Data Analysis with R
Completed by Jaeyoung Jeong
November 27, 2023
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 Analysis
- Category: Box Plots
- Category: Data Manipulation
- Category: Tidyverse (R Package)
- Category: Data Science
- Category: R Programming
- Category: Data Transformation
- Category: Correlation Analysis
- Category: Data Wrangling
- Category: Regression Analysis
- Category: Statistical Methods
- Category: Data Visualization
