Series of videos on getting started in Analytics. The videos cover over 20 hours of SAS Programming (Base and Advanced) as well as an additional 20 hours on Basic Statistics, regression modelling and predictive analytics using SAS and R.
Key topics covered include Logistic Regression, propensity and credit risk modeling, clustering, hypothesis testing (t/z/chi etc.)

1.Logistic Regression – Prerequisites for Playlist
2:11
1.Logistic Regression – Prerequisites for Playlist
16. Logistic Regression – ROC Curves ( full series at https://vimeo.com/ondemand/logisticmodel/)
30:02
16. Logistic Regression – ROC Curves ( full series at https://vimeo.com/ondemand/logisticmodel/)
6.Logistic Regression – Splitting data into Training & Validation
8:26
6.Logistic Regression – Splitting data into Training & Validation
5. Logistic Regression – Generating Logistic estimates using Excel and Log Loss
11:46
5. Logistic Regression – Generating Logistic estimates using Excel and Log Loss
4.Logistic Regression – Log Loss Function
6:09
4.Logistic Regression – Log Loss Function
3.Logistic Regression – Logit Transformation in detail
3:20
3.Logistic Regression – Logit Transformation in detail
2. Logistic Regression – Introduction
12:08
2. Logistic Regression – Introduction
1. Logistic Regression – Prerequisites for Playlist
2:11
1. Logistic Regression – Prerequisites for Playlist
OLS Regression Estimates using Solver
18:35
OLS Regression Estimates using Solver
Base SAS Programming - Lecture 6 (Continued on Vimeo -see description)
1:59:35
Base SAS Programming - Lecture 6 (Continued on Vimeo -see description)
Base SAS Programming - Lecture 5
1:09:25
Base SAS Programming - Lecture 5
Base SAS Programming - Lecture 4
1:36:01
Base SAS Programming - Lecture 4
Base SAS Programming - Lecture 3
1:52:55
Base SAS Programming - Lecture 3
Base SAS Programming Lecture 2
1:43:36
Base SAS Programming Lecture 2
Base SAS Programming - Lecture 1
1:49:11
Base SAS Programming - Lecture 1
9. Residual Analysis in Linear Regression
43:07
9. Residual Analysis in Linear Regression
8. Overfitting in Linear Regression
30:21
8. Overfitting in Linear Regression
7. Automatic Variable Selection in SAS for Multiple Regression
34:16
7. Automatic Variable Selection in SAS for Multiple Regression
6. Using Nominal Variables in Linear Regression
28:52
6. Using Nominal Variables in Linear Regression
5. Detecting Multicollinearity in Regression using VIF
38:46
5. Detecting Multicollinearity in Regression using VIF
4. Introducing Multiple Independent Variables in Linear Regression
15:54
4. Introducing Multiple Independent Variables in Linear Regression
3. Interpreting Linear Regression Outputs in SAS
45:01
3. Interpreting Linear Regression Outputs in SAS
2. Assumptions of OLS Regression
24:18
2. Assumptions of OLS Regression
1. Introduction to OLS
43:25
1. Introduction to OLS
Base SAS Programming - Lecture 3
49:20
Base SAS Programming - Lecture 3
Base SAS Programming - Lecture 6 (continued @ https://vimeo.com/ondemand/sasuma)
1:59:54
Base SAS Programming - Lecture 6 (continued @ https://vimeo.com/ondemand/sasuma)
Base SAS Programming - Lecture 5
2:11:31
Base SAS Programming - Lecture 5
19. Introduction to Errors in Hypothesis Testing
14:17
19. Introduction to Errors in Hypothesis Testing
18. Examples on P Value Interpretation
9:39
18. Examples on P Value Interpretation