# Statistics

A Statistics course is required at the college level for completion of requirements in a surprisingly large number of fields of study that seem to vary widely. Topics in Statistics include the study of various “averages” and standard deviation and extend into probability, various sampling distributions, estimating using confidence intervals, and hypothesis testing. Special emphasis is given to real world applications. The graphing calculator is used extensively.

• 1.1  What Is Statistics?
• 1.2  Random Samples
• 1.3  Introduction to Experimental Design
• 2.1  Frequency Distributions, Histograms, and Related Topics
• 2.2  Bar Graphs, Circle Graphs, and Time-Series Graphs
• 2.3  Stem-and-Leaf Displays
• 3.1  Measures of Central Tendency: Mode, Median, and Mean
• 3.2  Measures of Variation
• 3.3  Percentiles and Box-and-Whisker Plots
• 4.1  Scatter Diagrams and Linear Correlation
• 4.2  Linear Regression and the Coefficient of Determination
• 5.1  What Is Probability
• 5.2  Some Probability Rules – Compound Events
• 5.3  Tree Diagrams and Counting Techniques
• 6.1  Introduction to Random Variables and Probability Distributions
• 6.2  Binomial Probabilities
• 6.3  Additional Properties of the Binomial Distribution
• 7.1  Graphs of Normal Probability Distributions
• 7.2  Standard Units and Areas Under the Standard Normal Distribution
• 7.3  Areas Under Any Normal Curve
• 7.4  Sampling Distributions
• 7.5  The Central Limit Theorem
• 7.6  Normal Approximations to the Binomial Distribution
• 8.1  Estimating μ When σ Is Known
• 8.2  Estimating μ When σ Is Unknown
• 8.3  Estimating p in the Binomial Distribution
• 9.1  Introduction to Statistical Tests
• 9.2  Testing the Mean μ
• 9.3  Testing a Proportion p
• 10.1  Tests Involving Paired Differences (Dependent Samples)
• 10.2  Inferences About the Difference of Two Means μ1 – μ2
• 10.3  Inferences About the Difference of Two Proportions p1 – p2
• 11.1  Chi-Square: Tests of Independence and of Homogeneity
• 11.2  Chi-Square: Goodness of Fit
• 11.3  Testing a Single Variance or Standard Deviation
• 11.4  Inferences for Correlation and Regression

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