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0:01:49

My Channel is Moving!

2:16:10

Probability and Measure, Lecture 8: Product Measure and Fubini-Tonelli

1:58:19

Probability and Measure, Lecture 6: Integration and Convergence Theorems

1:27:41

Probability and Measure, Lecture 7: Lebesgue-Stieltjes Measure and Monotone Classes

1:23:39

Probability and Measure, Lecture 5: Measurable Functions

1:22:00

Probability and Measure, Lecture 4: Lebesgue Measure

1:23:37

Probability and Measure, Lecture 3: Uniqueness and Dykin's Pi-Lambda Theorem

1:34:07

Probability and Measure, Lecture 2: Carathéodory's Extension Theorem

0:50:15

Probability and Measure Lecture 1: What is a Measure?

0:02:38

Channel Updates, January 2022

0:55:05

DoE Review Lecture

0:45:41

TSA Review Lecture

1:17:06

TSA Lecture 24: The GARCH Process

1:06:19

DoE Lecture 24: Crossover Design

0:59:59

TSA Lecture 23: Exponential Smoothing

1:08:46

DoE Lecture 23: Non-Normal Data in R Studio

1:17:38

TSA Lecture 22: Estimating the Spectral Density III

1:10:45

DoE Lecture 22: Designs with Non-Normal Data

1:21:09

DoE Lecture 21: Plackett-Burman Designs

1:15:26

TSA Lecture 21: Estimating the Spectral Density II

1:19:36

TSA Lecture 20: Estimating the Spectral Density

1:12:34

DoE Lecture 20: Mixed Level Designs and Designing Experiments in R

1:28:07

TSA Lecture 19: Spectral Density and Distribution

1:23:28

DoE Lecture 19: Prime and Mixed Level Designs