Description

Book Synopsis

Provides well-organized coverage of statistical analysis and applications in biology, kinesiology, and physical anthropology with comprehensive insights into the techniques and interpretations of R, SPSS, Excel, and Numbers output

An Introduction to Statistical Analysis in Research: With Applications in the Biological and Life Sciences develops a conceptual foundation in statistical analysis while providing readers with opportunities to practice these skills via research-based data sets in biology, kinesiology, and physical anthropology. Readers are provided with a detailed introduction and orientation to statistical analysis as well as practical examples to ensure a thorough understanding of the concepts and methodology. In addition, the book addresses not just the statistical concepts researchers should be familiar with, but also demonstrates their relevance to real-world research questions and how to perform them using easily available software packages inclu

Table of Contents

Preface ix

Acknowledgments xi

About the Companion Website xiii

1 Experimental Design 1

1.1 Experimental Design Background 1

1.2 Sampling Design 2

1.3 Sample Analysis 7

1.4 Hypotheses 9

1.5 Variables 10

2 Central Tendency and Distribution 13

2.1 Central Tendency and Other Descriptive Statistics 13

2.2 Distribution 18

2.3 Descriptive Statistics in Excel 34

2.4 Descriptive Statistics in SPSS 48

2.5 Descriptive Statistics in Numbers 52

2.6 Descriptive Statistics in R 57

3 Showing Your Data 61

3.1 Background on Tables and Graphs 61

3.2 Tables 62

3.3 Bar Graphs, Histograms, and Box Plots 63

3.4 Line Graphs and Scatter Plots 136

3.5 Pie Charts 165

4 Parametric versus Nonparametric Tests 191

4.1 Overview 192

4.2 Two-Sample and Three-Sample Tests 194

5 t-Test 195

5.1 Student’s t-Test Background 195

5.2 Examples t-Tests 196

5.3 Case Study 201

5.4 Excel Tutorial 205

5.5 Paired t-Test SPSS Tutorial 209

5.6 Independent t-Test SPSS Tutorial 213

5.7 Numbers Tutorial 218

5.8 R Independent/Paired-Samples t-Test Tutorial 223

6 ANOVA 227

6.1 ANOVA Background 227

6.2 Case Study 236

6.3 One-Way ANOVA Excel Tutorial 241

6.4 One-Way ANOVA SPSS Tutorial 247

6.5 One-Way Repeated Measures ANOVA SPSS Tutorial 252

6.6 Two-Way Repeated Measures ANOVA SPSS Tutorial 261

6.7 One-Way ANOVA Numbers Tutorial 272

6.8 One-Way R Tutorial 288

6.9 Two-Way ANOVA R Tutorial 291

7 Mann–Whitney U and Wilcoxon Signed-Rank 297

7.1 Mann–Whitney U and Wilcoxon Signed-Rank Background 297

7.2 Assumptions 298

7.3 Case Study – Mann—Whitney U Test 299

7.4 Case Study –Wilcoxon Signed-Rank 302

7.5 Mann–Whitney U Excel Tutorial 305

7.6 Wilcoxon Signed-Rank Excel Tutorial 313

7.7 Mann–Whitney U SPSS Tutorial 319

7.8 Wilcoxon Signed-Rank SPSS Tutorial 324

7.9 Mann–Whitney U Numbers Tutorial 328

7.10 Wilcoxon Signed-Rank Numbers Tutorial 337

7.11 Mann–Whitney U/Wilcoxon Signed-Rank R Tutorial 350

8 Kruskal–Wallis 353

8.1 Kruskal–Wallis Background 353

8.2 Case Study 1 354

8.3 Case Study 2 358

8.4 Kruskal–Wallis Excel Tutorial 362

8.5 Kruskal–Wallis SPSS Tutorial 368

8.6 Kruskal–Wallis Numbers Tutorial 375

8.7 Kruskal–Wallis R Tutorial 386

9 Chi-Square Test 393

9.1 Chi-Square Background 393

9.2 Case Study 1 394

9.3 Case Study 2 401

9.4 Chi-Square Excel Tutorial 405

9.5 Chi-Square SPSS Tutorial 418

9.6 Chi-Square Numbers Tutorial 426

9.7 Chi-Square R Tutorial 429

10 Pearson’s and Spearman’s Correlation 435

10.1 Correlation Background 435

10.2 Example 435

10.3 Case Study – Pearson’s Correlation 442

10.4 Case Study – Spearman’s Correlation 445

10.5 Pearson’s Correlation Excel and Numbers Tutorial 448

10.6 Spearman’s Correlation Excel Tutorial 455

10.7 Pearson/Spearman’s Correlation SPSS Tutorial 462

10.8 Pearson/Spearman’s Correlation R Tutorial 467

11 Linear Regression 473

11.1 Linear Regression Background 473

11.2 Case Study 480

11.3 Linear Regression Excel Tutorial 484

11.4 Linear Regression SPSS Tutorial 497

11.5 Linear Regression Numbers Tutorial 508

11.6 Linear Regression R Tutorial 517

12 Basics in Excel 523

12.1 Opening Excel 524

12.2 Installing the Data Analysis Tool Pak 525

12.3 Cells and Referencing 529

12.4 Common Commands and Formulas 532

12.5 Applying Commands to Entire Columns 534

12.6 Inserting a Function 536

12.7 Formatting Cells 537

13 Basics in SPSS 539

13.1 Opening SPSS 539

13.2 Labeling Variables 541

13.3 Setting Decimal Placement 543

13.4 Determining the Measure of a Variable 544

13.5 Saving SPSS Data Files 545

13.6 Saving SPSS Output 547

14 Basics in Numbers 551

14.1 Opening Numbers 551

14.2 Common Commands 553

14.3 Applying Commands 555

14.4 Adding Functions 557

15 Basics in R 561

15.1 Opening R 561

15.2 Getting Acquainted with the Console 562

15.3 Loading Data 566

15.4 Installing and Loading Packages 570

15.5 Troubleshooting 576

16 Appendix 579

Flow Chart 579

Literature Cited 581

Glossary 585

Index 591

An Introduction to Statistical Analysis in

    Product form

    £98.75

    Includes FREE delivery

    RRP £103.95 – you save £5.20 (5%)

    Order before 4pm tomorrow for delivery by Sat 11 Jul 2026.

    A Hardback by Kathleen F. Weaver, Vanessa C. Morales, Sarah L. Dunn

    10 in stock

      Trusted by thousands of customers. See 2,385+ Customer Reviews

      View other formats and editions of An Introduction to Statistical Analysis in by Kathleen F. Weaver

      Publisher: John Wiley & Sons Inc
      Publication Date: 26/09/2017
      ISBN13: 9781119299684, 978-1119299684
      ISBN10: 1119299683

      Description

      Book Synopsis

      Provides well-organized coverage of statistical analysis and applications in biology, kinesiology, and physical anthropology with comprehensive insights into the techniques and interpretations of R, SPSS, Excel, and Numbers output

      An Introduction to Statistical Analysis in Research: With Applications in the Biological and Life Sciences develops a conceptual foundation in statistical analysis while providing readers with opportunities to practice these skills via research-based data sets in biology, kinesiology, and physical anthropology. Readers are provided with a detailed introduction and orientation to statistical analysis as well as practical examples to ensure a thorough understanding of the concepts and methodology. In addition, the book addresses not just the statistical concepts researchers should be familiar with, but also demonstrates their relevance to real-world research questions and how to perform them using easily available software packages inclu

