Data Analysis with R
Completed by Jing Wang
April 19, 2026
15 hours (approximately)
Jing Wang's account is verified. Coursera certifies their successful completion of Data Analysis with R
What you will learn
Prepare data for analysis by handling missing values, formatting and normalizing data, binning, and turning categorical values into numeric values.
Compare and contrast predictive models using simple linear, multiple linear, and polynomial regression methods.
Examine data using descriptive statistics, data grouping, analysis of variance (ANOVA), and correlation statistics.
Evaluate a model for overfitting and underfitting conditions and tune its performance using regularization and grid search.
Skills you will gain
- Category: Data Visualization
- Category: Plot (Graphics)
- Category: R (Software)
- Category: Tidyverse (R Package)
- Category: Data Science
- Category: R Programming
- Category: Data Transformation
- Category: Box Plots
- Category: Exploratory Data Analysis
- Category: Statistical Visualization
- Category: Model Training
- Category: Statistical Analysis
