- Regression Analysis
- Data Wrangling
- Exploratory Data Analysis
- Data Preprocessing
- Data Cleansing
- Predictive Analytics
- R Programming
- Data Manipulation
- Model Evaluation
- Data Visualization
- Feature Engineering
- Forecasting
Data Analysis with R
Completed by ROYAL IWUNZE
February 13, 2024
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