      Table of Contents

      Preface ix

      Acknowledgments xi

      About the Companion Website xiii

      1 Experimental Design 1

      1.1 Experimental Design Background 1

      1.2 Sampling Design 2

      1.3 Sample Analysis 7

      1.4 Hypotheses 9

      1.5 Variables 10

      2 Central Tendency and Distribution 13

      2.1 Central Tendency and Other Descriptive Statistics 13

      2.2 Distribution 18

      2.3 Descriptive Statistics in Excel 34

      2.4 Descriptive Statistics in SPSS 48

      2.5 Descriptive Statistics in Numbers 52

      2.6 Descriptive Statistics in R 57

      3 Showing Your Data 61

      3.1 Background on Tables and Graphs 61

      3.2 Tables 62

      3.3 Bar Graphs, Histograms, and Box Plots 63

      3.4 Line Graphs and Scatter Plots 136

      3.5 Pie Charts 165

      4 Parametric versus Nonparametric Tests 191

      4.1 Overview 192

      4.2 Two-Sample and Three-Sample Tests 194

      5 t-Test 195

      5.1 Student’s t-Test Background 195

      5.2 Examples t-Tests 196

      5.3 Case Study 201

      5.4 Excel Tutorial 205

      5.5 Paired t-Test SPSS Tutorial 209

      5.6 Independent t-Test SPSS Tutorial 213

      5.7 Numbers Tutorial 218

      5.8 R Independent/Paired-Samples t-Test Tutorial 223

      6 ANOVA 227

      6.1 ANOVA Background 227

      6.2 Case Study 236

      6.3 One-Way ANOVA Excel Tutorial 241

      6.4 One-Way ANOVA SPSS Tutorial 247

      6.5 One-Way Repeated Measures ANOVA SPSS Tutorial 252

      6.6 Two-Way Repeated Measures ANOVA SPSS Tutorial 261

      6.7 One-Way ANOVA Numbers Tutorial 272

      6.8 One-Way R Tutorial 288

      6.9 Two-Way ANOVA R Tutorial 291

      7 Mann–Whitney U and Wilcoxon Signed-Rank 297

      7.1 Mann–Whitney U and Wilcoxon Signed-Rank Background 297

      7.2 Assumptions 298

      7.3 Case Study – Mann—Whitney U Test 299

      7.4 Case Study –Wilcoxon Signed-Rank 302

      7.5 Mann–Whitney U Excel Tutorial 305

      7.6 Wilcoxon Signed-Rank Excel Tutorial 313

      7.7 Mann–Whitney U SPSS Tutorial 319

      7.8 Wilcoxon Signed-Rank SPSS Tutorial 324

      7.9 Mann–Whitney U Numbers Tutorial 328

      7.10 Wilcoxon Signed-Rank Numbers Tutorial 337

      7.11 Mann–Whitney U/Wilcoxon Signed-Rank R Tutorial 350

      8 Kruskal–Wallis 353

      8.1 Kruskal–Wallis Background 353

      8.2 Case Study 1 354

      8.3 Case Study 2 358

      8.4 Kruskal–Wallis Excel Tutorial 362

      8.5 Kruskal–Wallis SPSS Tutorial 368

      8.6 Kruskal–Wallis Numbers Tutorial 375

      8.7 Kruskal–Wallis R Tutorial 386

      9 Chi-Square Test 393

      9.1 Chi-Square Background 393

      9.2 Case Study 1 394

      9.3 Case Study 2 401

      9.4 Chi-Square Excel Tutorial 405

      9.5 Chi-Square SPSS Tutorial 418

      9.6 Chi-Square Numbers Tutorial 426

      9.7 Chi-Square R Tutorial 429

      10 Pearson’s and Spearman’s Correlation 435

      10.1 Correlation Background 435

      10.2 Example 435

      10.3 Case Study – Pearson’s Correlation 442

      10.4 Case Study – Spearman’s Correlation 445

      10.5 Pearson’s Correlation Excel and Numbers Tutorial 448

      10.6 Spearman’s Correlation Excel Tutorial 455

      10.7 Pearson/Spearman’s Correlation SPSS Tutorial 462

      10.8 Pearson/Spearman’s Correlation R Tutorial 467

      11 Linear Regression 473

      11.1 Linear Regression Background 473

      11.2 Case Study 480

      11.3 Linear Regression Excel Tutorial 484

      11.4 Linear Regression SPSS Tutorial 497

      11.5 Linear Regression Numbers Tutorial 508

      11.6 Linear Regression R Tutorial 517

      12 Basics in Excel 523

      12.1 Opening Excel 524

      12.2 Installing the Data Analysis Tool Pak 525

      12.3 Cells and Referencing 529

      12.4 Common Commands and Formulas 532

      12.5 Applying Commands to Entire Columns 534

      12.6 Inserting a Function 536

      12.7 Formatting Cells 537

      13 Basics in SPSS 539

      13.1 Opening SPSS 539

      13.2 Labeling Variables 541

      13.3 Setting Decimal Placement 543

      13.4 Determining the Measure of a Variable 544

      13.5 Saving SPSS Data Files 545

      13.6 Saving SPSS Output 547

      14 Basics in Numbers 551

      14.1 Opening Numbers 551

      14.2 Common Commands 553

      14.3 Applying Commands 555

      14.4 Adding Functions 557

      15 Basics in R 561

      15.1 Opening R 561

      15.2 Getting Acquainted with the Console 562

      15.3 Loading Data 566

      15.4 Installing and Loading Packages 570

      15.5 Troubleshooting 576

      16 Appendix 579

      Flow Chart 579

      Literature Cited 581

      Glossary 585

      Index 591

      Recently viewed products

      © 2026 Book Curl

        • American Express
        • Apple Pay
        • Diners Club
        • Discover
        • Google Pay
        • Maestro
        • Mastercard
        • PayPal
        • Shop Pay
        • Union Pay
        • Visa

        Login

        Forgot your password?

        Don't have an account yet?
        Create account