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Tokunaga, H: Fundamental Statistics for the Social and Behav

Tokunaga, H: Fundamental Statistics for the Social and Behav


en Limba Engleză Paperback – 17 ian 2019

Observăm că a doua ediție a lucrării Fundamental Statistics for the Social and Behavioral Sciences aduce îmbunătățiri metodologice esențiale pentru studenții din domeniul științelor sociale. Cea mai importantă noutate este introducerea unui capitol dedicat regresiei, completând astfel setul de instrumente statistice fundamentale. Ne-a atras atenția modul în care Howard T. Tokunaga echilibrează rigoarea matematică cu aplicabilitatea practică, oferind un parcurs clar de la organizarea și prezentarea datelor până la testarea ipotezelor complexe în cercetare. Structura volumului este riguros organizată pentru a sprijini progresia învățării. Capitolele introductive pun bazele teoretice, fiind urmate de secțiuni tehnice despre tabele, figuri și măsuri ale tendinței centrale. Considerăm că includerea instrucțiunilor pentru software-ul IBM SPSS direct în text reprezintă un avantaj didactic major, transformând teoria abstractă în competențe de analiză aplicată. Fiecare unitate de învățare este punctată de „learning checks” și rezumate care consolidează informația înainte ca studentul să treacă la exercițiile de evaluare de la final. Această lucrare acoperă aceeași arie tematică precum Statistics for the Behavioral Sciences de Bryan Raudenbush, dar se diferențiază prin integrarea resurselor multimedia SAGE edge și o abordare mai extinsă a procedurilor statistice în funcție de numărul de variabile independente. Dacă volumul lui Raudenbush mizează pe o structură modulară și concisă, Fundamental Statistics for the Social and Behavioral Sciences oferă o explorare mai detaliată a contextelor de cercetare, fiind ideală pentru cei care au nevoie de o ghidare pas cu pas în procesul de analiză a datelor comportamentale.

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Specificații

ISBN-13: 9781506377483
ISBN-10: 1506377483
Pagini: 712
Dimensiuni: 183 x 268 x 23 mm
Greutate: 1.55 kg
Ediția:2 Revised edition
Editura: Sage Publications, Inc
Locul publicării:Thousand Oaks, United States

De ce să citești această carte

Recomandăm această carte studenților de la psihologie și sociologie care doresc să stăpânească statistica fără a fi intimidați de formule. Cititorul câștigă o înțelegere clară a modului în care datele pot susține sau infirma o ipoteză de cercetare. Motivul principal pentru achiziție este accesul la resursele video și suportul pentru SPSS, care fac din acest manual un instrument de studiu autonom extrem de eficient.

Despre autor

Howard T. Tokunaga este profesor de psihologie la San Jose State University, unde coordonează programul de master în Psihologie Industrială și Organizațională (I/O). Cu un doctorat obținut la UC Berkeley, Tokunaga îmbină experiența academică de predare a cursurilor de statistică și metode de cercetare cu activitatea de consultanță în sectorul public și privat. Expertiza sa în managementul resurselor umane și analiza datelor se reflectă în claritatea cu care explică aplicarea statisticii în problemele reale ale societății contemporane.

Descriere scurtă

The Second Edition includes a new chapter on regression; covers how collected data can be organized, presented and summarized; the process of conducting statistical analyses to test research questions, hypotheses, and issues/controversies; and examines statistical procedures used in research situations that vary in the number of independent variables in the study. Every chapter includes learning checks, such as review questions and summary boxes, to reinforce the content students just learned, and exercises at the end of every chapter help assess their knowledge. 

FREE SAGE edge online resources, including SAGE original videos with Howard T. Tokunaga, makes learning easier for students. 

Recenzii

“I think this is some of the best explanation for these concepts that I have read.”
“I appreciate the structures, the simplicity in the language, the clarity and the ability to pull material that is appropriate for college level courses.”
“I think the author has a strong command and grasp of the material which he demonstrates by providing students with a multitude of examples and formulas that are easy to understand and broken down into digestible portions for students to absorb at their own pace. The writing style of the author is excellent…He spends a significant amount of time decomposing and deconstructing complex ideas related to the measures of central tendency for both novice and expert students of statistics in a user-friendly and approachable tone.”
“The writing style is nice and easy to follow.”
 

