Fundamental Statistics for Behaviorial Science / Edition 7

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Overview

This text takes a traditional approach to teaching the basic statistical concepts and methods used in behavioral research. McCall emphasizes building an understanding of the logic of statistics rather than stressing the mechanics. Similarly, the data for computational problems has been kept simple, so students can focus on the rationale and outcome of techniques instead of the calculations themselves. Behavioral research issues are built into the problems and exercises.
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Editorial Reviews

Booknews
A textbook for a first course in applied statistics, primarily for students majoring in psychology, education, and other social and behavioral sciences. McCall (psychology, U. of Pittsburgh) emphasizes the purpose, rationale, and application of important statistical concepts over rote memorization and mechanical application of formula. Whenever possible, he explains in mathematically simple terms the logic that undergirds the concepts and techniques, though some require advanced mathematics that he requires students to take on faith for now. The eighth edition is revised somewhat according to suggestions, and adds a little new material; no dates are noted for earlier ones. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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Product Details

  • ISBN-13: 9780534523718
  • Publisher: Brooks/Cole
  • Publication date: 10/28/1997
  • Series: Psychology Series
  • Edition description: Older Edition
  • Edition number: 7
  • Pages: 512
  • Product dimensions: 7.72 (w) x 9.55 (h) x 1.02 (d)

Table of Contents

Part 1 Descriptive Statistics 1
Chapter 1 The Study of Statistics 3
Why Study Statistics? 4
Descriptive and Inferential Statistics 6
Measurement 9
Summation Sign 17
Summary 24
Chapter 2 Frequency Distributions and Graphing 28
Types of Frequency Distributions 29
Constructing Frequency Distributions with Class Intervals 34
Graphs of Frequency Distributions 40
How Distributions Differ 46
Summary 50
Chapter 3 Characteristics of Distributions 53
Indicators of Central Tendency 55
Indicators of Variability 63
Populations and Samples 69
A Note on Calculators and Computers 72
Summary 74
Chapter 4 Elements of Exploratory Data Analysis 78
Stem-and-Leaf Displays 79
Resistant Indicators 88
Summary 97
Chapter 5 Indicators of Relative Standing 100
Percentiles 101
Changing the Properties of Scales 107
Standard Scores and the Normal Distribution 113
Summary 129
Chapter 6 Regression 133
Linear Relationships 134
Regression Constants and the Regression Line 142
Standard Error of Estimate 152
Summary 158
Chapter 7 Correlation 162
The Pearson Product-Moment Correlation Coefficient 163
Properties of the Correlation Coefficient 170
Sampling Factors That Change the Correlation Coefficient 176
Causality and Correlation 183
Summary 184
Part 2 Inferential Statistics 189
Chapter 8 Sampling, Sampling Distributions, and Probability 191
Methods of Sampling 192
Sampling Distributions and Sampling Error 195
Probability and Its Application to Hypothesis Testing 204
Estimation 207
Summary 210
Chapter 9 Introduction to Hypothesis Testing: Terminology and Theory 214
Statistical Terminology 215
Hypothesis Testing When [sigma subscript x] Is Estimated by s[subscript x] 231
Summary 237
Chapter 10 Elementary Techniques of Hypothesis Testing 240
Inferences about the Difference between Means 241
Inferences about Correlation Coefficients 253
A Comparison of the Difference between Means and Correlation 260
Statistics in the Journals 263
Summary 264
Chapter 11 Beyond Hypothesis Testing: Effect Size and Interval Estimation 269
Beyond Hypothesis Testing 270
Indices of Size 273
Interval Estimation 277
Summary 291
Part 3 Special Topics 297
Chapter 12 Introduction to Research Design 299
Scientific Questions 301
Operationalizing 307
Data Collection and Data Analysis 313
Conclusions and Interpretations 314
The Research Report 314
Ethical Considerations 316
Summary 320
Chapter 13 Topics in Probability 322
Set Theory 323
Simple Classical Probability 328
Probability of Complex Events 333
Methods of Counting 340
Summary 347
Chapter 14 Simple Analysis of Variance 351
Logic of the Analysis of Variance 353
Computational Procedures 367
Comparisons between Specific Means 375
Size of Relationship 381
Summary 386
Chapter 15 Two-Factor Analysis of Variance 389
Two-Factor Classification 390
Logic of Two-Factor Analysis of Variance 394
Computational Procedures 41
Summary 420
Chapter 16 Nonparametric Techniques 424
Parametric and Nonparametric Tests 425
Tests on Independent Samples 428
Tests on Correlated Samples 446
Rank-Order Correlation 450
Summary 454
Appendix 1 Math Review 461
Appendix 2 Tables 469
Appendix 3 Symbols 490
Appendix 4 Terms 493
Appendix 5 Answers 502
Index 523
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