Computational Methods: Regression


Learning Objectives

Upon successful completion of this module, you will be able to:

1) Define regression analysis.

2) Conduct simple descriptive statistics required for regression analysis.

3) Find the absolute minimum of a continuous function needed for derivation of regression models.

4) Take partial derivatives of a function needed for derivation of regression models.

5) Enumerate effective use of regression.

6) Enumerate uses and abuses of regression.

 

Videos

Title: Prior Knowledge for Regression. Simple Statistics

Summary: This video is about simple statistics as prior knowledge needed for regression. Main items are average, sum of squares total, variance and standard deviation.

Learning Objectives: After watching this video, you should be able to calculate average, sum of squares total, variance and standard deviation.

Slides with Annotation: View slides with annotations


Title: Prior Knowledge for Regression: Absolute Minimum of a Function of One Variable.

Summary: Review finding the absolute minimum of a function of one variable.

Learning Objectives: After watching this video, you will be able to find the minimum of a function of one variable.

Slides with Annotation: View slides with annotations


Title: Prior Knowledge for Regression: Partial Derivatives

Summary: This video will review partial derivatives.

Learning Objectives: After watching this video, you will be able to find the partial derivatives of a function of more than one variable.

Slides with Annotation: View slides with annotations