A simple introduction about Regression analysis

1. Regression

2. Regression to Mediocrity

3. Regression towards mean

4. Eccentricity - Correlation

5. No Correlation = No Relationship

6. What does correlation mean?

7. A Use Case
⾼高⾎血压 糖尿病 没病

8. Regression Analysis
Relationship Variables
X : Independant Variables (predictor)
Y : dependant Variables
B : Unknown parameters
Y = f(B,X)

9. Linear Regress ( Ordinary Least Squares )
0
40
80
120
160
0 35 70 105 140

10. Story of Ceres

11. Demo
Wine Predict

12. Logistic Regression

13. Confusion Matrix
Sensitivity = TP/( TP + FN) Specificity = TN/( TN + FP)

14. Demo
Predict Election