 Child’s marriage 15 19 18 46 22 53 55

5 Purchase of land/house 20 20 17 46 34 43 57

6 Retirement 18 32 28 27 40 53 33

7 Medical expenses 19 39 47 34 34 26 35


105

Table 5.7 Belief of Respondent for reasons of savings.

Sl.

No.

Reasons for Savings Strongly Believe

Total of rank

1,2 & 3

Moderate

Believe Total

of rank 4,5,6

& 7

1 Emergency 151 87

2 For living expenses and bills 136 101

3 Education 149 94

4 Child’s marriage 52 176

5 Purchase of land/house 57 180

6 Retirement 78 153

7 Medical expenses 105 129

Table 5.7 represents the rank of choice of reasons for saving of respondents. To get

clearer picture of investor’s belief for particular reason we construct Table 5.8. Here

we consider Rank 1,2 & 3 as Strong belief, while Rank 4,5,6 & 7 represents the

moderate belief of respondent for the reasons of saving.

Emergency

21%

For living

expenses and

bills

19%

Education

20%

Child’s marriage

7%

Purchase

of

land/house

8%

Retirement

11%

Medical

expenses

14%

Strongly Believe

Fig. 5.10 Percentage of Strong belief of Respondents for reasons of

Savings


106

Emergency

For living expenses and bills

Education

Child’s marriage

Purchase of land/house

Retirement

Medical expenses

0

151

136

149

52

57

78

105

87

101

94

176

180

153

129

Modrately Believe 4,5,6 & 7 Strongly Believe

Fig. 5.11 Comparison between Strong and Moderate belief of respondents

for different saving reasons.

In financial market decision maker plays a very crucial role. In India in past

most of the decision are taken by Father/Husband, but in present scenario

Mother/Wife role is also very important in the changing sociological pattern. Looking

at Table 5.8, it can be easily seen that 47.86% decision are taken jointly, which make

one interest in study regarding investment pattern, while 30.71% decisions are taken

by Father/Husband. To get more clarity regarding decision pattern, we also plot the

figure of Table 5.8.

Table 5.8 Investment Decision Maker

Sl.

No.

Decision Maker Number of

Respondents

Percentage

to Total

1 Father/Husband 86 30.71

2 Mother/Wife 12 4.29

3 Joint 134 47.86

4 Financial Consultant 15 5.36

5 Friends/Relatives 33 11.79

Total 280 100.00


107

Father/Husband

31%

Mother/Wife

4%

Joint

48%

Financial

Consultant

5%

Friends/Relatives

12%

Other

12%

Number of Respondents

Fig 5.12 Investment Decision Maker of the Family

Objective 3

To study the role of financial advisors in taking decisions by individual

investors.

After liberalization, the investment in stock market shows increasing trend.

Retail investors now tempted to invest there investable amount in the share and

stocks of the company. In the development of economy the participation of retail

investor plays a vital role in the growth rate of economy. In our study 36% of the

respondents are investing in equity market. This is much more than the national

average because the region under study is known to be Hub for primary and

secondary equity market. One of the districts under study i.e. Rajkot is having their

Own Stock Exchange and probably this is the reason that investors are more inclined

to invest in stock market. One of the reasons for higher investment in stock market

may be due to temptation of higher and instant return. In Saurashtra especially

people of Rajkot and Bhavnagar are more speculative as compare to the other part

of the region, and no. of responses obtained in the survey from these districts are

more, this may be the reason of getting more percentage of respondent investing in

stocks than the national average.


108

yes

36%

no

64%

Fig 5.13 Percentage of Equity market investors

51%

9%

23%

17%

On my own On tips

Advice from broker Tv/Newspaper

Fig 5.14 Percentage of Investor’s using different method of

investing in the stock market.

About 50% of the respondents are investing in stock market on his own, 24%

of the investors are taking advice from financial brokers. Only 8% of the investors are

relying upon tip and rumors from different sources.

Table 5.9 Reasons shown by the respondent for not investing in stocks

Reasons for not investing in Stock

No. of

respondents

Stock Market are Gambling dens 46

I have lost money in past 5

Lack of knowledge 73

Other reasons 12


109

Stock

Market are

Gambling

dens

34%

I have lost

money in

past

3%

Lack of

knowledge

54%

Other

reasons

9%

Fig 5.15 Percentage of the respondent for not investing in stocks

Objective – 4

To analyze the behaviour of individual investors who are investing in the financial

market directly or indirectly through Mutual Funds or Equity linked Schemes.

Age, Income, Education, Place of residency and Type of family have effect on

investment decisions, considering this researcher has framed various hypothesis to

assess the relationship between various factors and investment in stocks. The

researcher has classified category of financial investment in Stock, to test the

association Chi-square test has been applied. The details are follows in Annexure

A.1. In Annexure A.1, researcher has tested Age of the investors and Investment

behaviour in Risky Asset like Stocks.

Hypothesis –A.1.1

H0: There is no significant association between Age of the Investors and Investment


H1: There is a significant association between Age of the Investors and Investment



110

Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 1.483 .830

The value of chi-square statistic is 1.483 with significance value 0.830, indicating no

significant association between Age and Investment in stocks of the investors.

7

13298

28 153

47 399 4

Below 20 20-25 26-35 36-45 Above 46

Age of respondents

Investors Investing

Fig 5.16 Association between Age of the Investors and Investment

behaviour in Risky Asset like Stocks

Figure 5.16 represents Association between Age of the Investors and Investment


Hypothesis –A.1.2

H0: There is no significant association between Age of the Investors and Time of

holding stocks in Risky Asset like Stocks.

H1: There is a significant association between Age of the Investors and Time of

holding stocks in Risky Asset like Stocks.

Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 15.448 0.004

The value of chi-square statistic is 15.448 with significance value 0.004, indicating

significant association between Age of investor and Time of holding stocks.


111

Hypothesis –A.1.3


Mechanism in Risky Asset like Stocks.



Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 10.005 0.019


significant association between Age and Investment Mechanism in stocks of the

investors.

Hypothesis –A.1.4

H0: There is no significant association between Age of the Investors and number of

companies they are holding.

H1: There is significant association between Age of the Investors and number of

companies they are holding.

Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 5.305 0.257


significant association between Age of investor and number of companies they hold.


112

Hypothesis –A.1.5

H0: There is no significant association between Age of the Investors and not

investing in Stock Market.

H1: There is significant association between Age of the Investors and not investing

in Stock Market.

Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 1.249 0.741


significant association between Age of investor and not investing in Stock Market.

The result of hypothesis A.1.1 and A.1.5 reveals that the effect of age does

not found on investment practices in stock market.

In Annexure A.2, researcher has tested Type of Family of the investors and

Investment behaviour in Risky Asset like Stocks.

Hypothesis –A.2.1

H0: There is no significant association between Type of Family of the Investors and


H1: There is a significant association between Type of Family of the Investors and


Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 16.981 0.0000


113


significant association between Type of Family and Investment in stocks of the

investors.

Hypothesis –A.2.2


Time of holding stocks in Risky Asset like Stocks.


Time of holding stocks in Risky Asset like Stocks.

Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 6.216 0.184


significant association between Type of Family and Time of holding stocks by the

investors.

Hypothesis –A.2.3


Investment Mechanism in Risky Asset like Stocks.



Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 1.161 0.762


114


significant association between Type of Family of investor and Investing Mechanism

in Risky Asset like Stocks.

Hypothesis –A.2.4


number of companies they are holding.

H1: There is significant association between Type of Family of the Investors and


Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 2.870 0.580


significant association between Type of Family of investor and number of companies

they hold.

Hypothesis –A.2.5


not investing in Stock Market.

H1: There is significant association between Type of Family of the Investors and not


Since most of the observations have zero value, chi-square test fails. Here we

represent graph to find association between type of family and not investing in Stock

Market.


115

02468

10

Nuclear

Joint

Fig 5.17 Association of the respondent’s type of family and Reasons for not

investing in stocks.

In Annexure A.3, researcher has tested Occupation of the investors and Investment


Hypothesis –A.3.1

H0: There is no significant association between Occupation of the Investors and


H1: There is a significant association between Occupation of the Investors and


Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 5.379 0.251


significant association between Occupation and Investment in stocks of the

investors.


116

Hypothesis –A.3.2


Time of holding stock in Risky Asset like Stocks.

H1: There is a significant association between Occupation of the Investors and Time

of holding stock in Risky Asset like Stocks.

