Chi Square
Content
CHI-SQUARE QUESTIONNAIRE: What is your family income? 1. Upto 20000 2. 20001-30000 3.30001-40000 4.40001-50000 5.50001 and above What is your total savings? 1. Upto 5000 2. 5001-10000 3.10001-15000 4.15001-20000 5.20001 and above
5.5.1.8.3. Family income and Total Savings Family income includes salary of the respondents, salary of spouse & children and income from all other sources. The family saving otherwise called as total savings includes discretionary savings and contractual saving. To understand the relationship between income and saving, the correlation analysis is done. TABLE 5.5.26 RELATIONSHIP BETWEEN FAMILY INCOME AND TOTAL SAVINGS S. No Particulars 1 Average Total Savings Rs.8238 2 Average Family Income Rs.30706.12 3 % of Total Savings in 28.1 Family Income 4 Ch-Square Value 128.683 5 Sig. Value 0.000 6 R (Correlation) value 0.438 7 Sig. Value 0.000 8 F Value 34.834 9 Sig. Value 0.000 10 Duncan subsets 4 sub sets The ‘r’ value for the relationship is 0.438 and its significant value is 0.000. This shows that there is a positive relationship between family income and family savings and that relationship is significant at 1 percent significant level.
Family Income Up to 20000 20001-30000 30001-40000 40001-50000 50001 and above Total
TABLE 5.5.27 TOTAL SAVINGS AND FAMILY INCOME Total Saving Up to 50011000115001Above 5000 10000 15000 20000 2000 67(34%)* 42(23%) 13(11%) 2(5%) 89(45%)* 80(43%)* 42(38%) 6(15%) 2 25(13%) 32(17%) 26(24%)* 15(37%)* 5 8(4%) 21(11%) 10(9%) 11(27%)* 4 7(4%) 196 9(5%) 184 19(17%)* 110 7 41 10 21
Total 124(22%) 219(40%) 103(17%) 54(10%) 52(9%) 552
The cross tabulation between family income and family saving indicates that families having less than Rs.20000 income account for 22 percent of total population but their population is 34 percent in less than Rs.5000 saving category. The families having income between Rs.20000 and Rs.30000 are saving to the extent of Rs10000. Likewise higher income families are associated with higher saving categories. This shows that there is a clear trend in the association, and the final inference can be that the size of saving increases with the rise in income. The chi-square test indicates that there is a significant association between income and saving. TABLE 5.2.26 CHI-SQUARE TEST VALUE FOR VARIOUS VARIABLES Variable Chi-Square value Sig. Value Significance or not Type of Institution 1.349 0.853 Not Significant Department 54.102 0.141 Not Significant Designation 5.117 0.745 Not Significant Age 3.287 0.511 Not Significant Experience 7.442 0.282 Not Significant Family Size 7.594 0.269 Not Significant Total Income 3.931 0.863 Not Significant Gender 1.673 0.433 Not Significant Source of Information 21.894 0.000 Significant Perception 19.165 0.001 Significant Choice Criteria 38.184 0.000 Significant Awareness Level 9.979 0.041 Significant Risk Category 9.675 0.046 Significant Frequency of Investment 12.808 0.012 Significant Channel of Investment 9.325 0.009 Significant
S. No 1 2 3 1 2 3 4 5 6 7 8 9 10 11 12
To understand the characteristics of these three motive segments, association among the segments with various demographic and investment related variables are analysed. Cross tabulation is used to find out the associations and the chi-square test is applied to test the significance of associations. The chi-square values along with their level of significance are given in the following table. From the chi-square test it is found that age, experience, family size,
gender and income per month have no significant association with motive based segments. The chi-square test table also reveals that there is a significant association between motive segments and source of information, perception of investors, investment behaviour, choice criteria, and awareness level and risk category of investors. This signifies that the demographic variables do not have association with motive segments whereas investment related variables have association. This shows that motive segmentation is mainly based on investment related variables and not on demographic variables.
