An introduction to statistical concepts

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Title:

Author:

Lomax, Richard G.

ISBN:

9780415880053

Personal Author:

Lomax, Richard G.

Edition:

3rd ed.

Publication Information:

New York : Routledge, c2012.

Physical Description:

xvii, 822 p. : ill. ; 26 cm.

General Note:

Formerly CIP.

Contents:

Machine generated contents note: 1.Introduction -- 1.1.What Is the Value of Statistics? -- 1.2.Brief Introduction to History of Statistics -- 1.3.General Statistical Definitions -- 1.4.Types of Variables -- 1.5.Scales of Measurement -- 1.6.Summary -- Problems -- 2.Data Representation -- 2.1.Tabular Display of Distributions -- 2.2.Graphical Display of Distributions -- 2.3.Percentiles -- 2.4.SPSS -- 2.5.Templates for Research Questions and APA-Style Paragraph -- 2.6.Summary -- Problems -- 3.Univariate Population Parameters and Sample Statistics -- 3.1.Summation Notation -- 3.2.Measures of Central Tendency -- 3.3.Measures of Dispersion -- 3.4.SPSS -- 3.5.Templates for Research Questions and APA-Style Paragraph -- 3.6.Summary -- Problems -- 4.Normal Distribution and Standard Scores -- 4.1.Normal Distribution -- 4.2.Standard Scores -- 4.3.Skewness and Kurtosis Statistics -- 4.4.SPSS -- 4.5.Templates for Research Questions and APA-Style Paragraph -- 4.6.Summary -- Problems --

Contents note continued: 5.Introduction to Probability and Sample Statistics -- 5.1.Brief Introduction to Probability -- 5.2.Sampling and Estimation -- 5.3.Summary -- Appendix: Probability That at Least Two Individuals Have the Same Birthday -- Problems -- 6.Introduction to Hypothesis Testing: Inferences About a Single Mean -- 6.1.Types of Hypotheses -- 6.2.Types of Decision Errors -- 6.3.Level of Significance (α) -- 6.4.Overview of Steps in Decision-Making Process -- 6.5.Inferences About μ When σ Is Known -- 6.6.Type II Error (β) and Power (1 -- β) -- 6.7.Statistical Versus Practical Significance -- 6.8.Inferences About μ When σ Is Unknown -- 6.9.SPSS -- 6.10.G*Power -- 6.11.Template and APA-Style Write-Up -- 6.12.Summary -- Problems -- 7.Inferences About the Difference Between Two Means -- 7.1.New Concepts -- 7.2.Inferences About Two Independent Means -- 7.3.Inferences About Two Dependent Means -- 7.4.SPSS -- 7.5.G*Power --

Contents note continued: 7.6.Template and APA-Style Write-Up -- 7.7.Summary -- Problems -- 8.Inferences About Proportions -- 8.1.Inferences About Proportions Involving Normal Distribution -- 8.2.Inferences About Proportions Involving Chi-Square Distribution -- 8.3.SPSS -- 8.4.G*Power -- 8.5.Template and APA-Style Write-Up -- 8.6.Summary -- Problems -- 9.Inferences About Variances -- 9.1.New Concepts -- 9.2.Inferences About Single Variance -- 9.3.Inferences About Two Dependent Variances -- 9.4.Inferences About Two or More Independent Variances (Homogeneity of Variance Tests) -- 9.5.SPSS -- 9.6.Template and APA-Style Write-Up -- 9.7.Summary -- Problems -- 10.Bivariate Measures of Association -- 10.1.Scatterplot -- 10.2.Covariance -- 10.3.Pearson Product-Moment Correlation Coefficient -- 10.4.Inferences About Pearson Product-Moment Correlation Coefficient -- 10.5.Assumptions and Issues Regarding Correlations -- 10.6.Other Measures of Association -- 10.7.SPSS -- 10.8.G*Power --

Contents note continued: 10.9.Template and APA-Style Write-Up -- 10.10.Summary -- Problems -- 11.One-Factor Analysis of Variance: Fixed-Effects Model -- 11.1.Characteristics of One-Factor ANOVA Model -- 11.2.Layout of Data -- 11.3.ANOVA Theory -- 11.4.ANOVA Model -- 11.5.Assumptions and Violation of Assumptions -- 11.6.Unequal n's or Unbalanced Procedure -- 11.7.Alternative ANOVA Procedures -- 11.8.SPSS and G*Power -- 11.9.Template and APA-Style Write-Up -- 11.10.Summary -- Problems -- 12.Multiple Comparison Procedures -- 12.1.Concepts of Multiple Comparison Procedures -- 12.2.Selected Multiple Comparison Procedures -- 12.3.SPSS -- 12.4.Template and APA-Style Write-Up -- 12.5.Summary -- Problems -- 13.Factorial Analysis of Variance: Fixed-Effects Model -- 13.1.Two-Factor ANOVA Model -- 13.2.Three-Factor and Higher-Order ANOVA -- 13.3.Factorial ANOVA With Unequal n's -- 13.4.SPSS and G*Power -- 13.5.Template and APA-Style Write-Up -- 13.6.Summary -- Problems --