Hypothesis –A.3.3





Hypothesis –A.3.4



H1: There is significant association between Occupation of the Investors and


Hypothesis –A.3.5

H0: There is no significant association between Occupation of the Investors and not


H1: There is significant association between Occupation of the Investors and not


In all the cases mentioned above, as per the annexure A.3, more than 20% of

the cells having frequency less than 5, while applying Chi-Square test, therefore Chi-

Square Test Fails here.


117

In Annexure A.4, researcher has tested Place of Residency of the investors and


Hypothesis –A.4.1

H0: There is no significant association between Place of Residence of the Investors

and Investment behaviour in Risky Asset like Stocks.

H1: There is a significant association between Place of Residence of the Investors


Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 0.828 0.661


significant association between Place of Residence and Investment in stocks of the

investors.

Hypothesis –A.4.2


and Time of holding stock in Risky Asset like Stocks.


and Time of holding stock in Risky Asset like Stocks.

Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 15.515 0.004


118


significant association between Place of Residence and Time of holding stock by the

investors.

While applying Chi-Square for Hypothesis –A.4.2, the data regarding Rural

respondents was statistically inappropriate, therefore researcher has not considered

that data in construction of test.

Hypothesis –A.4.3


and Investment Mechanism in Risky Asset like Stocks.


and Investment Mechanism in Risky Asset like Stocks.

Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 5.768 0.450


significant association between Place of Residence of investor and Investment


Hypothesis –A.4.4


and number of companies they are holding.

H1: There is significant association between Place of Residence of the Investors

and number of companies they are holding.


119

Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 6.461 0.167


significant association between Place of Residence of investor and number of

companies they hold.

While applying Chi-Square for Hypothesis –A.4.4, the data regarding Rural

respondents was statistically inappropriate, therefore researcher has not considered

that data in construction of test.

Hypothesis –A.4.5


and not investing in Stock Market.

H1: There is significant association between Place of Residence of the Investors and

not investing in Stock Market.

Since most of the observations have zero value, chi-square test fails.

In Annexure A.5, researcher has tested Educational Qualification of the investors


Hypothesis –A.5.1

H0: There is no significant association between Educational Qualification of the

Investors and Investment behaviour in Risky Asset like Stocks.

H1: There is a significant association between Educational Qualification of the

Investors and Investment behaviour in Risky Asset like Stocks.


120

Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 0.653 0.884


significant association between Educational Qualification and Investment in stocks of

the investors.

Hypothesis –A.5.2


Investors and Time of holding stock in Risky Asset like Stocks.


Investors and Time of holding stock in Risky Asset like Stocks.

Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 32.340 0.0000


significant association between Place of Residence and Time of holding stock by the

investors.

Hypothesis –A.5.3


Investors and Investment Mechanism in Risky Asset like Stocks.


Investors and Investment Mechanism in Risky Asset like Stocks.


121

Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 15.164 0.019


significant association between Educational Qualification of investor and Investment


Hypothesis –A.5.4


Investors and number of companies they are holding.

H1: There is significant association between Educational Qualification of the

Investors and number of companies they are holding.

Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 38.249 0.000


significant association between Educational Qualification of investor and number of

companies they hold.

Hypothesis –A.5.5


Investors and not investing in Stock Market.




122

Few responses have been received for association between Educational

Qualification of the Investors and not investing in Stock Market, therefore chi-square

test has not been calculated.

In Annexure A.5, majority of the hypothesis are rejected, one can say that

Educational Qualification has significant effect on investing in Stock Market.

In Annexure A.6, researcher has tested Annual Income of the investors and


Hypothesis –A.6.1

H0: There is no significant association between Annual Income of the Investors and


H1: There is a significant association between Annual Income of the Investors and


Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 8.325 0.004


significant association between Annual Income and Investment in stocks of the

investors.

Hypothesis –A.6.2






123

Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 36.316 0.0000


significant association between Annual Income and Time of holding stock by the

investors.

Hypothesis –A.6.3





Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 6.724 0.081


significant association at 10% level of significance between Annual Income of

investor and Investment Mechanism in Risky Asset like Stocks.

Hypothesis –A.6.4



H1: There is significant association between Annual Income of the Investors and



124

Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 19.925 0.000


significant association between Annual Income of investor and number of companies

they hold.

Hypothesis –A.6.5





Few responses have been received for association between Annual Income of

the Investors and not investing in Stock Market, therefore chi-square test has not

been calculated.