Cuprins

About the Author
Preface to the Second Edition
Preface to the First Edition
Acknowledgments
Companion Site
Chapter 1. Introduction to Statistics
1.1 What Is Statistics?
1.2 Why Learn Statistics?
1.3 Introduction to the Stages of the Research Process
1.4 Plan of the Book
1.5 Looking Ahead
1.6 Summary
1.7 Important Terms
1.8 Exercises
Chapter 2. Examining Data: Tables and Figures
2.1 An Example From the Research: Winning the Lottery
2.2 Why Examine Data?
2.3 Examining Data Using Tables
2.4 Grouped Frequency Distribution Tables
2.5 Examining Data Using Figures
2.6 Examining Data: Describing Distributions
2.7 Looking Ahead
2.8 Summary
2.9 Important Terms
2.10 Formulas Introduced in This Chapter
2.11 Using IBM SPSS Software
2.12 Exercises
Chapter 3. Measures of Central Tendency
3.1 An Example From the Research: The 10% Myth
3.2 Understanding Central Tendency
3.3 The Mode
3.4 The Median
3.5 The Mean
3.6 Comparison of the Mode, Median, and Mean
3.7 Measures of Central Tendency: Drawing Conclusions
3.8 Looking Ahead
3.9 Summary
3.10 Important Terms
3.11 Formulas Introduced in This Chapter
3.12 Exercises
Chapter 4. Measures of Variability
4.1 An Example From the Research: How Many “Sometimes” in an “Always”?
4.2 Understanding Variability
4.3 The Range
4.4 The Interquartile Range
4.5 The Variance (s2)
4.6 The Standard Deviation (s)
4.7 Measures of Variability for Populations
4.8 Measures of Variability for Nominal Variables
4.9 Measures of Variability: Drawing Conclusions
4.10 Looking Ahead
4.11 Summary
4.12 Important Terms
4.13 Formulas Introduced in This Chapter
4.14 Using SPSS
4.15 Exercises
Chapter 5. Normal Distributions
5.1 Example: SAT Scores
5.2 Normal Distributions
5.3 The Standard Normal Distribution
5.4 Applying z-Scores to Normal Distributions
5.5 Standardizing Frequency Distributions
5.6 Looking Ahead
5.7 Summary
5.8 Important Terms
5.9 Formulas Introduced in This Chapter
5.10 Exercises
Chapter 6. Probability and Introduction to Hypothesis Testing
6.1 A Brief Introduction to Probability
6.2 Example: Making Heads or Tails of the Super Bowl
6.3 Introduction to Hypothesis Testing
6.4 Issues Related to Hypothesis Testing: An Introduction
6.5 Looking Ahead
6.6 Summary
6.7 Important Terms
6.8 Formulas Introduced in This Chapter
6.9 Exercises
Chapter 7. Testing One Sample Mean
7.1 An Example From the Research: Do You Read Me?
7.2 The Sampling Distribution of the Mean
7.3 Inferential Statistics: Testing One Sample Mean (s Known)
7.4 A Second Example From the Research: Unique Invulnerability
7.5 Introduction to the t-Distribution
7.6 Inferential Statistics: Testing One Sample Mean (s Not Known)
7.7 Factors Affecting the Decision About the Null Hypothesis
7.8 Looking Ahead
7.9 Summary
7.10 Important Terms
7.11 Formulas Introduced in This Chapter
7.12 Using SPSS
7.13 Exercises
Chapter 8. Estimating the Mean of a Population
8.1 An Example From the Research: Salary Survey
8.2 Introduction to the Confidence Interval for the Mean
8.3 The Confidence Interval for the Mean (s Not Known)
8.4 The Confidence Interval for the Mean (s Known)
8.5 Factors Affecting the Width of the Confidence Interval for the Mean
8.6 Interval Estimation and Hypothesis Testing
8.7 Looking Ahead
8.8 Summary
8.9 Important Terms
8.10 Formulas Introduced in This Chapter
8.11 Using SPSS
8.12 Exercises
Chapter 9. Testing the Difference Between Two Means
9.1 An Example From the Research: You Can Just Wait
9.2 The Sampling Distribution of the Difference
9.3 Inferential Statistics: Testing the Difference Between Two Sample Means
9.4 Inferential Statistics: Testing the Difference Between Two Sample Means (Unequal Sample Sizes)
9.5 Inferential Statistics: Testing the Difference Between Paired Means
9.6 Looking Ahead
9.7 Summary
9.8 Important Terms
