Course Outline

 

Course Description:

This course is an introduction to probability, descriptive and inferential statistics, with applications to the natural sciences, business, economics, and the behavioral sciences.

 

Course Outline:

1)           Introduction to Statistics

              a)           Statistical and Critical Thinking

              b)           Types of Data

              c)           Collecting Sample Data

2)           Exploring Data with Tables and Graphs

              a)           Frequency Distributions for Organizing and Summarizing Data

              b)           Histograms       

              c)           Graphs That Enlighten and Graphs That Deceive

              d)           Scatterplots, Correlation, and Regression

3)           Describing, Exploring, and Comparing Data

              a)           Measures of Center

              b)           Measures of Variation

              c)           Measures of Relative Standing and Boxplots

4)           Probability

              a)           Basic Concepts of Probability

              b)           Addition Rule and Multiplication Rule

              c)           Complements, Conditional Probability, and Bayes’ Theorem

              d)           Counting

              e)           Probabilities Through Simulations

5)           Discrete Probability Distributions

              a)           Probability Distributions

              b)           Binomial Probability Distributions

              c)           Poisson Probability Distributions

6)           Normal Probability Distributions

              a)           The Standard Normal Distribution

              b)           Real Applications of Normal Distributions

              c)           Sampling Distributions and Estimators

              d)           The Central Limit Theorem

              e)           Assessing Normality

              f)            Normal as Approximation to Binomial

7)           Estimating Parameters and Determining Sample Sizes

              a)           Estimating a Population Proportion

              b)           Estimating a Population Mean

              c)           Estimating a Population Standard Deviation or Variance

              d)           Bootstrapping: Using Excel for Estimates

8)           Hypothesis Testing

              a)           Basics of Hypothesis Testing

              b)           Testing a Claim About a Proportion

              c)           Testing a Claim About a Mean

              d)           Testing a Claim About a Standard Deviation or Variance

9)           Inferences From Two Samples

              a)           Two Proportions

              b)           Two Means: Independent Samples

              c)           Two Dependent Samples (Matched Pairs)

              d)           Two Variances or Standard Deviations

10)         Correlation and Regression

              a)           Correlation

              b)           Regression

              c)           Prediction Intervals and Variation

              d)           Multiple Regression

              e)           Nonlinear Regression

11)         Goodness-of-Fit and Contingency Tables

              a)           Goodness-of-Fit

              b)           Contingency Tables

12)         Analysis of Variance

              a)           One-Way ANOVA

              b)           Two-Way ANOVA

13)         Nonparametric Tests

              a)           Basics of Nonparametric Tests

              b)           Sign Test

              c)           Wilcoxon Signed-Ranks Test for Matched Pairs

              d)           Wilcoxon Rank-Sum Test for Two Independent Samples

              e)           Kruskal-Wallis Test for Three or More Samples

              f)            Rank Correlation

              g)           Runs Test for Randomness

14)         Statistical Process Control

              a)           Control Charts for Variation and Mean

              b)           Control Charts for Attributes