In Annexure A.6, all the hypotheses are rejected; one can say that Annual

Income has significant effect on investing in Stock Market because as general income

level, the risk appetite capacity of an individual increases, it shows the causal link

between income level and investment in Risky Assets.

Post liberalization period shows the change in the investment pattern of the

retail investor, the investment in mutual fund indicates increasing trend. Retail

investors now tempted to invest their savings in the mutual funds of the non-

banking financial companies. Now a day, mutual Fund is one of the popular financial

tool in the market. In the development of economy the participation of retail

investor plays a vital role in the growth rate of economy. Figure 5.18 indicates that

41% of the respondents are investing in Mutual Fund.


125

yes

41%

no

59%

Fig 5.18 Investment in Mutual Fund

In Table 5.10, researcher has provided percentages of different investment

mechanism in Mutual Fund. From the Figure 5.19, one can easily see that majority of

the respondents are investing in Growth Funds and Tax-Saving Funds, therefore it

can be said that investors are investing for the purpose of higher income as well as

Tax-Saving.

Table 5.10 Investment mechanism in Mutual Fund

Sl.

No.

Tenure Number of

Respondents

Percentage

to Total

1 Half yearly 03 2.22

2 Yearly 30 22.22

3 Lump sum 33 24.44

4 Systematic Investment

Plan

69 51.11

15%

23%

11%19%

24%

8%

Income funds

Growth funds

Balance funds

Diversified

Tax-saving schemes

Fig. 5.19 Investment in different mutual fund schemes


126

Investment in Insurance policy is also increased as it serves two purposes; one is

comparatively good rate of return and safety of the investment as well as it covers

the life risks of the investor. Out of 280 respondents 82% are investing in Insurance

Policies, most of the investors are having their insurance policies for last more than 5

years.

yes

82%

no

18%

Fig 5.20 Investment in Life Insurance Policies

Table 5.11 Life Insurance Term of Holding

Sl.

No.

Tenure Number of

Respondents

Percentage

to Total

1 Last One year 59 25.65

2 Last Five years 81 35.22

3 Last Ten years 30 13.04

4 Last fifteen years 60 26.09

Total 230 100.00

From Figure 5.21, it can be easily seen that most of the investors are investing in Life

Insurance and Mediclaim policies. An increase in investment in Mediclaim shows

that people become more aware about their health expenses.


127

83

194

3712

36

Fig 5.21 Investment in different Insurance Policies

In Annexure B.1, researcher has tested Age of the investors and Investment

behaviour in Fairly Safe Assets like Mutual Funds and Insurance Policies.

Hypothesis –B.1.1


behaviour of investors in Fairly Safe Asset like Mutual Funds.

H1: There is significant association between Age of the Investors and Investment


Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 11.73 0.018


significant association between Age of the investors and Investment behaviour of

investors in Fairly Safe Asset like Mutual Funds.


128

Hypothesis –B.1.2

H0: There is no significant association between Age of the Investors and Different

MF Schemes.

H1: There is significant association between Age of the Investors and Different MF

Schemes.

Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 17.96 0.117


significant association between Age of investor and different MF Schemes, which

shows that each age group investors are investing in each kind of MF Schemes.

Hypothesis –B.1.3


Mechanism in Mutual Funds.


Mechanism in Mutual Funds.

Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 24.034 0.001


significant association between Age and Investment Mechanism in Mutual Funds of

the investors. Here the result of the test shows that Age and Investment Mechanism

does have strong association, i.e. Age of the investor plays an important role in

Investment Mechanism.


129

Hypothesis –B.1.4


behaviour of investors in Fairly Safe Asset like Insurance Policies.

H1: There is significant association between Age of the Investors and Investment

behaviour of investors in Fairly Safe Asset like Insurance Policies.

Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 0.162 0.997


significant association between Age of the investors and Investment behaviour of

investors in Fairly Safe Asset like Insurance Policies.

Hypothesis –B.1.5


holding in Insurance Policies.

H1: There is significant association between Age of the Investors and Time of


Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 13.395 0.037


significant association at 5% level of significance between Age of investor and Time


130

of holding in Insurance Policies. Here the result indicates that as the investor become

older, the time of holding of Insurance Policies is higher.

Hypothesis –B.1.6

H0: There is no significant association between Age of the Investors and different

Insurance Policies.

H1: There is a significant association between Age of the Investors and different

Insurance Policies.

Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 31.793 0.000


significant association between Age and different Insurance Policies. The result of

Chi-Square test, here clearly indicates that there is a strong association between

different age group and choice of Insurance Policies.


131

MediclaimLife

InsuranceTerm Plans

Endowme

nt policies

Unit-Link

Insurance

Plan

LIC Plans

Below 20 4 6 0 0 0

20-25 30 92 13 5 7

26-35 27 63 17 3 27

36-45 14 22 5 2 2

Above 46 8 11 2 2 0

0

10

20

30

40

50

60

70

80

90

100

inv

est

ors

Fig 5.22 Association between Age and Choice of Insurance Plans

In Annexure B.2, researcher has tested Type of Family of the investors and

Investment behaviour in Fairly Safe Assets like Mutual Funds and Insurance Policies.

Hypothesis –B.2.1

H0: There is no significant association between Type of Family and Investment


H1: There is significant association between Type of Family and Investment


Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 1.306 0.520


significant association between Type of Family of the investors and Investment


132

behaviour of investors in Fairly Safe Asset like Mutual Funds. Therefore we can say

that the type of family and investment in mutual fund does not have any significant

association.

Hypothesis –B.2.2


Different MF Schemes.



Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 1.622 0.106


significant association between Type of Family of investor and different MF Schemes.

Hypothesis –B.2.3


Investment Mechanism in Mutual Funds.



Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 5.603 0.133


133


significant association between Type of Family and Investment Mechanism in Mutual

Funds of the investors.

Hypothesis –B.2.4


Investment behaviour of investors in Fairly Safe Asset like Insurance Policies.



Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 9.474 0.009


significant association between Type of Family of the investors and Investment

behaviour of investors in Fairly Safe Asset like Life Insurance Policies.

Hypothesis –B.2.5


Time of holding in Insurance Policies.



Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 23.195 0.000


134


significant association between Type of Family of investor and Time of holding in

Insurance Policies.

Hypothesis –B.2.6


different Insurance Plans.



Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 47.762 0.000


significant association between Type of Family and different Insurance Plans. The

result of Chi-Square test, here clearly indicates that there is a strong discrimination

between different Type of Family group and choice of Insurance Plans.

In Annexure B.3, researcher has tested Occupation of the investors and

Investment behaviour in Fairly Safe Assets like Mutual Funds and Insurance Policies.

Hypothesis –B.3.1


Investment behaviour of investors in Fairly Safe Asset like Mutual Funds.




135

Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 15.423 0.009


significant association between Occupation of the investors and Investment

behaviour of investors in Fairly Safe Asset like Mutual Funds. Here the result shows

that the occupation of Investors does have effect on their decision in MF Investment.

Hypothesis –B.3.2





Since Most of cells in Annexure B.3.2 has zero values, Chi-Square Fails.

Hypothesis –B.3.3





Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 27.112 0.0000


136


significant association between Occupation and Investment Mechanism in Mutual

Funds of the investors. Due to Small values in Agriculture row and once in six month

column in Annexure B.3.3, these two are omitted while performing Chi-Square Test.

Hypothesis –B.3.4





Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 9.523 0.049


significant association between Occupation of the investors and Investment


Hypothesis –B.3.5


holding in Life Insurance Policies.

H1: There is significant association between Age of the Investors and Time of

holding in Life Insurance Policies.

Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 24.806 0.000


137


significant association between Occupation of investor and Time of holding in

Insurance Policies.

Hypothesis –B.3.6





Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 12.630 0.125


significant association between occupation and different Insurance Plans. The result

of Chi-Square test, here clearly indicates that there is no discrimination between

different Occupation and choice of Insurance Plans, i.e. different kind of occupant

have different kind of policies.

In Annexure B.4, researcher has tested Place of Residence of the investors

and Investment behaviour in Fairly Safe Assets like Mutual Funds and Insurance

Policies.

Hypothesis –B.4.1

H0: There is no significant association between Place of Residence and Investment


H1: There is significant association between Place of Residence and Investment



138

Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 3.909 0.142


significant association between Place of Residence of the investors and Investment


Hypothesis –B.4.2


and Different MF Schemes.



Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 7.645 0.265


significant association between Place of Residence of investor and different MF

Schemes, which shows that the place of residence of investors does not affect the

investor’s behaviour on different MF Schemes.

Hypothesis –B.4.3


and Investment Mechanism in Mutual Funds.


and Investment Mechanism in Mutual Funds.


