5:02
02 1 Background
Brian Caffo
2:28
02 2 Background
6:38
02 3 Background
2:25
02 4 Background
6:39
02 5 Background
2:11
02 6 Background
4:38
03 1 single parameter
8:04
03 2 single parameter
1:58
03 3 single parameter
7:50
03 4 single parameter
1:38
03 5 single parameter
4:39
03 6 single parameter
17:46
03 7 single parameter
5:13
04 1 linear regression
1:17
04 2 linear regression
2:06
04 3 linear regression
2:10
04 4 linear regression
04 5 linear regression
1:54
04 6 linear regression
6:25
04 7 linear regression
3:48
05 1 least squares
3:15
05 2 least squares
4:44
05 3 least squares
7:41
05 4 least squares
9:47
05 5 least squares
12:24
05 6 least squares corrected
4:59
05 7 least squares
24:31
06 1 examples
4:21
06 2 examples
5:00
06 3 examples
10:35
06 4 examples
4:18
07 1 bases
5:07
07 2 bases
8:32
07 3 bases
9:48
07 4 bases
5:47
08 1 residuals
10:24
08 2 residuals
4:45
09 1 Expected Values
2:35
09 2 Expected Values
5:36
09 3 Expected Values
5:45
09 4 Expected Values
3:46
09 5 Expected Values
13:47
09 6 Expected Values
8:34
10 1 Normal Distribution
7:54
10 2 Normal Distribution
5:23
10 3 Normal Distribution
8:49
10 4 Normal Distribution
10:31
11 1 Distributional Results
6:44
11 2 Distributional Results
4:51
11 3 Distributional Results
7:43
11 4 Distributional Results
11:22
11 5 Distributional Results
5:11
11 6 Distributional Results
7:28
11 7 Distributional Results
6:01
11 8 Distributional Results
5:15
12 1 residuals
3:16
12 2 residuals
8:38
12 3 residuals
14:37
12 4 residuals
3:44
13 1 Overfitting and Underfitting
4:47
13 2 Underfitting Bias
1:59
13 3 Variance with an Underfit Model
6:58
13 4 Residual Variance Bias under an Underfit Model
13 5 Bias in an Overfit Model
13 6 Variance of the Residual Variance in an Overfit Model
13:17
13 7 Impact of Inclusion of Variables on Standard Errors
6:45
13 8 Variance Inflation Factors
