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Lecture Notes

MATLAB® software is required to run the .m files in this section.

The notes for Lectures 9 and 12 are not available.

LEC # TOPICS SUPPORTING FILES
1 Course Introduction (PDF)
2 Descriptive Statistics (PDF)
3 Probablility (PDF) virtual.m (M)
4 Joint Probability, Independence, Repeated Trials (PDF)
5 Combinatorial Methods for Deriving Probabilities (PDF) combinatorial_example.pdf (PDF)
balls.m (M)
6 Conditional Probability and Baye's Theorem (PDF)
7 Random Variables and Probability Distributions (PDF)
8 Expectation, Functions of a Random Variable (PDF)
9 Risk
10 Some Common Probability Distributions (PDF) cdffit.m (M)
11 Multivariate Probability (PDF)
12 Functions of Many Random Variables
13 Populations and Samples (PDF)
14 Estimation (PDF)
15 Confidence Intervals (PDF)
16 Testing Hypotheses about a Single Population (PDF)
17 Testing Hypotheses about Two Populations (PDF)
18 Small Sample Statistics (PDF)
19 Analysis of Variance (PDF)
20 Analysis of Variance (contd.) (PDF)
21 Multifactor Analysis of Variance (PDF)
22 Linear Regression (PDF)
23 Analyzing Regression Results (PDF)


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