5.2.1.1.9 Characteristics of Motive Segments
In the previous section, investors have been classified into three categories namely highly motivated, self centered and least motivated on the basis of their saving motives. It has also been noticed that the highly motivated people will save more than the least motivated people. As the motivation level of highly motivated people is high, convincing them to make investment will not require much effort. To sell more with limited effort, the institutions who offer investment products can concentrate on highly motivated segment. To device effective marketing strategy, it is necessary for them to understand the characteristics of this motive segment. If necessary, they can also alter the existing features of their products and service levels to suit the requirements of a particular segment. In this section of the research, the characteristics of motive segments are identified through chi-square test along with correspondence analysis and analysis of variance.
TABLE 5.2.26 CHI-SQUARE TEST VALUE FOR VARIOUS VARIABLES S. No 1 2 3 1 2 3 4 5 6 7 Variable Type of Institution Department Designation Age Experience Family Size Total Income Gender Source of Information Perception Chi-Square value 1.349 54.102 5.117 3.287 7.442 7.594 3.931 1.673 21.894 19.165 Sig. Value 0.853 0.141 0.745 0.511 0.282 0.269 0.863 0.433 0.000 0.001 Significance or not Not Significant Not Significant Not Significant Not Significant Not Significant Not Significant Not Significant Not Significant Significant Significant
8 9 10 11 12
Choice Criteria Awareness Level Risk Category Frequency of Investment Channel of Investment
38.184 9.979 9.675 12.808 9.325
0.000 0.041 0.046 0.012 0.009
Significant Significant Significant Significant Significant
To understand the characteristics of these three motive segments, association among the segments with various demographic and investment related variables are analysed. Cross tabulation is used to find out the associations and the chi-square test is applied to test the significance of associations. The chi-square values along with their level of significance are given in the following table. From the chi-square test it is found that age, experience, family size, gender and income per month have no significant association with motive based segments. The chi-square test table also reveals that there is a significant association between motive segments and source of information, perception of investors, investment behaviour, choice criteria, and awareness level and risk category of investors. This signifies that the demographic variables do not have association with motive segments whereas investment related variables have association. This shows that motive segmentation is mainly based on investment related variables and not on demographic variables.
5.5.1.8.3. Family income and Total Savings Family income includes salary of the respondents, salary of spouse & children and income from all other sources. The family saving otherwise called as total savings includes discretionary savings and contractual saving. To understand the relationship between income and saving, the correlation analysis is done. TABLE 5.5.26 RELATIONSHIP BETWEEN FAMILY INCOME AND TOTAL SAVINGS S. No Particulars 1 Average Total Savings Rs.8238 2 Average Family Income Rs.30706.12 3 % of Total Savings in 28.1 Family Income 4 Ch-Square Value 128.683 5 Sig. Value 0.000 6 R (Correlation) value 0.438 7 Sig. Value 0.000 8 F Value 34.834 9 Sig. Value 0.000 10 Duncan subsets 4 sub sets The ‘r’ value for the relationship is 0.438 and its significant value is 0.000. This shows that there is a positive relationship between family income and family savings and that relationship is significant at 1 percent significant level.
