Kaggle.com: rosaaestrada - Mental Health & Age Analysis Among U.S. Adults

public.tableau.com: rosaestrada - Factors Influencing 'No Good' Mental Health Days

In this project I analyzed the relationship between mental health and age in adults between the ages of 18 and 99 in the United States using Pearson's Chi-square, Analysis of Variance (ANOVA), and Correlation Matrix.

This project employs a structured methodology consisting of (Data cleaning, Exploratory Data Analysis (EDA), and feature engineering). Following those steps, statistical analysis is conducted utilizing Pearson's Chi-Square, Analysis of Variance (ANOVA), and Correlation Matrix.

• 1 in 5 adults have a mental health condition; that is more than the population of New York and Florida combined, making up more than 40 million Americans (Mental Health America, 2023).
• In 2018, 19% of adults experienced a mental health illness (Terlizzi & Zablotsky, 2020).
• In 2019, 20% of adults were living with a mental health illness, and in 2020, the percentage increased to 40% (The Blackberry Center, 2020).
• The National Alliance on Mental Health Illness found that 50% of all lifetime mental illnesses begin at the age of 14, and 75% begin at the age of 24 (2023).

References:

• Mental Health America. (2023). The State of Mental Health in America 2018. Mental Health America. Retrieved March 23, 2023, from https://www.mhanational.org/issues/state-mental-health-america-2018
• National Alliance on Mental Illness. (n.d.). Mental Health Conditions. NAMI. Retrieved April 8, 2024, from https://www.nami.org/About-Mental-Illness/Mental-Health-Conditions
• Terlizzi, E. P., & Zablotsky, B. (2020, September). Mental Health Treatment Among Adults: United States, 2019. PubMed. Retrieved April 8, 2024, from https://pubmed.ncbi.nlm.nih.gov/33054921/
• The Blackberry Center. (2020, December 28). Mental Health Statistics in 2020 Compared to 2019 - BBC. The Blackberry Center. Retrieved March 27, 2023, from https://www.theblackberrycenter.com/mental-health-statistics-in-2020-compared-to-2019/

• Python= 3.9.13
• Pandas= 1.4.4
• NumPy= 1.21.5
• Seaborn= 0.11.2
• Statsmodels= 0.13.2
• Matplotlib= 3.5.2
• Dataset loaded with chunksize= 10000

• Data - Contains raw data, preprocessed data, and the location where the data was collected
• Jupyter Notebook - The full source code along with explanations as a .ipynb file
• Python Code - The full source code along with explanations as a .py file
• Results - Summary Statistics, Visualizations, and Final Evaluation of the project