In their own classrooms, through their popular texts, and in the conferences they lead, Bob Johnson and Pat Kuby have inspired hundreds of thousands of students and their instructors to see the utility and practicality of statistics. Robert Johnson and Patricia Kuby's ELEMENTARY STATISTICS, Tenth Edition has been consistently praised by users and reviewers for its clear exposition and relevant examples, exercises, and applications. Technology enhancements include the addition of Video Skillbuilders and StatisticsNow™ (part of the CengageNOW suite of technology products), our personalized online learning companion. This increased focus on technology to help students succeed, along with the wealth of instructor supplements and flexibility of technology coverage (with MINITAB, Excel, and TI-83 output and instructions throughout) clearly differentiate this text from its competitors as the most accessible text for students to learn from and the most straightforward text for instructors to teach from.
This edition is the first 11 chapters of the parent book Elementary Statistics 10e.
Table of Contents
Part I: DESCRIPTIVE STATISTICS.
Americans, Here''s Looking At You. What is Statistics? Measurability and Variability. Data Collection. Comparison of Probability and Statistics. Statistics and Technology.
2. Descriptive Analysis and Presentation of Single-Variable Data.
You and the Internet. Graphical Presentation of Data. Graphs, Pareto Diagrams, and Stem-And-Leaf Displays. Frequency Distributions and Histograms. Numerical Descriptive Statistics. Measures of Central Tendency. Measures of Dispersion. Measures of Position. Interpreting and Understanding Standard Deviation. The Art of Statistical Deception. Mean and Standard Deviation of Frequency Distribution (Optional).
3. Descriptive Analysis and Presentation of Bivariate Data.
The Kid is All Grown Up. Bivariate Data. Linear Correlation. Linear Regression.
Part II: PROBABILITY.
Sweet Statistics. Probability of Events. Conditional Probability of Events. Rules of Probability. Mutually Exclusive Events. Independent Events. Mutually Exclusive, Independent Events—A Relationship?
5. Probability Distributions (Discrete Variables).
Caffeine Drinking. Random Variables. Probability Distribution of a Discrete Random Variable. Mean and Variance of a Discrete Probability Distribution. The Binomial Probability Distribution. Mean and Standard Deviation of the Binomial Distribution.
6. Normal Probability Distributions.
Intelligence Scores. Normal Probability Distributions. The Standard Normal Distribution. Applications of Normal Distributions. Notation. Normal Approximation of the Binomial.
7. Sample Variability.
275 Million Americans. Sampling Distributions. The Sampling Distribution of Sample Means. Application of the Sampling Distribution of Sample Means.
Part III: INFERENTIAL STATISTICS.
8. Introduction to Statistical Inferences.
Were They Shorter Back Then? The Nature of Estimation. Estimation of a Mean (ó known). The Nature of Hypothesis Testing. Hypothesis Test of Mean ì (ó Known): A Probability Value Approach. Hypothesis Test of Mean ì (ó Known): A Classical Approach.
9. Inferences Involving One Population.
Get Enough Daily Exercise? Inferences About Mean ì (ó Unknown). Inferences About the Binomial Probability of Success. Inferences About Variance and Standard Deviation.
10. Inferences Involving Two Populations.
Students, Credit Cards and Debt. Independent and Dependent Samples. Inferences Concerning the Mean Difference Using Two Dependent Samples. Inferences Concerning the Difference Between Means Using Two Independent Samples. Inferences Concerning the Difference Between Proportions Using Two Independent Samples. Inferences Concerning the Ratio of Variances Using Two Independent Samples.
Part IV: MORE INFERENTIAL STATISTICS.
11. Applications of Chi-Square.
Cooling a Great Hot Taste. Chi-Square Statistic. Inferences Concerning Multinomial Experiments. Inferences Concerning Contingency Tables.