Family Income Up to 20000 20001-30000 30001-40000 40001-50000 50001 and above Total
TABLE 5.5.27 TOTAL SAVINGS AND FAMILY INCOME Total Saving Up to 50011000115001Above 5000 10000 15000 20000 2000 67(34%)* 42(23%) 13(11%) 2(5%) 89(45%)* 80(43%)* 42(38%) 6(15%) 2 25(13%) 32(17%) 26(24%)* 15(37%)* 5 8(4%) 21(11%) 10(9%) 11(27%)* 4 7(4%) 196 9(5%) 184 19(17%)* 110 7 41 10 21
Total 124(22%) 219(40%) 103(17%) 54(10%) 52(9%) 552
The cross tabulation between family income and family saving indicates that families having less than Rs.20000 income account for 22 percent of total population but their population is 34 percent in less than Rs.5000 saving category. The families having income between Rs.20000 and Rs.30000 are saving to the extent of Rs10000. Likewise higher income families are associated with higher saving categories. This shows that there is a clear trend in the association, and the final inference can be that the size of saving increases with the rise in income. The chi-square test indicates that there is a significant association between income and saving. TABLE 5.2.26 CHI-SQUARE TEST VALUE FOR VARIOUS VARIABLES Variable Chi-Square value Sig. Value Significance or not Type of Institution 1.349 0.853 Not Significant Department 54.102 0.141 Not Significant Designation 5.117 0.745 Not Significant Age 3.287 0.511 Not Significant Experience 7.442 0.282 Not Significant Family Size 7.594 0.269 Not Significant Total Income 3.931 0.863 Not Significant Gender 1.673 0.433 Not Significant Source of Information 21.894 0.000 Significant Perception 19.165 0.001 Significant Choice Criteria 38.184 0.000 Significant Awareness Level 9.979 0.041 Significant Risk Category 9.675 0.046 Significant Frequency of Investment 12.808 0.012 Significant Channel of Investment 9.325 0.009 Significant
S. No 1 2 3 1 2 3 4 5 6 7 8 9 10 11 12
To understand the characteristics of these three motive segments, association among the segments with various demographic and investment related variables are analysed. Cross tabulation is used to find out the associations and the chi-square test is applied to test the significance of associations. The chi-square values along with their level of significance are given in the following table. From the chi-square test it is found that age, experience, family size,
gender and income per month have no significant association with motive based segments. The chi-square test table also reveals that there is a significant association between motive segments and source of information, perception of investors, investment behaviour, choice criteria, and awareness level and risk category of investors. This signifies that the demographic variables do not have association with motive segments whereas investment related variables have association. This shows that motive segmentation is mainly based on investment related variables and not on demographic variables.
5.2.1.1.9 Characteristics of Motive Segments
In the previous section, investors have been classified into three categories namely highly motivated, self centered and least motivated on the basis of their saving motives. It has also been noticed that the highly motivated people will save more than the least motivated people. As the motivation level of highly motivated people is high, convincing them to make investment will not require much effort. To sell more with limited effort, the institutions who offer investment products can concentrate on highly motivated segment. To device effective marketing strategy, it is necessary for them to understand the characteristics of this motive segment. If necessary, they can also alter the existing features of their products and service levels to suit the requirements of a particular segment. In this section of the research, the characteristics of motive segments are identified through chi-square test along with correspondence analysis and analysis of variance.
TABLE 5.2.26 CHI-SQUARE TEST VALUE FOR VARIOUS VARIABLES S. No 1 2 3 1 2 3 4 5 6 7 Variable Type of Institution Department Designation Age Experience Family Size Total Income Gender Source of Information Perception Chi-Square value 1.349 54.102 5.117 3.287 7.442 7.594 3.931 1.673 21.894 19.165 Sig. Value 0.853 0.141 0.745 0.511 0.282 0.269 0.863 0.433 0.000 0.001 Significance or not Not Significant Not Significant Not Significant Not Significant Not Significant Not Significant Not Significant Not Significant Significant Significant
8 9 10 11 12
Choice Criteria Awareness Level Risk Category Frequency of Investment Channel of Investment
38.184 9.979 9.675 12.808 9.325
0.000 0.041 0.046 0.012 0.009
Significant Significant Significant Significant Significant
To understand the characteristics of these three motive segments, association among the segments with various demographic and investment related variables are analysed. Cross tabulation is used to find out the associations and the chi-square test is applied to test the significance of associations. The chi-square values along with their level of significance are given in the following table. From the chi-square test it is found that age, experience, family size, gender and income per month have no significant association with motive based segments. The chi-square test table also reveals that there is a significant association between motive segments and source of information, perception of investors, investment behaviour, choice criteria, and awareness level and risk category of investors. This signifies that the demographic variables do not have association with motive segments whereas investment related variables have association. This shows that motive segmentation is mainly based on investment related variables and not on demographic variables.
