This project concerns analysis of data pertaining to Answers to the Depression Anxiety Stress Scale using data from openpsychometrics.org responses of 2018.
The purpose of this project is to gain and provide more insights to silent killers like Depression, Anxiety and Stress. Silent killers in this context refer to diseases with no obvious symptomps or indications. Representing this data in a way which is more engaging is important to those affected and those susceptible so they know how to identify, deal with their situations and when to throw in the towel to ask for help.
- Inferential Statistics
- Data Exploration and Manipulation
- Data Analysis
- Data Modelling
- Data Visualization
Working with open data under “Answers to the Depression Anxiety Stress scales”, the goal is to provide an overview of DASS (Depression Anxiety Stress Scale) scores and other significant variables present in the data according to informative demographics. Country and age are important demographics because countries differ in how children are brought up and the types of freedom they are given, which in turn affects how they tend to perceive themselves.
What would I like to know?
- What demographics influence these diseases? I'm assuming location and upbringing play a major role in childrens psychological health. But what other demographics play roles and to what extent?
Progress Report.
[X] Download the data.
[X] Overview of the data.
[X] Separate into Depression, Anxiety and Stress.
[X] Calculate percentages of distributions.
[X] Visualize each of these separately.
[X] Look for obvious relationships.
[X] Calculate covariance and correlation of variables.
[X] Discard unnecessary variables.
[X] Select a tool for visualization.
[ ] Publish visualization.
Goal With this project I’ll like to make more people aware of these “silent killers”. I would like to know what percentage of the population is affected by what mental diseases and explore possible causes. It is worth noting that these tests were carried out online so I'm not certain of how honest the participants were.
- data exploration/descriptive statistics
- data processing/cleaning
- statistical modeling
- writeup/reporting/visualization
- Python
- VSCode
- Pandas, jupyter, Altair
- Procreate