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  1. Introduction

   1. What Is Machine Learning.srt

   2. Types of Machine Learning.srt

  2. Simple Linear Regression

   1. Linear Regression Introduction.srt

   10. Interpreting Regression Tables (Part 3).srt

   2. Linear Regression.srt

   3. Linear Regression Model (Graphical Representation).srt

   4. Formatting Excel Spreadsheets.srt

   5. First Regression in Excel.srt

   6. What Is OLS.srt

   7. Interpreting Regression Tables (Part 1).srt

   8. Decomposition of Variability.srt

   9. Interpreting Regression Tables (Part 2).srt

  3. Multiple Linear Regression

   1. Multiple Regression Analysis.srt

   10. Dummy Variables.srt

   11. Making Predictions Using Linear Regression.srt

   2. Multiple Linear Regression (Example).srt

   3. Mutiple Linear Regression (Results).srt

   4. OLS Assumptions.srt

   5. OLS Assumptions Linearity.srt

   6. OLS Assumptions No Endogeneity.srt

   7. OLS Assumptions Normality and Homoscedasticity.srt

   8. OSL Assumptions No Autocorrelation.srt

   9. OLS Assumptions No Multicollinearity.srt

  4. Logistic Regression

   1. Introduction to Logistic Regression.srt

   2. From Linear to Logistic Regression.srt

   3. Logistic vs. Logit Function.srt

   4. Applying Logistic Regression in Excel.srt

   5. Interpreting Regression Coefficients.srt

   6. Logistic Regression with XReal.srt

   7. Understanding the Logistic Regression Summary (Part 2).srt

   8. ROC Curve.srt

   9. Underfitting and Overfitting.srt