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Fundamental Statistics for the Behavioral Sciences (8th edition)

Download Fundamental Statistics for the Behavioral Sciences (8th edition) written by David C. Howell in PDF format. This book is under the category Mathematics and bearing the isbn/isbn13 number 1285076915/9781285076911. You may reffer the table below for additional details of the book.

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Specifications

book-author

David C. Howell

publisher

Cengage Learning; 8th edition (February 19; 2013)

file-type

PDF

pages

672 pages

language

English

asin

B00BSJAQQU

isbn10

1285076915

isbn13

9781285076911


Book Description

Fundamental Statistics For The Behavioral Sciences 8th edition focuses on providing the context of statistics in behavioral research; while emphasizing the importance of looking at data before jumping into a test. This practical approach provides readers and students with an understanding of the logic behind the statistics; so they understand how and why certain methods are used — rather than simply carry out techniques by rote. Readers move beyond number crunching to discover the meaning of statistical results and appreciate how the statistical test to be employed relates to the research questions posed by an experiment. An abundance of real data and research studies provide a real-life perspective and help you understand concepts as you learn about the analysis of data.

book-author

David C. Howell

publisher

Cengage Learning; 8th edition (February 19; 2013)

file-type

PDF

pages

672 pages

language

English

asin

B00BSJAQQU

isbn10

1285076915

isbn13

9781285076911

Table of contents


Table of contents :
Cover
……Page 1
Title Page
……Page 7
Copyright
……Page 8
Brief Contents……Page 10
Contents……Page 11
Preface……Page 15
Ch 1: Introduction……Page 23
1.1: A Changing Field……Page 25
1.2: The Importance of Context……Page 26
1.3: Basic Terminology……Page 28
1.4: Selection among Statistical Procedures……Page 32
1.5: Using Computers……Page 34
1.6: Summary……Page 36
1.7: A Quick Review……Page 37
1.8: Exercises……Page 38
Ch 2: Basic Concepts……Page 40
2.1: Scales of Measurement……Page 41
2.2: Variables……Page 47
2.3: Random Sampling……Page 48
2.4: Notation……Page 50
2.5: Summary……Page 52
2.6: A Quick Review……Page 53
2.7: Exercises……Page 54
Ch 3: Displaying Data……Page 58
3.1: Plotting Data……Page 60
3.2: Stem-and-Leaf Displays……Page 63
3.3: Reading Graphs……Page 68
3.4: Alternative Methods of Plotting Data……Page 70
3.5: Describing Distributions……Page 73
3.6: Using Computer Programs to Display Data……Page 75
3.7: Summary……Page 76
3.8: A Quick Review……Page 77
3.9: Exercises……Page 78
Ch 4: Measures of Central Tendency……Page 84
4.2: The Median……Page 85
4.3: The Mean……Page 86
4.4: Relative Advantages and Disadvantages of the Mode, the Median, and the Mean……Page 87
4.5: Obtaining Measures of Central Tendency Using SPSS……Page 90
4.6: A Simple Demonstration – Seeing Statistics……Page 92
4.7: Summary……Page 95
4.9: Exercises……Page 96
Ch 5: Measures of Variability……Page 100
5.1: Range……Page 103
5.2: Interquartile Range and Other Range Statistics……Page 104
5.3: The Average Deviation……Page 105
5.4: The Variance……Page 106
5.5: The Standard Deviation……Page 108
5.6: Computational Formulae for the Variance and the Standard Deviation……Page 109
5.7: The Mean and the Variance as Estimators……Page 110
5.8: Boxplots: Graphical Representations of Dispersion and Extreme Scores……Page 112
5.9: A Return to Trimming……Page 116
5.10: Obtaining Measures of Dispersion Using SPSS……Page 118
5.11: The Moon Illusion……Page 119
5.12: Seeing Statistics……Page 122
5.13: Summary……Page 123
5.15: Exercises……Page 125
Ch 6: The Normal Distribution……Page 129
6.1: The Normal Distribution……Page 132
6.2: The Standard Normal Distribution……Page 136
6.3: Setting Probable Limits on an Observation……Page 142
6.4: Measures Related to z……Page 144
6.5: Seeing Statistics……Page 145
6.6: Summary……Page 146
6.8: Exercises……Page 147
Ch 7: Basic Concepts of Probability……Page 151
7.1: Probability……Page 152
7.2: Basic Terminology and Rules……Page 155
7.3: The Application of Probability to Controversial Issues……Page 160
7.4: Writing Up the Results……Page 163
7.5: Discrete versus Continuous Variables……Page 164
7.6: Probability Distributions for Discrete Variables……Page 165
7.7: Probability Distributions for Continuous Variables……Page 166
7.8: Summary……Page 168
7.10: Exercises……Page 170
