Data Analysis with R
Completed by Ka Shing Yam
September 28, 2026
15 hours (approximately)
Ka Shing Yam'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 Analysis
- Category: Exploratory Data Analysis
- Category: Correlation Analysis
- Category: Data Import/Export
- Category: Box Plots
- Category: Statistical Analysis
- Category: Model Optimization
- Category: Model Evaluation
- Category: Data Visualization
- Category: Data Cleansing
- Category: Data Science
- Category: R Programming
