Data Analysis with R
Completed by Yu Lun Cheng
September 30, 2024
15 hours (approximately)
Yu Lun Cheng'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 Transformation
- Category: Statistical Methods
- Category: Correlation Analysis
- Category: Tidyverse (R Package)
- Category: R Programming
- Category: Model Training
- Category: Predictive Modeling
- Category: Data Science
- Category: Data Manipulation
- Category: Data Wrangling
- Category: Regression Analysis
- Category: Exploratory Data Analysis