139

Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 9.303 0.054


significant association at 10% level of significance between Place of Residence and

Investment Mechanism in Mutual Funds of the investors.

Hypothesis –B.4.4


and Investment behaviour of investors in Fairly Safe Asset like Insurance Policies.



Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 8.517 0.014


significant association at 5% level of significance between Place of Residence of the

investors and Investment behaviour of investors in Fairly Safe Asset like Insurance

Policies.

Hypothesis –B.4.5


and Time of holding in Insurance Policies.




140

Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 8.973 0.175


significant association between Place of Residence of investor and Time of holding in

Insurance Policies.

Hypothesis –B.4.6


and different Insurance Plans.


and different Insurance Plans.

Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 10.002 0.265


significant association between Type of Family and different Insurance Plans. The

result of Chi-Square test, here clearly indicates that there is no discrimination

between different Place of Residence and choice of Insurance Plans.

In Annexure B.5, researcher has tested Education of the investors and

Investment behaviour in Fairly Safe Assets like Mutual Funds and Life Insurance

Policies.


141

Hypothesis –B.5.1

H0: There is no significant association between Education and Investment


H1: There is significant association between Education and Investment behaviour

of investors in Fairly Safe Asset like Mutual Funds.

Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 2.905 0.234


significant association between Education of the investors and Investment behaviour

of investors in Fairly Safe Asset like Mutual Funds.

Hypothesis –B.5.2

H0: There is no significant association between Education of the Investors and


H1: There is significant association between Education of the Investors and


Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 6.253 0.619


significant association between Education of investor and different MF Schemes,

which shows that Education level of investor and choice of MF schemes does not

have any association.


142

Hypothesis –B.5.3



H1: There is a significant association between Education of the Investors and


Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 8.253 0.220


significant association between Education and Investment Mechanism in Mutual

Funds of the investors.

Hypothesis –B.5.4



H1: There is significant association between Education of the Investors and


Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 5.826 0.212


significant association between Education of the investors and Investment behaviour

of investors in Fairly Safe Asset like Insurance Policies.


143

Hypothesis –B.5.5

H0: There is no significant association between Education of the Investors and Time

of holding in Insurance Policies.

H1: There is significant association between Education of the Investors and Time of


Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 14.212 0.027


significant association between Education of investor and Time of holding in

Insurance Policies. It can be said that as investor’s educations is higher the decision

of holding the insurance policies is longer.

Hypothesis –B.5.6



H1: There is a significant association between Education of the Investors and


Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 17.978 0.021


significant association between Education and different Insurance Plans. The result


144

of Chi-Square test, here clearly indicates that there is a strong discrimination

between different Educational group and choice of Insurance Plans.

In Annexure B.6, researcher has tested Annual Income of the investors and

Investment behaviour in Fairly Safe Assets like Mutual Funds and Life Insurance

Policies.

Hypothesis –B.6.1





Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 10.82 0.001


significant association between Annual Income of the investors and Investment

behaviour of investors in Fairly Safe Asset like Mutual Funds. Here the result shows

that the Annual Income of Investors does have effect on their decision in MF

Investment.


145

Hypothesis –B.6.2





Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 30.221 0.000


significant association between Annual Income of investor and different MF

Schemes.

Hypothesis –B.6.3





Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 3.758 0.289


significant association between Annual Income and Investment Mechanism in

Mutual Funds of the investors.


146

Hypothesis –B.6.4





Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 11.11 0.001


significant association between Annual Income of the investors and Investment


Hypothesis –B.6.5


Time of holding in Life Insurance Policies.


Time of holding in Life Insurance Policies.

Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 6.656 0.084


significant association between Occupation of investor and Time of holding in

Insurance Policies at 10% level of significance.


147

Hypothesis –B.6.6





Chi-Square Tests

Value

Asymp. Sig.

(2-sided)

Pearson Chi-

Square 39.830 0.000


significant association between Annual Income and different Insurance Plans. The

result of Chi-Square test, here clearly indicates that there is strong discrimination

between different Annual Income and choice of Insurance Plans, i.e. different kind of

occupant have different kind of policies.

Objective – 5

To study the determinants of the composition of individual portfolio and the

diversification pattern of their portfolio.

Table 5.12 Determinant of the composition of individual portfolio

Rank on Seven Point Scale

Rank Sl.

No.

