Statistics for research.

Format:

Book

Author/Creator:

Dowdy, S. M.

Contributor:

Wearden, Stanley, 1926-2012.

Chilko, Daniel M.

Alumni and Friends Memorial Book Fund.

Series:

Wiley series in probability and statistics

Language:

English

Subjects (All):

Mathematical statistics.

Physical Description:

xvi, 627 pages : illustrations ; 25 cm.

Edition:

Third edition / Shirley Dowdy, Stanley Weardon, Daniel Chilko.

Place of Publication:

Hoboken, N.J. : Wiley-Interscience, [2004]

Summary:

Although the goals and procedures of statistical research have changed little since the Second Edition of Statistics for Research was published, the almost universal availability of personal computers and statistical computing application packages have made it possible for today's statisticians to do more in less time than ever before. The Third Edition of this bestselling text reflects how the changes in the computing environment have transformed the way statistical analyses are performed today. Based on extensive input from university statistics departments throughout the country, the authors have made several important and timely revisions The text features the most commonly used statistical techniques for the analysis of research data. As in the earlier editions, emphasis is placed on how to select the proper statistical procedure and how to interpret results. Whenever possible, to avoid using the computer as a "black box" that performs a mysterious process on the data, actual computational procedures are also given. A must for scientists who analyze data, professionals and researchers who need a self-teaching text, and graduate students in statistical methods, Statistics for Research, Third Edition brings the methodology up to date in a very practical and accessible way.

Contents:

1 The Role of Statistics 1

1.1 The Basic Statistical Procedure 1

1.2 The Scientific Method 11

1.3 Experimental Data and Survey Data 19

1.4 Computer Usage 20

2 Populations, Samples, and Probability Distributions 25

2.1 Populations and Samples 25

2.2 Random Sampling 27

2.3 Levels of Measurement 30

2.4 Random Variables and Probability Distributions 33

2.5 Expected Value and Variance of a Probability Distribution 39

3 Binomial Distributions 49

3.1 The Nature of Binomial Distributions 49

3.2 Testing Hypotheses 59

3.3 Estimation 70

3.4 Nonparametric Statistics: Median Test 77

4 Poisson Distributions 81

4.1 The Nature of Poisson Distributions 81

4.2 Testing Hypotheses 84

4.3 Estimation 87

4.4 Poisson Distributions and Binomial Distributions 90

5 Chi-Square Distributions 95

5.1 The Nature of Chi-Square Distributions 95

5.2 Goodness-of-Fit Tests 104

5.3 Contingency Table Analysis 108

5.4 Relative Risks and Odds Ratios 117

5.5 Nonparametric Statistics: Median Test for Several Samples 121

6 Sampling Distribution of Averages 127

6.1 Population Mean and Sample Average 127

6.2 Population Variance and Sample Variance 132

6.3 The Mean and Variance of the Sampling Distribution of Averages 138

6.4 Sampling Without Replacement 143

7 Normal Distributions 147

7.1 The Standard Normal Distribution 147

7.2 Inference From a Single Observation 152

7.3 The Central Limit Theorem 155

7.4 Inferences About a Population Mean and Variance 157

7.5 Using a Normal Distribution to Approximate Other Distributions 164

7.6 Nonparametric Statistics: A Test Based on Ranks 173

8 Student's t Distribution 179

8.1 The Nature of t Distributions 179

8.2 Inference About a Single Mean 182

8.3 Inference About Two Means 190

8.4 Inference About Two Variances 197

8.5 Nonparametric Statistics: Matched-Pair and Two-Sample Rank Tests 204

9 Distributions of Two Variables 211

9.1 Simple Linear Regression 211

9.2 Model Testing 223

9.3 Inferences Related to Regression 233

9.4 Correlation 238

9.5 Nonparametric Statistics: Rank Correlation 250

9.6 Computer Usage 253

9.7 Estimating Only One Linear Trend Parameter 256

10 Techniques for One-way Analysis of Variance 265

10.1 The Additive Model 265

10.2 One-Way Analysis-of-Variance Procedure 272

10.3 Multiple-Comparison Procedures 283

10.4 One-Degree-of-Freedom Comparisons 294

10.5 Estimation 300

10.6 Bonferroni Procedures 303

10.7 Nonparametric Statistics: Kruskal-Wallis ANOVA for Ranks 309

11 The Analysis-of-Variance Model 317

11.1 Random Effects and Fixed Effects 317

11.2 Testing the Assumptions for ANOVA 324

11.3 Transformations 329

12 Other Analysis-of-Variance Designs 341

12.1 Nested Design 341

12.2 Randomized Complete Block Design 350

12.3 Latin Square Design 360

12.4 a x b Factorial Design 368

12.5 a x b x c Factorial Design 376

12.6 Split-Plot Design 387

12.7 Split Plot with Repeated Measures 398

13 Analysis of Covariance 409

13.1 Combining Regression with ANOVA 409

13.2 One-Way Analysis of Covariance 413

13.3 Testing the Assumptions for Analysis of Covariance 418

13.4 Multiple-Comparison Procedures 423

14 Multiple Regression and Correlation 431

14.1 Matrix Procedures 431

14.2 ANOVA Procedures for Multiple Regression and Correlation 439

14.3 Inferences About Effects of Independent Variables 444

14.4 Computer Usage 451

14.5 Model Fitting 458

14.6 Logarithmic Transformations 475

14.7 Polynomial Regression 484

14.8 Logistic Regression 495.

Notes:

Includes bibliographical references and index.

Local Notes:

Acquired for the Penn Libraries with assistance from the Alumni and Friends Memorial Book Fund.

ISBN:

047126735X

OCLC:

52377620

Online:

Publisher description