- Descriptive Statistics
- Regression Analysis
- Probability & Statistics
- Data Cleansing
- Exploratory Data Analysis
- Predictive Modeling
- Feature Engineering
- Statistical Inference
- R (Software)
- Statistical Analysis
- Data Wrangling
- Public Health
Logistic Regression in R for Public Health
Completed by Sajith Sasidharan
April 11, 2020
12 hours (approximately)
Sajith Sasidharan's account is verified. Coursera certifies their successful completion of Logistic Regression in R for Public Health
What you will learn
Describe a data set from scratch using descriptive statistics and simple graphical methods as a first step for advanced analysis using R software
Interpret the output from your analysis and appraise the role of chance and bias as potential explanations
Run multiple logistic regression analysis in R and interpret the output
Evaluate the model assumptions for multiple logistic regression in R
Skills you will gain
