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

In this tutorial, we analyze the retail expansion strategy for In-N-Out Burger using R.

Neste trabalho, foi realizada uma análise de churn utilizando Modelos Lineares Generalizados (MLG) com um conjunto de dados de uma empresa de telecomunicações. Foram examinadas variáveis como idade, tipo de contrato, serviços utilizados (internet, segurança online, streaming) e métodos de pagamento para identificar fatores que influenciam o cancelamento de clientes. O modelo estimou as probabilidades de churn, destacando que contratos mais longos e suporte técnico reduzem o cancelamento, enquanto internet de fibra e cheque eletrônico estão associados a maiores chances de saída. Os insights obtidos orientam estratégias para aumentar a retenção de clientes.

Statistical modeling final for MSDA Fall 2024