9.9 Formulas Introduced in This Chapter
9.10 Using SPSS
9.11 Exercises
Chapter 10. Errors in Hypothesis Testing, Statistical Power, and Effect Size
10.1 Hypothesis Testing vs. Criminal Trials
10.2 An Example From the Research: Truth or Consequences
10.3 Two Errors in Hypothesis Testing: Type I and Type II Error
10.4 Controlling Type I and Type II Error
10.5 Measures of Effect Size
10.6 Looking Ahead
10.7 Summary
10.8 Important Terms
10.9 Formulas Introduced in This Chapter
10.10 Exercises
Chapter 11. One-Way Analysis of Variance (ANOVA)
11.1 An Example From the Research: It’s Your Move
11.2 Introduction to Analysis of Variance (ANOVA)
11.3 Inferential Statistics: One-Way Analysis of Variance (ANOVA)
11.4 A Second Example: The Parking Lot Study Revisited
11.5 Analytical Comparisons Within the One-Way ANOVA
11.6 Looking Ahead
11.7 Summary
11.8 Important Terms
11.9 Formulas Introduced in This Chapter
11.10 Using SPSS
11.11 Exercises
Chapter 12. Two-Way Analysis of Variance (ANOVA)
12.1 An Example From the Research: Vote—or Else!
12.2 Introduction to Factorial Research Designs
12.3 The Two-Factor (A × B) Research Design
12.4 Introduction to Analysis of Variance (ANOVA) for the Two-Factor Research Design
12.5 Inferential Statistics: Two-Way Analysis of Variance (ANOVA)
12.6 Investigating a Significant A × B Interaction Effect: Analysis of Simple Effects
12.7 Looking Ahead
12.8 Summary
12.9 Important Terms
12.10 Formulas Introduced in This Chapter
12.11 Using SPSS
12.12 Exercises
Chapter 13. Correlation
13.1 An Example From the Research: It’s Good for You!
13.2 Introduction to the Concept of Correlation
13.3 Inferential Statistics: Pearson Correlation Coefficient
13.4 Correlating Two Sets of Ranks: The Spearman Rank-Order Correlation
13.5 Correlational Statistics vs. Correlational Research
13.6 Looking Ahead
13.7 Summary
13.8 Important Terms
13.9 Formulas Introduced in This Chapter
13.10 Using SPSS
13.11 Exercises
Chapter 14. Linear Regression and Multiple Correlation
14.1 Predicting One Variable From Another: Linear Regression
14.2 Correlation With Two or More Predictors: Introduction to Multiple Correlation and Regression
14.3 Looking Ahead
14.4 Summary
14.5 Important Terms
14.6 Formulas Introduced in This Chapter
14.7 Using SPSS
14.8 Exercises
Chapter 15. Chi-Square
15.1 An Example From the Research (One Categorical Variable): Are You My Type?
15.2 Introduction to the Chi-Square Statistic
15.3 Inferential Statistic: Chi-Square Goodness-of-Fit Test
15.4 An Example From the Research (Two Categorical Variables): Seeing Red
15.5 Inferential Statistic: Chi-Square Test of Independence
15.6 Parametric and Nonparametric Statistical Tests
15.7 Looking Ahead
15.8 Summary
15.9 Important Terms
15.10 Formulas Introduced in This Chapter
15.11 Using SPSS
15.12 Exercises
Tables
Appendix: Review of Basic Mathematics
Glossary
References
Index

Notă biografică

Howard T. Tokunaga is Professor of Psychology at San Jose State University, where he serves as Coordinator of the MS Program in Industrial/Organizational (I/O) Psychology and teaches undergraduate and graduate courses in statistics, research methods, and I/O psychology. He received his bachelor¿s degree in psychology at UC Santa Cruz and his PhD in psychology at UC Berkeley. In addition to his teaching, he has consulted with a number of public-sector and private-sector organizations on a wide variety of management and human resource issues. He is coauthor (with G. Keppel) of Introduction to Design and Analysis: A Student¿s Handbook.

Descriere

Fundamental Statistics is designed not to just teach students how to calculate statistics, but how to interpret the results of statistical analyses in light of a research hypothesis, and to communicate the results and interpretations to a broader audience.