Marital status of women compared to the economic conditions of the women before and after taking a loan from MFIs.Marital statusR2Adjusted R2Stan. ErrorUnstndardized BetaStandard BetaSig.

Married0.1650.1620.0510.4170.4060.04*

Single0.2030.1460.1560.2940.250*

Widowed0.3190.3040.1240.5640.5650*

Significant at 0.05 *In the above mentioned table, we compare the marital status of women who took part in microfinance activities with the economic conditions of the poor women before and after taking a loan from MFIs. When linear regression analysis technique was run by selecting the marital status of the women who took the loan. R2 coefficient of determination of married women shows the cases explained by independent variable, i.e. condition of the women before micro-finance into dependent variable i.e. condition of the women after micro-finance. The value of R2 is about 16.5% of married women. After removing error chances from R2 the value is 16.2%. The comparison of Standard Error 0.051 and Unstandarized beta 0.417 shows that data lie near the regression line which means that dispersion of data is nearly normal. Standards beta for married women is 40.6%, which means when one unit of standard deviation is increased with independent variable there is 0.406 unit increase independent variable. Significant value for married women who are taking loans from MFIs is 0.04 which is less than P-value 0.05, which shows that our null hypothesis is rejected and the alternative hypothesis is accepted which is that there is difference between before and after economic conditions of poor women.When linear regression analysis technique was run by selecting the marital status of the women who took the loan. R2 coefficient of determination of married women shows the cases explained by independent variable, i.e. condition of the women before micro-finance into dependent variable i.e. condition of the women after micro-finance. The value of R2 is about 16.5% of married women. After removing error chances from R2 the value is 16.2%. The comparison of Standard Error 0.051 and Unstandarized beta 0.417 shows that data lie near the regression line which means that dispersion of data is nearly normal. Standards beta for married women is 40.6%, which means when one unit of standard deviation is increased with independent variable there is 0.406 unit increase independent variable. Significant value for married women who are taking loans from MFIs is 0.04 which is less than P-value 0.05, which shows that our null hypothesis is rejected and the alternative hypothesis is accepted which is that there is difference between before and after economic conditions of poor women.When linear regression analysis technique was run by selecting the marital status of the women who took the loan. R2 coefficient of determination of married women shows the cases explained by independent variable, i.e. condition of the women before micro-finance into dependent variable i.e. condition of the women after micro-finance. The value of R2 is about 16.5% of married women. After removing error chances from R2 the value is 16.2%. The comparison of Standard Error 0.051 and Unstandarized beta 0.417 shows that data lie near the regression line which means that dispersion of data is nearly normal. Standards beta for married women is 40.6%, which means when one unit of standard deviation is increased with independent variable there is 0.406 unit increase independent variable. Significant value for married women who are taking loans from MFIs is 0.04 which is less than P-value 0.05, which shows that our null hypothesis is rejected and the alternative hypothesis is accepted which is that there is difference between before and after economic conditions of poor women.

When comparing the results for married, single and widows there are quite different results. Widows experienced the most benefit as the beta value of them is 56.5%.

Model Summary

ModelRR SquareAdjusted R SquareStd. Error of the Estimate

1.415a.173.170.25681

a. Predictors: (Constant), Before_Microfinance

Coefficients

ModelUnstandardized CoefficientsStandardized CoefficientstSig.

BStd. ErrorBeta

1(Constant)1.344.07717.375.000

Before_Microfinance.415.046.4159.111.000

a. Dependent Variable: After_Microfinance

In the above mentioned table, we compare the economic conditions of the women before and after taking a loan from MFIs. In this table, we do a a Paired Samples Test to compare the conditions of women who taking part

Adjusted R2 show the value explained by the independent variable into a dependent variable after removing error chances from R2The comparison of Stann. Erro and unstandard beta show the dispersion of data along regression lineStandard beta shows the change in term of standard deviation when one standard deviation increases in independent variable how many units of standard deviation increased in the perception