Predictive Analytics for Diabetes Risk Assessment: Unraveling the Data Maze

Diabetes mellitus is a chronic metabolic disorder characterized by high blood sugar levels over a prolonged period. With its prevalence on the rise globally, there's an increasing need for effective predictive models to identify individuals at risk of developing diabetes. This project aims to utilize statistical techniques to analyze a dataset containing various demographic, lifestyle, and clinical factors to predict the risk of diabetes.

1. Diabetes risk P rediction data

2. Objectives Improve overall quality of life by preventing complications. To optimize prevention strategies and treatment plans. preventing or delaying diabetes reduces healthcare costs by lowering treatment expenses and improving overall economic productivity.

3. Uses Personal care Insurance Help Treatment effectiveness Track disease progression

4. Decision making To understand the disease improving prevention strategies To enhance overall public health outcomes.

5. Application in different fields It is used to represent the population in a study. We can use the data to apply data analysis tools like frequency analysis, charts and graphs, tabular representations(pivot table), descriptive statistics (mean, median, mode, variance, standard deviation), correlation and regression, trend lines (forecasting techniques).

6. Qualitative Gender, Weakness, Visual blurring, Hairloss , Itching, Irritablity , Muscles stiffness, Obsesity Put a check ( ) to the correct answer. Quantitative Weightloss , Diabetes values, Age

7. Descriptive statistics Diabetes Value Mean 284.0269231 Standard Error 2.225893225 Median 285 Mode 352 Standard Deviation 50.75817508 Sample Variance 2576.392337 Kurtosis 1.738508795 Skewness -1.069832083 Range 239 Minimum 120 Maximum 359 Sum 147694 Count 520 Largest(1) 359 Smallest(1) 120 Interpretation :- On diabetes value t he mean is 284.03 The median is 285 The mode is 352 The standard deviation is 50.75 that means if the average 284 is a changing it will be within +-51 values so it will be within a 284-51and 284+51

8. Correlation & Regression SUMMARY OUTPUT Regression Statistics Multiple R 0.021325645 R Square 0.000454783 Adjusted R Square -0.001474841 Standard Error 50.7955914 Observations 520 ANOVA   df SS MS F Significance F Regression 1 608.1121964 608.1121964 0.235685 0.627546 Residual 518 1336539.511 2580.192106 Total 519 1337147.623         Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 279.7485204 9.089996325 30.77542723 4.9E-119 261.8907 297.6063 261.8907 297.6063 Age 0.089079855 0.183490535 0.485473843 0.627546 -0.2714 0.449557 -0.2714 0.449557

9. . . If- Y=Value of Diabetes(Dependent) X=Age Group(Independent) Multiple R is a correlation 0.0213 that means lower positive correlation is a possible means Diabetes value will not get affected much if age group is higher or lower R square is a coefficient of determination that means if there is any change in diabetes values it will be 0.045 % for age group

10. Forecasting Method Analysis . .

11. Pivot table weakness (All) Itching No visual blurring (All) Sum of sudden weight loss by Kgs Column Labels Row Labels Female Male Grand Total 16-25 2 4 6 26-35 122 234 356 36-45 73 230 303 46-55 121 127 248 56-65 44 135 179 66-75 3 55 58 Grand Total 365 785 1150

12. . Interpretation- There are highest number of diabetes patient who belongs from the age group of 26-35 The diagram is positively skewed Under the age group of 16-25 child/teenage the level of diabetes is comparatively low. In compare to male the level of diabetes in female is low.

13. Suggestions Healthy eating Blood Sugar Monitoring Stress Management

14. Diabetes is a disease that should be taken seriously. If there are no significant complication with diabetes mellitus, patients can enjoy exercise with very few limitations. The study suggest that incorporating regular physical activity and adopting a balanced diet could play pivotal roles in reducing the likelihood of developing diabetes. Conclusion

15. THANKYOU

16. Presented by: Parth Chauhan Hitanshi Mamtora Chandni Vyas Pankti Patel Harita Raythatha Digvijay Solanki