Includes index.

Previous ed.: 2001.

Text on lining papers.

Now revised with updated exercises, Johnson and Bhattacharyya's Fifth Edition of Statistics: Principles and Applications once again offers an easy to read, easy to understand introduction to statistics. The authors use real world examples, fresh hands on exercises, and crystal clear explanations to motivate students to explore the powerful ideas of modern statistics. Exercises and data sets are updated throughout for currency. Each major section and chapter in the text ends with a set of exercises that provides students with the opportunity to practice the ideas they just learned. Data sets are available on the book's website. A wide variety of timely example applications throughout the text connect statistics to real life problems. Extended Statistics in Context examples reveal the value of understanding statistics. This Fifth Edition features new screen shots and keystrokes for MINITAB, Excel, and TI 83 integrated into the text examples, as appropriate, as well as new technology manuals for MINITAB, Excel, and TI 83 on the book's website. It adopts a student friendly approach. Featuring an engaging writing style with easy to follow explanations, this text makes statistics accessible to students from a wide range of disciplines. Johnson and Bhattacharyya help students understand the meaning behind key statistical methods, appreciate the underlying logic of statistics, and recognize the possible pitfalls of statistical analysis.

1. Introduction. 1. What is Statistics? 2. Statistics in Our Everyday Life. 3. Statistics in Aid of Scientific Inquiry. 4. Two Basic Concepts- Population and Sample. 5. The Purposeful Collection of Data. 6. Statistics in Context. 7. Objectives of Statistics. 8. Review Exercises. 2. Organization and Description of Data. 1. Introduction. 2. Main Types of Data. 3. Describing Data by Tables and Graphs. 4. Measures of Center. 5. Measures of Variation. 6. Checking the Stability of the Observations over Time. 7. More on Graphics. 8. Statistics in Context. 9. Review Exercises. 3. Descriptive Study of Bivariate Data. 1. Introduction. 2. Summarization of Bivariate Categorical Data. 3. A Designed Experiment for Making a Comparison. 4. Scatter Diagram of Bivariate Measurement Data. 5. The Correlation Coefficient- A Measure of Linear Relation. 6. Prediction of One Variable from Another (Linear Regression). 7. Review Exercises. 4. Probability. 1. Introduction. 2. Probability of an Event. 3. Methods of Assigning Probability. 4. Event Relations and Two Laws of Probability. 5. Conditional Probability and Independence. 6. Random Sampling from a Finite Population. 7. Review Exercises. 5. Probability Distributions. 1. Introduction. 2. Random Variables. 3. Probability Distribution of a Discrete Random Variable. 4. Expectation (Mean) and Standard Deviation of a Probability Distribution. 5. Success and Failures- Bernoulli Trials. 6. The Binomal Distribution. 7. The Binomal Distribution in Context. 8. Review Exercises. 6. The Normal Distribution. 1. Probability Model for a Continuous Random Variable. 2. The Normal Distribution-Its General Features. 3. The Standard Normal Distribution. 4. Probability Calculations with Normal Distributions. 5. The Normal Approximation to the Binomial. 6. Checking the Plausibility of a Normal Model. 7. Transf