Contents note continued: 14.Introduction to Analysis of Covariance: One-Factor Fixed-Effects Model With Single Covariate -- 14.1.Characteristics of the Model -- 14.2.Layout of Data -- 14.3.ANCOVA Model -- 14.4.ANCOVA Summary Table -- 14.5.Partitioning the Sums of Squares -- 14.6.Adjusted Means and Related Procedures -- 14.7.Assumptions and Violation of Assumptions -- 14.8.Example -- 14.9.ANCOVA Without Randomization -- 14.10.More Complex ANCOVA Models -- 14.11.Nonparametric ANCOVA Procedures -- 14.12.SPSS and G*Power -- 14.13.Template and APA-Style Paragraph -- 14.14.Summary -- Problems -- 15.Random- and Mixed-Effects Analysis of Variance Models -- 15.1.One-Factor Random-Effects Model -- 15.2.Two-Factor Random-Effects Model -- 15.3.Two-Factor Mixed-Effects Model -- 15.4.One-Factor Repeated Measures Design -- 15.5.Two-Factor Split-Plot or Mixed Design -- 15.6.SPSS and G*Power -- 15.7.Template and APA-Style Write-Up -- 15.8.Summary -- Problems --

Contents note continued: 16.Hierarchical and Randomized Block Analysis of Variance Models -- 16.1.Two-Factor Hierarchical Model -- 16.2.Two-Factor Randomized Block Design for n = 1 -- 16.3.Two-Factor Randomized Block Design for n > 1 -- 16.4.Friedman Test -- 16.5.Comparison of Various ANOVA Models -- 16.6.SPSS -- 16.7.Template and APA-Style Write-Up -- 16.8.Summary -- Problems -- 17.Simple Linear Regression -- 17.1.Concepts of Simple Linear Regression -- 17.2.Population Simple Linear Regression Model -- 17.3.Sample Simple Linear Regression Model -- 17.4.SPSS -- 17.5.G*Power -- 17.6.Template and APA-Style Write-Up -- 17.7.Summary -- Problems -- 18.Multiple Regression -- 18.1.Partial and Semipartial Correlations -- 18.2.Multiple Linear Regression -- 18.3.Methods of Entering Predictors -- 18.4.Nonlinear Relationships -- 18.5.Interactions -- 18.6.Categorical Predictors -- 18.7.SPSS -- 18.8.G*Power -- 18.9.Template and APA-Style Write-Up -- 18.10.Summary -- Problems --

Contents note continued: 19.Logistic Regression -- 19.1.How Logistic Regression Works -- 19.2.Logistic Regression Equation -- 19.3.Estimation and Model Fit -- 19.4.Significance Tests -- 19.5.Assumptions and Conditions -- 19.6.Effect Size -- 19.7.Methods of Predictor Entry -- 19.8.SPSS -- 19.9.G*Power -- 19.10.Template and APA-Style Write-Up -- 19.11.What Is Next? -- 19.12.Summary -- Problems.

Subject Term:

Statistics.

Mathematical statistics.

Added Author:

Hahs-Vaughn, Debbie L.

Copies:

Available:*

Library	Material Type	Item Barcode	Shelf Number	Copy	Status
Searching... 1:IIEMSA	1:GEN-BOOK	23168001673647	519.5 L839.I 2012	1	Searching... Unknown

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Summary

This comprehensive, flexible text is used in both one- and two-semester courses to review introductory through intermediate statistics. Instructors select the topics that are most appropriate for their course. Its conceptual approach helps students more easily understand the concepts and interpret SPSS and research results. Key concepts are simply stated and occasionally reintroduced and related to one another for reinforcement. Numerous examples demonstrate their relevance. This edition features more explanation to increase understanding of the concepts. Only crucial equations are included.

In addition to updating throughout, the new edition features:

New co-author, Debbie L. Hahs-Vaughn, the 2007 recipient of the University of Central Florida's College of Education Excellence in Graduate Teaching Award. A new chapter on logistic regression models for today's more complex methodologies. More on computing confidence intervals and conducting power analyses using G*Power. Many more SPSS screenshots to assist with understanding how to navigate SPSS and annotated SPSS output to assist in the interpretation of results. Extended sections on how to write-up statistical results in APA format. New learning tools including chapter-opening vignettes, outlines, and a list of key concepts, many more examples, tables, and figures, boxes, and chapter summaries. More tables of assumptions and the effects of their violation including how to test them in SPSS. 33% new conceptual, computational, and all new interpretative problems. A website that features PowerPoint slides, answers to the even-numbered problems, and test items for instructors, and for students the chapter outlines, key concepts, and datasets that can be used in SPSS and other packages, and more.

Each chapter begins with an outline, a list of key concepts, and a vignette related to those concepts. Realistic examples from education and the behavioral sciences illustrate those concepts. Each example examines the procedures and assumptions and provides instructions for how to run SPSS, including annotated output, and tips to develop an APA style write-up. Useful tables of assumptions and the effects of their violation are included, along with how to test assumptions in SPSS. 'Stop and Think' boxes provide helpful tips for better understanding the concepts. Each chapter includes computational, conceptual, and interpretive problems. The data sets used in the examples and problems are provided on the web. Answers to the odd-numbered problems are given in the book.

The first five chapters review descriptive statistics including ways of representing data graphically, statistical measures, the normal distribution, and probability and sampling. The remainder of the text covers inferential statistics involving means, proportions, variances, and correlations, basic and advanced analysis of variance and regression models. Topics not dealt with in other texts such as robust methods, multiple comparison and nonparametric procedures, and advanced ANOVA and multiple and logistic regression models are also reviewed.

Intended for one- or two-semester courses in statistics taught in education and/or the behavioral sciences at the graduate and/or advanced undergraduate level,nbsp;knowledge ofnbsp;statistics is not a prerequisite. A rudimentary knowledge of algebra is required.