Understanding Basic Statistics - 5th edition

Charles Brase has more than 30 years of full-time teaching experience in mathematics and statistics. He taught at the University of Hawaii, Manoa Campus, for several years and at Regis University in Denver, Colorado, for more than 28 years. Charles received the Excellence in Teaching award from the University of Hawaii and the Faculty Member of the Year from Regis University on two occasions. He earned degrees from the University of Colorado, Boulder, and has a Ph.D. in Mathematics, an M.A. in Mathematics, and a B.A. in Physics.

Corrinne has taught at Hawaii Pacific College, Honolulu Community College, and Arapahoe Community College in Littleton, Colorado. She was also involved in the mathematics component of an equal opportunity program at the University of Colorado. Corrinne received the Faculty of the Year award from Arapahoe Community College. She earned degrees from the University of Colorado, Boulder, and has an M.A. and B.A. in Mathematics.

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 PROBABILITY 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. Graphs and Normal Probability Distributions. Standard Units and Areas Under the Standard Normal Distribution. Areas Under Any Normal Curve. Sampling Distributions. The Central Limit Theorem. Normal Approximation to the Binomial Distribution. 8. ESTIMATION. Estimating µ When ? Is Known. Estimating µ When ? is Unknown. Estimating p in a Binomial Distribution. 9. HYPOTHESIS TESTING. Introduction to Statistical Tests. Testing the Mean µ. Testing a Proportion p. 10. INFERNECES 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. Chi-Square: Tests of Independence and of Homogeneity. Chi-Square: Goodness of Fit. Testing and Estimating a Single Variance or Standard Deviation. Inferences for Correlation and Regression.