Regression with Excel#
You’ll learn to perform regression analysis using Excel, covering:
- Data Preparation: Understanding the cleaned dataset and necessary columns for analysis.
- Enabling the Tool: How to enable the Data Analysis Tool Pack in Excel.
- Types of Regression: Differences between simple and multiple linear regression.
- Setting Up Regression: Steps to input dependent (new deaths) and independent variables (new cases, new tests, new vaccinations, stringency index) for the analysis.
- Interpreting Output: Reading the regression output, focusing on adjusted R-squared, significance value (F-test), and P-values.
- Coefficient Interpretation: Understanding the impact of each independent variable on the dependent variable, including scaling factors (per 1000 units).
- Model Evaluation: Evaluating the model based on significance values and understanding the implications of unexpected results (e.g., stringency index).
- Further Analysis: Recognizing the need for additional analysis when encountering unexpected or inconclusive results.
Here are the links used in the video: