Statistics for the Behavioral Sciences, 10th Edition PDF by Frederick J Gravetter and Larry B. Wallnau

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Statistics for the Behavioral Sciences, 10th Edition
by Frederick J Gravetter and Larry B. Wallnau
Statistics for the Behavioral Sciences, 10th Edition

Contents

C H A P t E R 1 Introduction to Statistics 1
PREVIEW 2
1.1 Statistics, Science, and Observations 2
1.2 Data Structures, Research Methods, and Statistics 10
1.3 Variables and Measurement 18
1.4 Statistical Notation 25
Summary 29
Focus on Problem Solving 30
Demonstration 1.1 30
Problems 31
CHAP t E R 2 Frequency Distributions 33
PREVIEW 34
2.1 Frequency Distributions and Frequency Distribution Tables 35
2.2 Grouped Frequency Distribution Tables 38
2.3 Frequency Distribution Graphs 42
2.4 Percentiles, Percentile Ranks, and Interpolation 49
2.5 Stem and Leaf Displays 56
Summary 58
Focus on Problem Solving 59
Demonstration 2.1 60
Demonstration 2.2 61
Problems 62
CHA P t E R 3 Central Tendency 67
PREVIEW 68
3.1 Overview 68
3.2 The Mean 70
3.3 The Median 79
3.4 The Mode 83
3.5 Selecting a Measure of Central Tendency 86
3.6 Central Tendency and the Shape of the Distribution 92
Summary 94
Focus on Problem Solving 95
Demonstration 3.1 96
Problems 96
CHAP t ER 4 Variability 99
PREVIEW 100
4.1 Introduction to Variability 101
4.2 Defining Standard Deviation and Variance 103
4.3 Measuring Variance and Standard Deviation for a Population 108
4.4 Measuring Standard Deviation and Variance for a Sample 111
4.5 Sample Variance as an Unbiased Statistic 117
4.6 More about Variance and Standard Deviation 119
Summary 125
Focus on Problem Solving 127
Demonstration 4.1 128
Problems 128
CHA P t E R 5
z-Scores: Location of Scores
and Standardized Distributions 131
PREVIEW 132
5.1 Introduction to z-Scores 133
5.2 z-Scores and Locations in a Distribution 135
5.3 Other Relationships Between z, X, š¯›¨, and š¯›” 138
5.4 Using z-Scores to Standardize a Distribution 141
5.5 Other Standardized Distributions Based on z-Scores 145
5.6 Computing z-Scores for Samples 148
5.7 Looking Ahead to Inferential Statistics 150
Summary 153
Focus on Problem Solving 154
Demonstration 5.1 155
Demonstration 5.2 155
Problems 156
CHAP t E R 6 Probability 159
PREVIEW 160
6.1 Introduction to Probability 160
6.2 Probability and the Normal Distribution 165
6.3 Probabilities and Proportions for Scores
from a Normal Distribution 172
6.4 Probability and the Binomial Distribution 179
6.5 Looking Ahead to Inferential Statistics 184
Summary 186
Focus on Problem Solving 187
Demonstration 6.1 188
Demonstration 6.2 188
Problems 189
CHA P t E R 7
Probability and Samples: The Distribution
of Sample Means 193
PREVIEW 194
7.1 Samples, Populations, and the Distribution
of Sample Means 194
7.2 The Distribution of Sample Means for any Population
and any Sample Size 199
7.3 Probability and the Distribution of Sample Means 206
7.4 More about Standard Error 210
7.5 Looking Ahead to Inferential Statistics 215
Summary 219
Focus on Problem Solving 219
Demonstration 7.1 220
Problems 221
CHAP t E R 8 Introduction to Hypothesis Testing 223
PREVIEW 224
8.1 The Logic of Hypothesis Testing 225
8.2 Uncertainty and Errors in Hypothesis Testing 236
8.3 More about Hypothesis Tests 240
8.4 Directional (One-Tailed) Hypothesis Tests 245
8.5 Concerns about Hypothesis Testing: Measuring Effect Size 250
8.6 Statistical Power 254
Summary 260
Focus on Problem Solving 261
Demonstration 8.1 262
Demonstration 8.2 263
Problems 263
CHAP t E R 9 Introduction to the t Statistic 267
PREVIEW 268
9.1 The t Statistic: An Alternative to z 268
9.2 Hypothesis Tests with the t Statistic 274
9.3 Measuring Effect Size for the t Statistic 279
9.4 Directional Hypotheses and One-Tailed Tests 288
Summary 291
Focus on Problem Solving 293
Demonstration 9.1 293
Demonstration 9.2 294
Problems 295
CHAPtER 10 The t Test for Two Independent Samples 299
PREVIEW 300
10.1 Introduction to the Independent-Measures Design 300
10.2 The Null Hypothesis and the Independent-Measures t Statistic 302
