In this exercise, results from a depression survey are compared with NYC public health data. Statistical analysis is demonstrated along with different examples of data transformation.

For Applied Statistics Project

Final

San Bernardino County has variable CES 4.0 Scores depending on geographic location. As CES 4.0 Scores take into account both Pollution Burden scores and Population Characteristics, this dashboard aims to explore the areas with both the lowest and highest mean numbers of Asthma-related Emergency Department visits (per 10,000) and their percent of Poverty and Pollution Burden Score from 2015 to 2017 to visualize if differences in Poverty and Pollution Burden lead to differences in numbers of Asthma-related Emergency Department visits in San Bernardino County. This dashboard can guide public health response in San Bernardino County in targeting resources and environmental policy change within areas and populations with the most vulnerability to respiratory illness.

Use of unique RandIDs Limited to 2K datapoints Fixed cigperday Transformation for skewness of Cigperday skewness Scaling of Age and Cigperday Exclusion of outliers Encoding categorical features. RFE better features and metrics Features by RF, byLasso, by Correlation clight increase of measures with RFE, increase of specificity: ## Accuracy Precision Recall Specificity F1_Score AUC ## Accuracy 0.7983871 0.4888889 0.2222222 0.9420655 0.3055556 0.7611633

Unique RandIDs

Unique IDS