- Data Cleansing
- Data Visualization
- Data Manipulation
- Model Evaluation
- Data Transformation
- Data Analysis
- R Programming
- Statistical Analysis
- Correlation Analysis
- Data Preprocessing
- Tidyverse (R Package)
- Exploratory Data Analysis
Data Analysis with R
Completed by Eunice Gaille Rh. Nicomedes
July 8, 2022
16 hours (approximately)
Eunice Gaille Rh. Nicomedes '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
