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Syllabus for MATH 2500

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Statistics - Principles & Methods, R. Johnson and G. Bhattachryya, 7th edition

Mandatory Topics

1 – Introduction

Overview Only - 2 days

2 –Organization & Description of Data

2.1 – Main Types of Data

2.2 – Tables and Graphs

2.3 – Measures of Center

2.4 – Measures of Variation

4-6 days

3 – Descriptive Bivariate Data

3.1 – Summarization

3.2 – A Designed Experiment

3.3 – Scatter Diagram

3.4 – Correlation Coefficient

3.5 – Prediction

4-6 days

4 – Probability

4.1 – Prob. of an Event

4.2 – Assigning Probabilities

4.3 – Event Relations

4.4 – Conditional Probablity

4.6 – Random Sampling

8days

5 – Distributions

5.1 – Random Variables

5.2 – Distribution of a Discrete R.V.

5.3 – Expectation and Standard Deviation

5.4 – Bernoulli Trials

5.5 – Binomial Distribution

8-10 days

6 – Normal Distribution

6.1 – Continuous R.V.

6.2 – Normal Distribution

6.3 – Standard Normal Dist.

6.4 – Probability Calculations

5-6 days

7 – Sampling Distributions

7.1 – Sampling Dist. of a Statistic

7.2 – Central Limit Theorem

4-5 days

8 – Inferences from Large Samples

8.1 – Estimation and Testing

8.2 – Point Estimation

8.3 – Confidence Interval

8.4 – Hypothesis Testing

8.5 – Inferences about Proportion

10-12 days

Optional Topics

Instructors may choose to cover some, but certainly not all, of the following sections.

4.5 – Bayes’ Theorem – 2 days

5.6 – Poisson Distribution – 1 day

9 – Small Sample Inferences

9.1 – Student’s t distribution

9.2 – Inferences about μ

9.3 – Tests & Confidence Intervals

9.4 – Inferences about σ

5-6 days

6.5 – Normal Approx. to Binomial – 2 days

10 – Comparing Two Treatments

10.1 – Two Designs

10.2 – Difference of Means

10.3 – Inference from Small Samples

10.4 – Randomization

10.5 – Matched Pairs Comparisons

10.7 – Comparing Two Proportions

6-8 days

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