10.3 Hypothesis Tests with the Independent-Measures t Statistic 310
10.4 Effect Size and Confidence Intervals for the
Independent-Measures t 316
10.5 The Role of Sample Variance and Sample Size in the
Independent-Measures t Test 322
Summary 325
Focus on Problem Solving 327
Demonstration 10.1 328
Demonstration 10.2 329
Problems 329
CHAPtER 11 The t Test for Two Related Samples 335
PREVIEW 336
11.1 Introduction to Repeated-Measures Designs 336
11.2 The t Statistic for a Repeated-Measures Research Design 339
11.3 Hypothesis Tests for the Repeated-Measures Design 343
11.4 Effect Size and Confidence Intervals for the Repeated-Measures t 347
11.5 Comparing Repeated- and Independent-Measures Designs 352
Summary 355
Focus on Problem Solving 358
Demonstration 11.1 358
Demonstration 11.2 359
Problems 360
CHAPtER 12 Introduction to Analysis of Variance 365
PREVIEW 366
12.1 Introduction (An Overview of Analysis of Variance) 366
12.2 The Logic of Analysis of Variance 372
12.3 ANOVA Notation and Formulas 375
12.4 Examples of Hypothesis Testing and Effect Size with ANOVA 383
12.5 Post Hoc Tests 393
12.6 More about ANOVA 397
Summary 403
Focus on Problem Solving 406
Demonstration 12.1 406
Demonstration 12.2 408
Problems 408
CHAPtER 13 Repeated-Measures Analysis of Variance 413
PREVIEW 414
13.1 Overview of the Repeated-Measures ANOVA 415
13.2 Hypothesis Testing and Effect Size with the
Repeated-Measures ANOVA 420
13.3 More about the Repeated-Measures Design 429
Summary 436
Focus on Problem Solving 438
Demonstration 13.1 439
Demonstration 13.2 440
Problems 441
CHAPtER 14
Two-Factor Analysis of Variance
(Independent Measures) 447
PREVIEW 448
14.1 An Overview of the Two-Factor, Independent-Measures, ANOVA: Main
Effects and Interactions 448
14.2 An Example of the Two-Factor ANOVA and Effect Size 458
14.3 More about the Two-Factor ANOVA 467
Summary 473
Focus on Problem Solving 475
Demonstration 14.1 476
Demonstration 14.2 478
Problems 479
CHAPtER 15 Correlation 485
PREVIEW 486
15.1 Introduction 487
15.2 The Pearson Correlation 489
15.3 Using and Interpreting the Pearson Correlation 495
15.4 Hypothesis Tests with the Pearson Correlation 506
15.5 Alternatives to the Pearson Correlation 510
Summary 520
Focus on Problem Solving 522
Demonstration 15.1 523
Problems 524
CHAPtER 16 Introduction to Regression 529
PREVIEW 530
16.1 Introduction to Linear Equations and Regression 530
16.2 The Standard Error of Estimate and Analysis of Regression:
The Significance of the Regression Equation 538
16.3 Introduction to Multiple Regression with Two Predictor Variables 544
Summary 552
Linear and Multiple Regression 554
Focus on Problem Solving 554
Demonstration 16.1 555
Problems 556
CHAPtER 17
The Chi-Square Statistic: Tests for Goodness
of Fit and Independence 559
PREVIEW 560
17.1 Introduction to Chi-Square: The Test for Goodness of Fit 561
17.2 An Example of the Chi-Square Test for Goodness of Fit 567
17.3 The Chi-Square Test for Independence 573
17.4 Effect Size and Assumptions for the Chi-Square Tests 582
17.5 Special Applications of the Chi-Square Tests 587
Summary 591
Focus on Problem Solving 595
Demonstration 17.1 595
Demonstration 17.2 597
Problems 597
CHAPtER 18 The Binomial Test 603
PREVIEW 604
18.1 Introduction to the Binomial Test 604
18.2 An Example of the Binomial Test 608
18.3 More about the Binomial Test: Relationship with Chi-Square
and the Sign Test 612
Summary 617
Focus on Problem Solving 619
Demonstration 18.1 619
Problems 620
APPENDIXES
A Basic Mathematics Review 625
A.1 Symbols and Notation 627
A.2 Proportions: Fractions, Decimals, and Percentages 629
A.3 Negative Numbers 635
A.4 Basic Algebra: Solving Equations 637
A.5 Exponents and Square Roots 640
B Statistical Tables 647
C Solutions for Odd-Numbered Problems in the Text 663
D General Instructions for Using SPSS 683
E Hypothesis Tests for Ordinal Data: Mann-Whitney,
Wilcoxon, Kruskal-Wallis, and Friedman Tests 687
Statistics Organizer: Finding the Right Statistics for Your Data 701
References 717
Name Index 723
Subject Index 725
 
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