- Data Science
- Data Analysis
- Model Evaluation
- Statistical Analysis
- Statistical Modeling
- Feature Engineering
- Predictive Analytics
- Exploratory Data Analysis
- Forecasting
- Data Wrangling
- R Programming
- Regression Analysis
Data Analysis with R
Completed by MUHAMMAD DZAKY RAFIAN
June 11, 2022
16 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
