Data Analysis with R
Completed by Tiago De Souza Vicente
July 15, 2025
15 hours (approximately)
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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 Wrangling
- Category: Regression Analysis
- Category: Statistical Methods
- Category: Model Evaluation
- Category: Box Plots
- Category: Statistical Analysis
- Category: Exploratory Data Analysis
- Category: Statistical Visualization
- Category: Data Science
- Category: Data Transformation
- Category: Data Visualization
- Category: Data Analysis
