Data Analysis with R
Completed by Tzu-Liang Yang
September 28, 2025
15 hours (approximately)
Tzu-Liang Yang'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 Science
- Category: R Programming
- Category: Data Transformation
- Category: Tidyverse (R Package)
- Category: Data Visualization
- Category: Plot (Graphics)
- Category: R (Software)
- Category: Model Training
- Category: Exploratory Data Analysis
- Category: Correlation Analysis
- Category: Statistical Visualization
- Category: Box Plots
