Solution Manual for Understanding Basic Statistics, 8th Edition, Charles Henry Brase, Corrinne Pellillo Brase

1. GETTING STARTED.

What Is Statistics? Random Samples. Introduction to Experimental Design.

2. ORGANIZING DATA.

Frequency Distributions, Histograms, and Related Topics. Bar Graphs, Circle Graphs, and Time-Series Graphs. Stem-and-Leaf Displays.

3. AVERAGES AND VARIATION.

Measures of Central Tendency: Mode, Median, and Mean. Measures of Variation. Percentiles and Box-and-Whisker Plots.

4. CORRELATION AND REGRESSION.

Scatter Diagrams and Linear Correlation. Linear Regression and the Coefficient of Determination.

5. ELEMENTARY PROBABILITY THEORY.

What Is Probability? Some Probability Rules-Compound Events. Trees and Counting Techniques.

6. THE BINOMIAL DISTRIBUTION AND RELATED TOPICS.

Introduction to Random Variables and Probability Distributions. Binomial Probabilities. Additional Properties of the Binomial Distribution.

7. NORMAL CURVES AND SAMPLING DISTRIBUTIONS.

Part I: Graphs of Normal Probability Distributions. Standard Units and Areas under the Standard Normal Distribution. Areas Under Any Normal Curve. Part II: Sampling Distributions. The Central Limit Theorem. Normal Approximation to Binomial Distribution and to p ^ Distribution.

8. ESTIMATION.

Estimating µ When s Is Known. Estimating µ When s Is Unknown. Estimating p in the Binomial Distribution.

9. HYPOTHESIS TESTING.

Introduction to Statistical Tests. Testing the Mean µ. Testing a Proportion p.

10. INFERENCES ABOUT DIFFERENCES.

Tests Involving Paired Differences (Dependent Samples). Inferences about the Difference of Two Means µ1 – µ2. Inferences about the Difference of Two Proportions p1 – p2.

11. ADDITIONAL TOPICS USING INFERENCE.

Part I: Inferences Using the Chi-Square Distribution.

Overview of the Chi-Square Distribution. Chi-Square: Tests of Independence and of Homogeneity. Chi-Square: Goodness of Fit. Testing a Single Variance or Standard Deviation.

Part II: Inferences Relating to Linear Regression.

Inferences for Correlation and Regression.