Mitigating Crime through socio-economic policy: regression analysis - Mukhamedkhanova , А.B.; Shadieva, А.А.; Seitova , V.; Koibagarova , S.Т.; Kulbai , B.S. (BUKETOV BUSINESS REVIEW, 2024)
Object: to build a linear regression model for predicting the number of reported crimes using 10 socio-political indicators. Methods: methods of correlation and regression analysis were used for this study. All calculations were performed in the MS EXCEL program. 1 dependent and 10 independent indicators were used as a basis. Findings: 10 variables have been identified that can affect the number of reported crimes and statistical data on these indicators were found in the Bureau of National Statistics of the Republic of Kazakhstan from 2010 to 2022. As a result of this check, only two independent variables were left, on the basis of which a linear regression model was built. The model was highly appreciated by generally accepted estimates, including: significance of f, p-value, normalized R square. Conclusions: Our analysis shows the influence of recipients of targeted social assistance and registered divorces on the crime rate, which allows us to formulate a highly effective linear regression model. Thanks to accurate assessment and reliable predictive ability, our findings shed light on the directions of political interventions aimed at combating crime and improving the welfare and development of society in Kazakhstan.