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About this book
This book provides a vivid and meaningful introduction to statistics. The principles of both descriptive and inferential statistics are illustrated in situations that are close to students' own experience. The authors provide illustrations and exercises drawn from disciplines as varied as sociology, education, business, sports, demography, meteorology, politics, and mathematics. -- New "Real Stat" boxes with fascinating, and often humorous, applications of statistical methods scattered throughout each chapter -- New "drill" and regular exercises -- A data set on schools at the end of every chapter -- A new chapter on quality control with real-life applications -- Minitab "RM" session commands throughout the text -- A new section on the uses and abuses of statistics -- Each chapter begins with a set of "Learning Objectives" that motivates students and helps them to organize the material. -- Following the "Learning Objectives" is a chapter-opening problem that is continued throughout the chapter and is solved within discussion of applicable concepts. -- A "Unit Review" after each group of six chapters helps students study for tests. -- Every important term is defined and placed in a box for easy reference. -- Each text discussion is followed by a realistic problem and solution. -- Each chapter is interspersed with "Self Reviews".
Contents
Part 1 An introduction to statistics: Who Else Uses Statistics? Graphic Presentation of Data. Types of Statistics. Types of Variables. Levels of Measurement. Uses and Abuses of Statistics. A Word of Encouragement. Computer Applications. Part 2 Summarizing data - frequency distributions and graphic presentations: Frequency Distributions. Stem-and-Leaf Charts. Portraying the Frequency Distributions Graphically. Misuses of Charts and Graphs. Part 3 Descriptive statistics - measures of central tendency: The Sample Mean. The Population Mean. Properties of the Arithmetic Mean. The Weighted Arithmetic Mean. The Median. The Mode. Choosing an Average. Estimating the Arithmetic Mean from Grouped Data. Estimating the Median from Grouped Data. Estimating the Mode from Grouped Data. Choosing an Average for Data in a Frequency Distribution. Part 4 Descriptive statistics - measures of dispersion and skewness. Measures of Dispersion for Raw Data. Measures of Dispersion for Grouped Data. Interpreting and Using the Standard Deviation. Box Plots. Relative Dispersion. The Coefficient of Skewness. Software Example. Part 5 An introduction to probability: Concepts of Probability. Types of Probability. Classical Concept of Probablity. Probability Rules. Some Counting Principles. Part 6 Probability distributions: What is a Probability Distribution? Discrete and Continuous Random Variables. The Mean and Variance of a Probability Distribution. The Binomial Probability Distribution. The Poisson Probability Distribution. Part 7 The normal probability distribution: Characteristics of a Normal Probability Distribution. The "Family" of Normal Distributions. The Standard Normal Probability Distribution. The Normal Approximation to the Binomial. The Normal Approximation to the Poisson Distribution. Part 8 Sampling methods and sampling distributions: Designing the Sample Survey or Experiment. Methods of Probability Sampling. The Sampling Error. The Sampling Distribution of the Sample Mean. Part 9 The central limit theorem and confidence intervals: The Central Limit Theorem. Confidence Intervals for Means. The Standard Error of the Sample Mean. The Standard Error of the Sample Proportion. Confidence Intervals for Proportions. The Finite Population Correction Factor. Choosing an Appropriate Sample Size. Part 10 Hypothesis tests - large-sample methods: The General Idea of Hypothesis Testing. A Test Involving the Population Mean (Large Samples.) A Test for Two Population Means (Large Samples.) A Test Involving the Population Proportion (Large Samples). A Test Involving Two Population Proportions (Large Samples). Part 11 Hypothesis tests - small-sample method: Characteristics of the T Distribution. Testing a Hypothesis about a Population Mean. Comparing Two Population Means. Testing with Dependent Observations. Comparing Dependent and Independent Samples.
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