Statistical Methods (eBook)

Donna L. Mohr (Autor)

eBook Download: EPUB

2010 | 3. Auflage
824 Seiten
Elsevier Science (Verlag)
978-0-08-096103-3 (ISBN)

Infos

Statistical Methods, 3e 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 intepreting 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:

• 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
• NEW case studies for gathering, summarizing, and analyzing data

Supplements:

• NEW companion website with downloadable data sets and additional resources including live links to statistical software such as SAS and SPSS
• Student Solutions Manual - to come
• Instructor Manual - to come
• Sample chapter - http://www.elsevierdirect.com/product.jsp?isbn=9780123749703

• Integrates the classical conceptual approach with modern day computerized data manipulation and computer applications
• Accessibile to students who may not have a background in probability or calculus
• Offers reader-friendly exposition, without sacrificing statistical rigor
• Includes many new data sets in various applied fields such as Psychology, Education, Biostatistics, Agriculture, Economics

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Statistical Methods, Third Edition, 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 that emphasizes concepts and techniques for working out problems and intepreting results. The book includes research projects, real-world case studies, numerous examples, and data exercises organized by level of difficulty. Students are required to be familiar with algebra. This updated edition includes new 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. - Integrates the classical conceptual approach with modern day computerized data manipulation and computer applications- Accessibile to students who may not have a background in probability or calculus- Offers reader-friendly exposition, without sacrificing statistical rigor- Includes many new data sets in various applied fields such as Psychology, Education, Biostatistics, Agriculture, Economics

