INTRODUCTORY STATISTICS COURSE
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The Introductory Statistics course contains 93 selfgrading microlearning lessons that work instantly inside your Learning Management System (LMS).
Introductory Statistics is intended for the onesemester introduction to statistics course. It focuses on the interpretation of statistical results, especially in real world settings, and assumes that students have an understanding of intermediate algebra. In addition to practice and homework sets, examples of each microlearning topic are explained stepbystep throughout. This course also includes collaborative exercises and statistics labs designed to give students the opportunity to work together and explore key concepts. While the course has been built so that each microlearning topic builds on the previous, it can be rearranged to accommodate any instructor’s particular needs.
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Definitions of Statistics, Probability, and Key Terms

Data, Sampling, and Variation in Data and Sampling

Frequency, Frequency Tables, and Levels of Measurement

Experimental Design and Ethics

Data Collection Experiment

Sampling Experiment
 Final Assessment

StemandLeaf Graphs (Stemplots), Line Graphs, and Bar Graphs

Histograms, Frequency Polygons, and Time Series Graphs

Measures of the Location of the Data

Box Plots

Measures of the Center of the Data

Skewness and the Mean, Median, and Mode <– TRY ONE!

Measures of the Spread of the Data

Descriptive Statistics
 Final Assessment

Terminology

Independent and Mutually Exclusive Events

Two Basic Rules of Probability

Contingency Tables

Tree and Venn Diagrams

Probability Topics
 Final Assessment

Probability Distribution Function (PDF) for a Discrete Random Variable

Mean or Expected Value and Standard Deviation

Binomial Distribution

Geometric Distribution

Hypergeometric Distribution

Poisson Distribution

Discrete Distribution (Playing Card Experiment)

Discrete Distribution (Lucky Dice Experiment)
 Final Assessment

Continuous Probability Functions

The Uniform Distribution

The Exponential Distribution

Continuous Distribution
 Final Assessment

The Standard Normal Distribution

Using the Normal Distribution

Normal Distribution (Lap Times)

Normal Distribution (Pinkie Length)
 Final Assessment

The Central Limit Theorem for Sample Means (Averages)

The Central Limit Theorem for Sums

Using the Central Limit Theorem

Central Limit Theorem (Pocket Change)

Central Limit Theorem (Cookie Recipes)
 Final Assessment

A Single Population Mean using the Normal Distribution

A Single Population Mean using the Student t Distribution

A Population Proportion

Confidence Interval (Home Costs)

Confidence Interval (Place of Birth)

Confidence Interval (Women’s Heights)
 Final Assessment

Null and Alternative Hypotheses

Outcomes and the Type I and Type II Errors

Distribution Needed for Hypothesis Testing

Rare Events, the Sample, Decision and Conclusion

Additional Information and Full Hypothesis Test Examples

Hypothesis Testing of a Single Mean and Single Proportion
 Final Assessment

Two Population Means with Unknown Standard Deviations

Two Population Means with Known Standard Deviations

Comparing Two Independent Population Proportions

Matched or Paired Samples

Hypothesis Testing for Two Means and Two Proportions
 Final Assessment

Facts About the ChiSquare Distribution

GoodnessofFit Test

Test of Independence

Test for Homogeneity

Comparison of the ChiSquare Tests

Test of a Single Variance

Lab 1: ChiSquare GoodnessofFit

Lab 2: ChiSquare Test of Independence
 Final Assessment

Linear Equations

Scatter Plots

The Regression Equation

Testing the Significance of the Correlation Coefficient

Prediction

Outliers

Regression (Distance from School)

Regression (Textbook Cost)

Regression (Fuel Efficiency)
 Final Assessment

OneWay ANOVA

The F Distribution and the FRatio

Facts About the F Distribution

Test of Two Variances

Lab: OneWay ANOVA
 Final Assessment
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