Regression Analysis Using Excel And R programming language (With Certificate)

Service Description

This online course is designed to introduce learners to the foundational principles of regression analysis, using both Excel and R programming. It focuses on practical, hands-on learning, making complex statistical concepts easier to understand and apply in real-world scenarios. Whether you are a student, professional, or researcher, this course will enhance your analytical skills and deepen your understanding of data-driven decision-making.

You will start by learning basic regression techniques, including linear regression and multiple regression. By using Excel’s built-in tools and R’s powerful coding environment, you will gain the ability to analyze and interpret build predictive models, and make sound conclusions.

1. Introduction to Regression Analysis

– Overview of regression analysis
– Types of regression (linear, multiple, logistic)
– The importance of regression in data analysis

2. Getting Started with Excel for Regression
– Using Excel’s data analysis tool
– Creating scatter plots and trendlines
– Running linear regression models in Excel

3. Introduction to R Programming for Regression
– Basics of R programming
– Installing necessary R packages
– Running your first regression analysis in R

4. Simple Linear Regression
– Understanding the simple linear regression model
– Assumptions of linear regression
– Estimating coefficients and interpreting results

5. Multiple Regression Analysis

– Extending linear regression to multiple predictors
– Handling multicollinearity
– Interaction terms in multiple regression

6. Diagnostic Measures and Model Evaluation
– Checking for residual errors
– R-squared, adjusted R-squared, and other key metrics
– Cross-validation and model performance

7. Final Project: Analyzing Real-World Data 
– Applying learned skills to a practical dataset
– Reporting and presenting your finding