Ch 8: Sampling Distributions and Hypothesis Testing……Page 173
8.1: Sampling Distributions and the Standard Error……Page 174
8.2: Two More Examples Involving Course Evaluations and Human Decision Making……Page 176
8.3: Hypothesis Testing……Page 179
8.4: The Null Hypothesis……Page 182
8.5: Test Statistics and Their Sampling Distributions……Page 184
8.6: Using the Normal Distribution to Test Hypotheses……Page 185
8.7: Type I and Type II Errors……Page 190
8.8: One- and Two-Tailed Tests……Page 194
8.9: Seeing Statistics……Page 198
8.10: A Final Example……Page 199
8.12: Summary……Page 201
8.13: A Quick Review……Page 202
8.14: Exercises……Page 203
Ch 9: Correlation……Page 206
9.1: Scatter Diagrams……Page 207
9.2: An Example: The Relationship between the Pace of Life and Heart Disease……Page 214
9.3: The Covariance……Page 215
9.4: The Pearson Product-Moment Correlation Coefficient (r)……Page 216
9.5: Correlations with Ranked Data……Page 218
9.6: Factors That Affect the Correlation……Page 220
9.7: Beware Extreme Observations……Page 223
9.8: Correlation and Causation……Page 225
9.9: If Something Looks Too Good to Be True, Perhaps It Is……Page 226
9.10: Testing the Significance of a Correlation Coefficient……Page 227
9.11: Intercorrelation Matrices……Page 230
9.12: Other Correlation Coefficients……Page 232
9.14: Seeing Statistics……Page 235
9.15: Does Rated Course Quality Relate to Expected Grade?……Page 238
9.16: Summary……Page 241
9.17: A Quick Review……Page 242
9.18: Exercises……Page 243
Ch 10: Regression……Page 247
10.1: The Relationship between Stress and Health……Page 249
10.3: The Regression Line……Page 251
10.4: The Accuracy of Prediction……Page 260
10.5: The Influence of Extreme Values……Page 265
10.6: Hypothesis Testing in Regression……Page 266
10.7: Computer Solution Using SPSS……Page 268
10.8: Seeing Statistics……Page 270
10.9: Course Ratings as a Function of Anticipated Grade……Page 275
10.10: Regression versus Correlation……Page 276
10.11: Summary……Page 277
10.12: A Quick Review……Page 278
10.13: Exercises……Page 279
Ch 11: Multiple Regression……Page 284
11.1: Overview……Page 286
11.2: Funding Our Schools……Page 289
11.3: Residuals……Page 300
11.4: Hypothesis Testing……Page 301
11.5: Refining the Regression Equation……Page 303
11.6: A Second Example: What Makes a Confident Mother?……Page 304
11.7: A Third Example: Psychological Symptoms in Cancer Patients……Page 307
11.8: Summary……Page 310
11.9: A Quick Review……Page 311
11.10: Exercises……Page 312
Ch 12: Hypothesis Tests Applied to Means: One Sample……Page 317
12.1: Sampling Distribution of the Mean……Page 319
12.2: Testing Hypotheses about Means When a is Known……Page 322
12.3: Testing a Sample Mean When a is Unknown……Page 326
12.5: A Second Example: The Moon Illusion……Page 332
12.6: How Large is Our Effect?……Page 333
12.7: Confidence Limits on the Mean……Page 334
12.8: Using SPSS to Run One-Sample t Tests……Page 338
12.9: A Good Guess is Better than Leaving It Blank……Page 339
12.10: Seeing Statistics……Page 342
12.11: Summary……Page 345
12.12: A Quick Review……Page 346
12.13: Exercises……Page 347
Ch 13: Hypothesis Tests Applied to Means: Two Related Samples……Page 349
13.1: Related Samples……Page 350
13.2: Student’s t Applied to Difference Scores……Page 351
13.3: The Crowd within is Like the Crowd Without……Page 354
13.4: Advantages and Disadvantages of Using Related Samples……Page 356
13.5: How Large an Effect Have We Found?……Page 357
13.6: Confidence Limits on Changes……Page 359
13.8: Writing Up the Results……Page 360
13.9: Summary……Page 361
13.10: A Quick Review……Page 362
13.11: Exercises……Page 363
Ch 14: Hypothesis Tests Applied to Means: Two Independent Samples……Page 366
14.1: Distribution of Differences between Means……Page 367
14.2: Heterogeneity of Variance……Page 375
14.4: A Second Example with Two Independent Samples……Page 377
14.5: Effect Size Again……Page 379
14.6: Confidence Limits on u1 – u2……Page 380
14.7: Plotting the Results……Page 381
14.8: Writing Up the Results……Page 382
14.10: Do Lucky Charms Work?……Page 383
14.11: Seeing Statistics……Page 388
14.12: Summary……Page 389
14.13: A Quick Review……Page 390
14.14: Exercises……Page 391
Ch 15: Power……Page 394
15.1: The Basic Concept of Power……Page 397
15.2: Factors Affecting the Power of a Test……Page 399
15.3: Calculating Power the Traditional Way……Page 402
15.4: Power Calculations for the One-Sample t Test……Page 404
15.5: Power Calculations for Differences between Two Independent Means……Page 407
15.6: Power Calculations for the t Test for Related Samples……Page 410
