25:24

Model Comparison (Logistic & Decision Tree)

50:57

Neural Networks

31:21

Exam 2 Sample Test Review

58:58

Cluster Analysis

42:39

Decision Tree Analysis

54:00

Business Analytics - Logistic Regression

34:46

Syllabus, How-to succeed in BStat, etc

34:07

Module 9 - 2 Sample Hypothesis Testing

45:43

Module 8 Review Problems

17:29

8.3 Hypothesis Testing about a population proportion

18:28

8.2 1-Sample Hypothesis Testing (unkown sigma)

10:31

8.1 1-Sample Hypothesis Testing with known sigma (p-value)

26:32

8.1 1-Sample Hypothesis Testing with a known sigma

36:21

Modules 6 & 7 Review

16:12

Confidence Intervals and Sample Size Determination Pop Prop

11:58

Confidence Intervals for a Pop Mean w Unknown Std Dev (T)

20:52

Confidence Interval & Sample Size determination(known sigma)

09:25

The Central Limit Theorem

06:43

Point Estimators and Sampling Distributions

17:53

Exam 1 - Policies & Guidelines Walkthrough

37:29

Exam 1 - Study Guide Review/Walkthrough

40:11

Modules 4 & 5 Review - More Problems

05:08

How to: Post Your Problem/Explanation Write-Ups

35:45

5.2/5.3 The Normal Distribution & Applications

12:46

4.4 The Poisson Probability Distribution

20:03

4.3 The Binomial Probability Distribution

40:51

4.1/4.2/5.1 Distributions of Discrete & Continuous RVs

06:51

Problem Write-Up/Explanation Directions

26:19

Group Case Directions/Guidance

04:58

3.6 Using Complements

08:03

3.5 Multiplication Rule of Probability

29:33

3.4 Conditional Rule of Probability

17:00

3.3 Addition Rule of Probability

16:37

3.2 Counting Techniques

15:06

3.1 Basic Probability

08:26

2.8 Relative Position (Z-Score calcuation)

04:48

2.7 Empirical Rule

10:34

2.5 Measures of Dispersion

07:15

2.4 Measures of Center

05:31

2.3 Summation Notation Explanation

11:56

2.2 Summarizing Quantitative Data

13:47

2.1 Summarizing Qualitative Data

09:40

Business Stat Introduction

12:49

1.3/1.5 - Populations & Samples, Scales of Measurement ("NOIR")

18:01

1.1/1.2 - Data & Data Sources

14:18

4.3 - Elementary Probability Rules

11:37

4.1/4.2 - Probability, Sample Spaces & Events

23:31

4.5 - Bayes' Theorem

20:02

6.3 - Normal Probability Distribution

11:53

4.4 - Conditional Probability

33:09

5.3 - Binomial Distribution

27:01

5.4 - Poisson Distribution

12:51

6.5 - Exponential Distribution

21:05

7.1/7.2 Sampling Distribution of a Sample mean

21:50

8.2/8.3 t-based distribution, Confidence Intervals & Sample size determination

22:40

8.1 - Z-based Distribution & Confidence Intervals

57:16

12 - Chi Square Tests (for Categorical Data)

28:25

11 - Randomized Block ANOVA

50:07

11 - One-Way ANOVA & Tukey Post-Hoc Analysis

01:08:49

10 - 2-sample hypothesis testing