Statistics for the Utterly Confused, Second Edition

When it comes to understanding statistics, even good students can be confused. Perfect for students in any introductory non-calculus-based statistics course, and equally useful to professionals working in the world, Statistics for the Utterly Confused is your ticket to success. Statistical concepts are explained step-by-step and applied to such diverse fields as business, economics, finance, and more.

The message of Statistics for the Utterly Confused is simple: you don't have to be confused anymore. Updated and expanded to give you the latest changes in the field, this up-to-the-minute edition includes many new examples of Excel output, the most widely used of all statistics programs; a new chapter on Analysis of Variance (ANOVA); and 200 additions to the 700 self-testing questions and answers. The expert author's Web site also gives you tons of fresh examples, practice problems, and strategies--so you can go from utterly confused to totally prepared in no time!

Inside, you'll discover how to:

• Grasp the meaning of everyday statistical concepts
• Find out what's probable and what isn't
• Read, understand, and solve statistics problems
• Improve your scores on exams
• Use your skills in any field

Lloyd R. Jaisingh, Ph.D., is Professor of Mathematics at Morehead State University, Morehead, Kentucky. He has taught statistics for the past thirteen years at Morehead State University, and has published several articles in applied statistics as well as books dealing with elementary statistics and the use of technology in the classroom. He has received a number of grants and fellowships, and an award as Outstanding Researcher of the Year at Morehead State.

Part I: Descriptive Statistics
1. Graphical Displays
2. Numerical Measures of Central Tendency
3. Numerical Measures of Variability
4. Numerical Measures of Positions
5. Exploring Bivariate Data
6. Exploring Categorical Data
Part II: Probability
7. Randomness, Uncertainty, and Probability
8. Discrete Probability Distributions
9. The Normal Probability Distribution
10. Sampling Distributions and the Central Limit Theorem
Part III: Statistical Inference
11. Confidence Intervals: Large Samples
12. Hypothesis Tests: Large Samples
13. Confidence Intervals and Hypothesis Tests: Small Samples
14. Chi-Square Procedures
15. One-Way Analysis of Variance