Inhalt

Front cover 1
Statistical Methods 4
Copyright page 5
Table of contents 6
Preface 18
Chapter 1. Data and Statistics 24
1.1 Introduction 24
1.2 Observations and Variables 29
1.3 Types of Measurements for Variables 33
1.4 Distributions 35
1.5 Numerical Descriptive Statistics 42
1.6 Exploratory Data Analysis 55
1.7 Bivariate Data 62
1.8 Populations, Samples, and Statistical Inference —A Preview 66
1.9 Data Collection 67
1.10 Chapter Summary 69
1.11 Chapter Exercises 74
Chapter 2. Probability and Sampling Distributions 90
2.1 Introduction 91
2.2 Probability 94
2.3 Discrete Probability Distributions 102
2.4 Continuous Probability Distributions 109
2.5 Sampling Distributions 120
2.6 Other Sampling Distributions 131
2.7 Chapter Summary 139
2.8 Chapter Exercises 139
Chapter 3. Principles of Inference 148
3.1 Introduction 149
3.2 Hypothesis Testing 150
3.3 Estimation 172
3.4 Sample Size 176
3.5 Assumptions 180
3.6 Chapter Summary 183
3.7 Chapter Exercises 185
Chapter 4. Inferences on a Single Population 192
4.1 Introduction 193
4.2 Inferences on the Population Mean 194
4.3 Inferences on a Proportion 201
4.4 Inferences on the Variance of One Population 204
4.5 Assumptions 207
4.6 Chapter Summary 215
4.7 Chapter Exercises 215
Chapter 5. Inferences for Two Populations 224
5.1 Introduction 225
5.2 Inferences on the Difference between Means Using Independent Samples 227
5.3 Inferences on Variances 238
5.4 Inferences on Means for Dependent Samples 242
5.5 Inferences on Proportions 247
5.6 Assumptions and Remedial Methods 252
5.7 Chapter Summary 255
5.8 Chapter Exercises 257
Chapter 6. Inferences for Two or More Means 268
6.1 Introduction 269
6.2 The Analysis of Variance 270
6.3 The Linear Model 281
6.4 Assumptions 285
6.5 Specific Comparisons 292
6.6 Random Models 320
6.7 Unequal Sample Sizes 323
6.8 Analysis of Means 324
6.9 Chapter Summary 332
6.10 Chapter Exercises 333
Chapter 7. Linear Regression 344
7.1 Introduction 345
7.2 The Regression Model 348
7.3 Estimation of Parameters ß0 and ß1 352
7.4 Estimation of s2 and the Partitioning of Sums of Squares 356
7.5 Inferences for Regression 360
7.6 Using the Computer 371
7.7 Correlation 374
7.8 Regression Diagnostics 380
7.9 Chapter Summary 386
7.10 Chapter Exercises 388
Chapter 8. Multiple Regression 398
8.1 The Multiple Regression Model 401
8.2 Estimation of Coefficients 404
8.3 Inferential Procedures 417
8.4 Correlations 430
8.5 Using the Computer 433
8.6 Special Models 437
8.7 Multicollinearity 447
8.8 Variable Selection 454
8.9 Detection of Outliers, Row Diagnostics 461
8.10 Chapter Summary 469
8.11 Chapter Exercises 473
Chapter 9. Factorial Experiments 496
9.1 Introduction 497
9.2 Concepts and Definitions 498
9.3 The Two-Factor Factorial Experiment 501
9.4 Specific Comparisons 512
9.5 Quantitative Factors 520
9.6 No Replications 525
9.7 Three or More Factors 525
9.8 Chapter Summary 529
9.9 Chapter Exercises 532
Chapter 10. Design of Experiments 544
10.1 Introduction 546
10.2 The Randomized Block Design 547
10.3 Randomized Blocks with Sampling 555
10.4 Other Designs 561
10.5 Repeated Measures Designs 570
10.6 Chapter Summary 584
10.7 Chapter Exercises 588
Chapter 11. Other Linear Models 600
11.1 Introduction 602
11.2 The Dummy Variable Model 603
11.3 Unbalanced Data 607
11.4 Computer Implementation of the DummyVariable Model 610
11.5 Models with Dummy and Interval Variables 612
11.6 Extensions to Other Models 624
11.7 Estimating Linear Combinations of RegressionParameters 625
11.8 Weighted Least Squares 629
11.9 Correlated Errors 633
11.10 Chapter Summary 636
11.11 Chapter Exercises 642
Chapter 12. Categorical Data 656
12.1 Introduction 657
12.2 Hypothesis Tests for a Multinomial Population 657
12.3 Goodness of Fit Using the .2 Test 660
12.4 Contingency Tables 664
12.5 Loglinear Model 672
12.6 Chapter Summary 678
12.7 Chapter Exercises 678
Chapter 13. Special Types of Regression 686
13.1 Introduction 686
13.2 Logistic Regression 688
13.3 Poisson Regression 695
13.4 Nonlinear Least-Squares Regression 701
13.5 Chapter Summary 706
13.6 Chapter Exercises 707
Chapter 14. Nonparametric Methods 712
14.1 Introduction 714
14.2 One Sample 719
14.3 Two Independent Samples 723
14.4 More Than Two Samples 725
14.5 Randomized Block Design 729
14.6 Rank Correlation 731
14.7 The Bootstrap 733
14.8 Chapter Summary 735
14.9 Chapter Exercises 737
Appendix A 744
A.1 The Normal Distribution—Probabilities Exceeding Z 744
A.1A Selected Probability Values for the Normal Distribution—Values of Z Exceeded with Given Probability 749
A.2 The t Distribution—Values of t Exceeded with Given Probability 750
A.3 The .2 Distribution—.2 Values Exceeded with Given Probability 751
A.4 The F Distribution, p = 0.1 752
A.4A The F Distribution, p = 0.05 754
A.4B The F Distribution, p = 0.025 756
A.4C The F Distribution, p = 0.01 758
A.4D The F Distribution, p = 0.005 760
A.5 The Fmax Distribution—Percentage Points of Fmax = s2max/s2max 762
A.6 Orthogonal Polynomials (Tables of Coefficients for Polynomial Trends) 763
A.7 Percentage Points of the Studentized Range 764
A.8 Percentage Points of Duncan’s Multiple Range Test 766
A.9 Critical Values for the Wilcoxon Signed Rank Test N = 5(1)50 768
A.10 The Mann–Whitney Two-Sample Test 769
A.11 Exact Critical Values for Use with the Analysis of Means 771
Appendix B. A Brief Introduction to Matrices 776
B.1 Matrix Algebra 777
B.2 Solving Linear Equations 781
Appendix C.1 784
C.1 Florida Lake Data 784
C.2 State Education Data Set 786
C.3 NADP Data Set 787
C.4 Florida County Data Set 789
C.5 Cowpea Data Set 789
Hints for Selected Exercises 792
References 808
Index 814

Produkt-Details

• Erscheint lt. Verlag: 17.8.2010
• Sprache: englisch
• Themenwelt: Sachbuch/Ratgeber
• Themenwelt: Mathematik / Informatik ► Mathematik ► Statistik
• Themenwelt: Technik
• ISBN-10: 0-08-096103-7 / 0080961037
• ISBN-13: 978-0-08-096103-3 / 9780080961033