Fall 2020:
1. First Lecture in BUAD 300
Provides a general introduction to the course and reviews the parameters of probability distributions.
2. Second Lecture in BUAD 300
Review of the normal distribution.
3. Linear Combinations
Examines the characteristics of the parameters of linear combinations of random variables.
4. Introduction to Hypothesis Testing
Reinforces concepts from Stat 200.
5. Review of the one-sample t-Distribution
Provides a review of the one-sample t-distribution.
6. Review of the two-sample t-distribution
Provides a review of the two-sample t-distribution.
7. t-Test: Minitab Tutorial
Provides illustrated Minitab instructions required to perform a one-sample t-test.
8. Correlation
Introduces basic concepts regarding correlation.
9. Ordinary Least Squares
Provides an introduction to the most frequently used method for estimating linear regression parameters – Ordinary Least Squares (OLS).
10. OLS Significant Estimators Review
Reviews residual error assumptions and significance test for OLS coefficients..
11. Time Trend and Residual Errors
Continues OLS: Introduces the calculation and analysis of residual errors and discusses the violations of assumptions.
12. Introduction to ANOVA for Regression
Introduces the analysis of variance and the F-ratio.
13. Prediction and Confidence Intervals
Examines the characteristics of the confidence interval about the prediction.
14. Runs Analysis for Residual Errors
Describes testing for correlated errors using a common non-parametric test.
15. Chi-Square
Introduces and describes a test performed on sample data to see if the sample is from a normally distributed population.
16. Project 1: Minitab Tutorial
Demonstrates the creation of a dummy variable matrix.
17. Multiple Regression
Regression technique for more than one independent variable.
18. Dummy Variables
Provides an explanation of dummy variables and their usage in regression models.
19. Creating Your Dummy Variable
Demonstrates the creation of a dummy variable matrix.
20. Project 2 Demonstration: Minitab Tutorial
Demonstrates the creation of a dummy variable matrix.
21. ANOVA for Surveys
Introduces the analysis of variance applied to survey data.
21. Sign Test
Non-parametric test 1 of 5.
22. Signed Rank Test
Non-parametric test 2 of 5.
23. Rank Correlation Test
Non-parametric test 3 of 5.
24. Mann-Whitney Test
Non-parametric test 4 of 5.
25. Kruscal Wallis Test
Non-parametric test 5 of 5.
26. Duty in Statistical Analysis
Ethical responsibilities in Statistics.
27. Analyzing Survey Data #1: MinitabTutorial
A Minitab tutorial demonstrating steps in analyzing survey data, 1 of 4.
28. Analyzing Survey Data #2: Minitab Tutorial
A Minitab tutorial demonstrating steps in analyzing survey data, 2of 4.
29. Analyzing Survey Data #3: Minitab Tutorial
A Minitab tutorial demonstrating steps in analyzing survey data, 3 of 4.
30. Analyzing Survey Data #4: Minitab Tutorial
A Minitab tutorial demonstrating steps in analyzing survey data, 1 of 4.
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Prof. Richard M. Robinson, PhD 