A Statistical Approach to Study the Socio Demographic Profile of Working Women of Rural and Urban Area of the Three Districts of Karnataka State-A Case Study

Dr. (Smt) C.P.S. Working women in the contemporary society are increasing day by day particularly in the urban area mainly due to the impact of education, employment opportunities, women reservation policies and so on to mention a few. This paper is mainly devoted to analyze and compare the social profile of rural and urban working women of the three districts of Karnataka state based on different demographic factors age, education, marital status, family type, monthly income, monthly saving and residence type with respect to area. It is essential to determine whether there is a difference in rural and urban working women in different socio-demographic characters. This is measured by testing the association between different demographic factors and area using Chi-square test through SPSS package.

cross-sectional study. Women who delivered a baby in the past 1 year were included in this study. A total of 300 women responded (93.2%) and gave consent to participate in the study. Prevalence of home delivery was 37.7%. Bivariate analysis showed that religion, caste, education of women and their partners, occupation of the spouse, monthly family income and socioeconomic status had a significant association with the choice of place of delivery. But multivariate regression analysis showed only religion, caste, education of spouse and monthly income to be significant factors in determining place of delivery. The findings of this study suggest that individual countries have to formulate interventions which will target marginalized or vulnerable populations with reference to caste, religion and wealth. A significant improvement in reaching the 5th MDG can be achieved if the first three MDG goals are focused on, i.e., eradication of poverty, achieving universal education and women empowerment.
Massiah J (4) presented "Employed women in Barbados: a demographic Profile, 1946-1970"which is based on data from population censuses from 1946, 1960, and 1970, analyzes demographic factors associated with female labor force participation in Barbados. The general worker rate among women had declined in the post-World War II period from 58.3% in 1946 to 45.6% in 1970; however, the rate for men showed a similar decline in this period, from 92.0% to 80.7%. The dissimilarity index of the age composition of male and female workers was only 4.8 in 1970, and the pattern of female age-specific worker rates at ages below 50 years is gradually approaching that of males. Female worker rates by education continue to be lower than those for males, yet are increasing for women in the higher educational categories. In 1970, 66% of working women were mothers. Younger working and nonworking women reveal lower levels of fertility than older women, although nonworking women tend to reveal higher fertility levels at all ages than their working counterparts. Labor force participation rates decline with parity. Among mothers, 1970 worker rates rose gradually to a peak of 52% at age 25-29 years, then assumed a plateau-like shape until age 45-49 years before beginning a gradual decline. In contrast, among non mothers, the curve rises from 40% at ages 15-19 years to a peak of 72% at age 25-29 and then drops to 48% for women at the end of the age span.

Preliminary Statistical Analysis:-
In this section, where association between different demographic factors and area were identified using chi-square test.

Association between age and area:-
In this section we test the following hypothesis H0: There is no significant association between age and area  From the above table, the result is significant since significant value is less than 0.05. Hence we reject null hypothesis, which indicates that there is an association between demographic factor age and area. Phi, Cramer"v and Contingency Coefficient measures the strength of the association. One can observe from the Table-3.1,3 that the association between demographic factor age and area is 0.218. It means that there is 21.8% of association between age and area.
Association between education and area:-H0: There is no significant association between demographic factor education and area  From the above table, the chi-square test reveals that the result is not significant since significant value is more than 0.05. Hence we accept the null hypothesis, that is, there is no significant association between demographic factor education and area. The symmetric measures reveals that the strength of an association between demographic factor education and area is is very week, that is,0.070. It means that , only 7 % of association between education and area.

Association between marital status and area:-
H0: There is no significant association between demographic factor marital status and Area   Table-3-3-2 indicates that the result is significant since the significant value is less than 0.05. Hence we reject the null hypothesis, that is, there is an association between demographic factor marital status and area. It is found that the strength of the association between demographic factor marital status and area is 0.109. It indicates that there is 10.9 % of association between marital status and area.
Association between family type and area:-H0: There is no significant association between demographic factor family type and area  From the above table, it shows that the result is significant since significant value is less than 0.05. Hence we reject null hypothesis, which indicates that there is an association between demographic factor family type and area. From the above table one can observe that the strength of the association between demographic factor family type and area shows 0.239. It means that , the strength of the association between family type and area is 23.9 %.

Association between monthly income and Area:-
H0: There is no significant association between monthly income and area.  From the above table, it shows that the result is significant since significant value is less than 0.05. Hence we reject the null hypothesis. Which indicates that there is an association between monthly income and area. It is found that the strength of the association between monthly income and area is 0.217,which indicates that there is 21.7 % of association between monthly income and area.

Association between monthly savings and Area:-
We test the following hypothesis by using chi square test H0: There is no significant association between monthly savings to area. From the above table, the result is not significant since significant value is more than 0.05. Hence we accept the null hypothesis, which implies that there is no association between demographic factor monthly savings and area Table : 3

. 6.3:-Symmetric Measures
It is found that an association between demographic factor monthly saving and area is 0.048. It means that , only 4.8 % of association between monthly income and area.
Association between residence type and Area:-H0: There is no significant association between residence type and area.  From the above table, the result is significant since significant value is less than 0.05. Hence we reject the null hypothesis ,that is, there is an association between demographic factor residence type and area.

Conclusion:-
The Statistical analysis of social profile of rural and urban working women of the three districts in Karnataka state was done by testing the association between various demographic factors and area of the respondents using chisquare test. From the analysis it reveals that the null hypotheses are rejected in the cases of testing the association between the demographic factors age, marital status, family type , monthly income, residence type and area of the respondents. In all the cases the significant value is less than 0.05.Which means that there is a significant association between the above mentioned demographic factors and area of the respondents. The study reveals that there is a significant difference in rural and urban working women in above mentioned demographic factors. One can observe that the association between the demographic factors education and monthly saving with area gives the chi-square value more than 0.05 which accepts the null hypotheses. Which indicates that there is no significant association between area and demographic factors education and monthly saving. Which indicates that there is no significant difference in rural and urban working women according to demographic factors education and monthly saving. The extent to which the variables are associated is measured by the symmetric measures of Phi, Cramer"s V and Contingency table. The strength of the association between the variables varies from 4.8% to 23.9%. The maximum strength of association is found for area and the demographic factors family type , that is, nearly 24% followed by age and monthly income nearly 22%. The minimum strength of association is found between area and the demographic factors education and monthly saving of strength 7% and 5%.
The study highlighted the role of working women in socio-economic development by studying level of participation in different types of occupations based on different demographic factors in three districts of Karnataka state with respect to area. The role of women in the social profile and status should be appreciated.