Factors

1 2 3 4 5 6 7

1 Safety of Principal 63 6 17 3 9 21 136

2 Liquidity 21 67 43 43 17 18 35

3 Income Stability 18 32 32 25 56 27 60

4 Tax advantage 7 30 15 21 47 30 93

5 Risk 30 8 22 26 26 45 70

6 Returns 7 11 18 47 56 40 79

7 Information 22 23 21 31 40 41 71

8 Hedge against inflation 56 30 36 35 26 25 33

Rank 1 = Least Important Factor and Rank 7 = Most Important Factor


148

To analyze the data, here researcher has used One Way ANOVA. The results

are as follows

ANOVA

Source of

Variation SS df MS F P-value F crit

Between

Groups 92.69643 7 13.2423 0.02016 0.999991 2.207436

Within Groups 31527.43 48 656.8214

Total 31620.13 55

The result of ANOVA of determinants of the composition of individual portfolio and

the diversification pattern of their portfolio indicates that there is no significant

difference between various factors of investment. To analyze the data further,

researcher has tried to test the data using Rank.

Table 5.13 Rank Analysis of Determinant of the composition of individual portfolio

Sl.

No.

Factors Rank on Seven Point Scale

1 Safety of Principal 2 6 4 7 5 3 1

2 Liquidity 5 1 2 2 7 6 4

3 Income Stability 7 3 3 6 2 5 1

4 Tax advantage 7 3 6 5 2 3 1

5 Risk 3 7 6 4 4 2 1

6 Returns 7 6 5 3 2 4 1

7 Information 6 5 7 4 3 2 1

8 Hedge against inflation 1 5 2 3 6 7 4

From Table 5.13, it is obvious that Safety of Principal, Income Stability, Tax

Advantage, Risk, Returns and Information are equally important for determining

individual’s portfolio, while Liquidity and Hedge against inflation is comparatively

less important.


149

Objective -6

To analyze, the investment preferences of individual investors for different saving

instruments available in the market, their expectations from the market, the

nature of their grievances and difficulties.

To study objective-6, researcher has framed Table 5.14, which represents

percentage of invested amount in various Investment Options.

Table 5.14 Invested Percentage in various Investment Tool

Sl.

No.

Investment Options Less

than

25%

25-

50%

50-

75%

More

than

75%

1 Cash (Saving bank account,

Bank/Postal deposits) less than 1 yr.

71 20 05 02

2 Bank deposits More than 1 year. 54 37 04 02

3 Postal saving schemes (POMIS, FDs

R.DS)

79 16 01 01

4 NSS, NSC, Kisan Vikas Patra 64 05 00 00

5 PPF 76 12 00 08

6 Mutual Fund 63 34 14 04

7 Infrastructure/RBI Bonds 54 04 01 00

8 Life insurance funds (Annual

Premium)

80 19 13 11

9 Shares 66 07 03 01

10 Corporate bonds 37 00 00 00

11 Gold and Silver 74 06 00 01

12 Residential house, land and other

Assets.

35 13 15 09

To analyze the collected data, researcher has applied Two Way ANOVA. The result of

ANOVA is as follow

ANOVA

Source of

Variation SS df MS F P-value F crit

Rows 1547.4 9 171.9333 2.524032 0.030323 2.250131

Columns 25261.8 3 8420.6 123.6169 6.96E-16 2.960351

Error 1839.2 27 68.11852

Total 28648.4 39


150

The result of ANOVA of the investment preferences of individual investors for

different saving instruments available in the market indicates that there is significant

difference between various investment tools as well as various invested percentage

levels.

To study objective-6 further, researcher has framed Table 5.15, which represents

Expected Percentage of Rate of Return in various Investment Avenues.

Table 5.15 Expected Percentage of Rate of Return in various Investment Avenues

Investment avenues 8% - 12% 13%-16% 17%-20% 21%-25% >25%

Equity shares 35 24 83 18 08

Convertible

debentures

76 32 08 01 00

Non Convertible

debentures

76 10 20 04 00

Fixed deposits 130 49 10 00 00

Corporate deposits 78 29 06 05 04

Mutual Funds 17 104 42 19 03

Following the Fig. 5.24, it can be said that in Expected Rate of Return 8-12% majority

of the investors prefers Fixed Deposit as most important investment avenues, it may

be because of the lesser risk taking capacity of the investor for other investment

avenues. In Expected Rate of Return 13-16%, most of investors prefers Mutual

Funds, while in 17-20%, Equity shares are preferred by most of the investors.

