"Statistical Methods, 3/e" provides students with a working introduction to statistical methods offering a wide range of applications that emphasize the quantitative skills useful across many academic disciplines. This text takes a classic approach emphasizing concepts and techniques for working out problems and interpreting results. The book includes research projects, real-world case studies, numerous examples and data exercises organized by level of difficulty. This text requires that a student be familiar with algebra. New to this edition include the following: new expansion of exercises applying different techniques and methods; new examples and datasets using current real-world data; new text organization to create a more natural connection between regression and the Analysis of the Variance; new material on generalized linear models; new expansion of nonparametric techniques; new student research projects; and, new case studies for gathering, summarizing, and analyzing data. Supplements include the following: New companion website with downloadable data sets and additional resources including live links to statistical software such as SAS and SPSS; Student Solutions Manual; and, Instructor Manual. This title integrates the classical conceptual approach with modern day computerized data manipulation and computer applications. It is accessible to students who may not have a background in probability or calculus. It offers reader-friendly exposition, without sacrificing statistical rigor. It includes many new data sets in various applied fields such as Psychology, Education, Biostatistics, Agriculture, and Economics.
Preface
Chapter 1 Data and Statistics 1
1.1 Introduction 1
1.1.1 Data Sources 4
1.1.2 Using the Computer 5
1.2 Observations and Variables 6
1.3 Types of Measurements for Variables 10
1.4 Distributions 12
1.4.1 Graphical Representation of Distributions 14
1.5 Numerical Descriptive Statistics 19
1.5.1 Location 20
1.5.2 Dispersion 23
1.5.3 Other Measures 29
1.5.4 Computing the Mean and Standard Deviation from a Frequency Distribution 30
1.5.5 Change of Scale 31
1.6 Exploratory Data Analysis 32
1.6.1 The Stem and Leaf Plot 33
1.6.2 The Box Plot 34
1.6.3 Comments 37
1.7 Bivariate Data 39
1.7.1 Categorical Variables 39
1.7.2 Categorical and Interval Variables 41
1.7.3 Interval Variables 42
1.8 Populations, Samples, and Statistical Inference---A Preview 43
1.9 Data Collection 44
1.10 Chapter Summary 46
Summary 50
1.11 Chapter Exercises 51