15.7: Power Considerations in Terms of Sample Size……Page 411
15.8: You Don’t Have to Do It by Hand……Page 412
15.9: Post-hoc (Retrospective) Power……Page 413
15.10: Summary……Page 414
15.12: Exercises……Page 415
Ch 16: One-Way Analysis of Variance……Page 418
16.1: The General Approach……Page 419
16.2: The Logic of the Analysis of Variance……Page 423
16.3: Calculations for the Analysis of Variance……Page 428
16.4: Unequal Sample Sizes……Page 435
16.5: Multiple Comparison Procedures……Page 437
16.7: The Size of the Effects……Page 446
16.8: Writing Up the Results……Page 449
16.9: The Use of SPSS for a One-Way Analysis of Variance……Page 450
16.10: A Final Worked Example……Page 451
16.11: Seeing Statistics……Page 454
16.12: Summary……Page 455
16.13: A Quick Review……Page 456
16.14: Exercises……Page 457
Ch 17: Factorial Analysis of Variance……Page 462
17.1: Factorial Designs……Page 463
17.2: The Eysenck Study……Page 466
17.3: Interactions……Page 471
17.4: Simple Effects……Page 473
17.5: Measures of Association and Effect Size……Page 475
17.6: Reporting the Results……Page 478
17.7: Unequal Sample Sizes……Page 479
17.8: Masculine Overcompensation Thesis: It’s a Male Thing……Page 480
17.9: Using SPSS for Factorial Analysis of Variance……Page 483
17.10: Seeing Statistics……Page 484
17.11: Summary……Page 485
17.12: A Quick Review……Page 486
17.13: Exercises……Page 487
Ch 18: Repeated-Measures Analysis of Variance……Page 492
18.1: An Example: Depression as a Response to an Earthquake……Page 493
18.2: Multiple Comparisons……Page 496
18.3: Effect Size……Page 498
18.5: Advantages and Disadvantages of Repeated-Measures Designs……Page 499
18.6: Using SPSS to Analyze Data in a Repeated-Measures Design……Page 500
18.7: Writing Up the Results……Page 503
18.8: A Final Worked Example……Page 504
18.9: Summary……Page 506
18.11: Exercises……Page 507
Ch 19: Chi-Square……Page 510
19.1: One Classification Variable: The Chi-Square Goodness-of-Fit Test……Page 512
19.2: Two Classification Variables: Analysis of Contingency Tables……Page 518
19.3: Possible Improvements on Standard Chi-Square……Page 520
19.4: Chi-Square for Larger Contingency Tables……Page 522
19.5: The Problem of Small Expected Frequencies……Page 523
19.6: The Use of Chi-Square as a Test on Proportions……Page 524
19.7: SPSS Analysis of Contingency Tables……Page 526
19.8: Measures of Effect Size……Page 528
19.9: A Final Worked Example……Page 533
19.11: Seeing Statistics……Page 535
19.12: Summary……Page 536
19.13: A Quick Review……Page 537
19.14: Exercises……Page 538
Ch 20: Nonparametric and Distribution-Free Statistical Tests……Page 542
20.1: The Mann-Whitney Test……Page 546
20.2: Wilcoxon’s Matched-Pairs Signed-Ranks Test……Page 553
20.3: Kruskal-Wallis One-Way Analysis of Variance……Page 558
20.4: Friedman’s Rank Test for k Correlated Samples……Page 560
20.6: Writing Up the Results……Page 562
20.7: Summary……Page 563
20.8: A Quick Review……Page 564
20.9: Exercises……Page 565
Ch 21: Meta-Analysis……Page 569
Meta-Analysis……Page 570
21.1: A Brief Review of Effect Size Measures……Page 571
21.2: An Example – Child and Adolescent Depression……Page 575
21.3: A Second Example – Nicotine Gum and Smoking Cessation……Page 581
21.4: A Quick Review……Page 584
21.5: Exercises……Page 585
Appendix A: Arithmetic Review……Page 588
Addition and Subtraction……Page 589
Parentheses……Page 590
Fractions……Page 591
Algebraic Operations……Page 592
English Letter Symbols……Page 595
Tests on Sample Means……Page 598
Correlation and Regression……Page 599
Meta-Analysis……Page 601
Appendix D: Data Set……Page 602
Appendix E: Statistical Tables……Page 606
Table E.1: Upper Percentage Points of the x2 Distribution……Page 607
Table E.2: Significant Values of the Correlation Coefficient……Page 608
Table E.3: Critical Values of the F Distribution: Alpha = .05……Page 609
Table E.4: Critical Values of the F Distribution: Alpha = .01……Page 610
Table E.5: Power as a Function of d and Significance Level (a)……Page 611
Table E.6: Percentage Points of the t Distribution……Page 612
Table E.7: Critical Lower-Tail Values of T (and Their Associated Probabilities) for Wilcoxon’s Matched-Pairs Signed-Ranks Test……Page 613
Table E.8: Critical Lower-Tail Values of Ws for the Mann-Whitney Test for Two Independent Samples (N1 < N2)……Page 614
Table E.9: Table of Uniform Random Numbers……Page 618
Table E.10: The Normal Distribution (z)……Page 620
Glossary……Page 624
References……Page 630
Answers to Exercises……Page 637
Index……Page 659

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