Moreover data indicates that in 21-25% Expected Rate of Return, Mutual Fund and

Equity shares equally preferred by respondents. In >25% Expected Rate of Return,

Equity share as investment avenues most preferred because as risk taking capacity

increases expectation of an investor(respondents) also increases and their

investment behaviour shifts from Fixed deposit to Equity shares, i.e. from clearly safe

avenue to risky avenue of investment.


151

35

76 76

130

78

1724

32

10

49

29

104

83

820

10 6

42

18

1 4 0 519

80 0 0 4 3

Equity shares Convertible

debentures

Non

Convertible

debentures

Fixed

deposits

Corporate

deposits

Mutual

Funds

8% - 12% 13%-16% 17%-20% 21%-25% >25%

Fig. 5.24 Expected Percentage of Rate of Return in various Investment Avenues

Objective – 7

To study the awareness about investors’ protection activities initiated by SEBI and

other Govt. agencies.

72%

28%

yes

no

Fig. 5.25 Investor’s awareness regarding SEBI

And RBI

From figure 5.25, one can easily say that 72% investors are aware of Market

regulatory body like Security Exchange Board of India (SEBI) and Reserve Bank of

India (RBI). Researcher has check for investors investing in Stock Market and aware

of SEBI and RBI guidelines. It has found that majority of the respondents who

investing in stock market are aware of Security Mechanism in investor protection

activity.


152

19%

81%

yes

no

Fig. 5.26 Investor’s awareness regarding SEBI Guidelines

Figure 5.26 reveals the fact that though investor’s are aware of agencies like SEBI

and RBI, but most of them had never been gone through the guidelines given by

Market Regulatory Authority.

Table 5.16 Ranking of probable future investment plan

of respondents

Instrument Rank-1 Rank-2 Rank-3

NSS / KVP 13 8 17

PF 40 66 36

Mutual Fund 51 23 30

Regular Income Funds 9 9 27

Equity link insurance 4 11 4

Traditional Insurance 9 9 17

Tax saving investment 17 28 22

Bank / Post Office 29 44 18

Share Market 14 28 34

Reality Sector 63 30 29


153

13

4051

9 4 9 1729

14

63

8

6623

9 11 9

28

44

28

30

17

36

30

27

417

22

18

34

29

Rank-1 Rank-2 Rank-3

Fig. 5.27 Ranking of probable future investment plan of respondents

As shown in the Table 5.16 and Figure 5.27, the general trend for future investment

avenues shows that maximum number of respondents has given 1st

rank to reality

sector for investment. As during the survey period reality sector was booming

therefore the data reveals the contemporary trend of investment. Observing the

overall data majority of the respondents has preferred Public Provident Fund, Reality

Sector, Mutual Fund and bank/post deposits sequentially preferred by the

respondent as future investment avenue.

To study the investment behaviour of an individual investor, researcher has framed

7-point Likert’s Scale which included 15 statements regarding investment decisions.

To test the reliability of scale, KMO and Bartlett's Test and Cronbach’s Alpha

Reliability Test has applied. Result of these test are as follows:


154

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of

Sampling Adequacy. .640

Approx. Chi-Square 838.124

df 105

Bartlett's Test of

Sphericity

Sig. .000

Reliability Statistics

Cronbach's

Alpha

Cronbach's

Alpha Based on

Standardized

Items N of Items

.663 .667 15

From the above tables, it can be said that Kaiser-Meyer-Olkin Measure of Sampling

Adequacy found 0.640, it indicates that the sample is adequate for Factor analysis.

The value of Bartlett’s Test of Sphericity is 838.124 with significance value 0.000,

while Cronbach’s Alpha value is 0.663 which give support to Reliability of

Questionnaire. Researcher has also done ANOVA with Cochran's Test.

ANOVA with Cochran's Test

Sum of

Squares df

Mean

Square

Cochran's

Q Sig

Between People 2777.065 279 9.954

Within

People

Between

Items 1648.342 14 117.739 438.559 .000

Residual 13085.125 3906 3.350

Total 14733.467 3920 3.759

Total 17510.531 4199 4.170

The value Cochran’s Q is 438.559 with significance value 0.000, which is significant

indicating that the questionnaire is reliable to do further analysis. Therefore it can be

concluded that the scale of the study found reliable.

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