In this Project we have done analysis for the CRIME AGAINST WOMEN STATE/UNION TERRITORY WISE under IPC FROM (2010 - 2021). In this model we calculated the measures of goodness of fit for the model which showed the following results:- In R- Square Value k > 1, ADJUSTED R2 < R2; that is, as the number of explanatory variables increases in a model, the adjusted R2 becomes increasingly smaller than the unadjusted R2. There seems to be a “penalty” involved in adding more explanatory variables to a regression model. Although the unadjusted R2 is positive, the adjusted R2 turns out to be negative. In The Confidence Interval Approach to Hypothesis Testing. The partial slope coefficient β̂t of V4, V5, V9, V12, V13 are positive which means rates of crime against women in these particular year (state wise) increases. From Anova Table Also since the R^2 value is equal to 30.5360% therefore; it states that the explanatory variables have no impact on the dependent variable (STATES/UT). Finally, after running regression, we tested for auto-correlation, heteroscedasticity and multicollinearity in the model. We found that there is no heteroscedasticity and no autocorrelation.