Data Analysis with R
Completed by Xamantha Gayle Riño Humawan
September 29, 2022
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: Plot (Graphics)
- Category: R (Software)
- Category: Data Visualization
- Category: Regression Analysis
- Category: Data Transformation
- Category: Statistical Methods
- Category: Correlation Analysis
- Category: Data Analysis
- Category: Statistical Visualization
- Category: Data Wrangling
- Category: Model Training
- Category: Exploratory Data Analysis
