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Introduction to Applied Statistics: With Step-By-Step SPSS Instructions 2nd edition [Kõva köide]

  • Formaat: Hardback, 698 pages, kõrgus x laius: 280x210 mm, kaal: 1510 g, 242 Tables, black and white; 340 Line drawings, black and white; 287 Halftones, black and white; 627 Illustrations, black and white
  • Ilmumisaeg: 23-Jul-2025
  • Kirjastus: Routledge
  • ISBN-10: 1032579951
  • ISBN-13: 9781032579955
Teised raamatud teemal:
  • Formaat: Hardback, 698 pages, kõrgus x laius: 280x210 mm, kaal: 1510 g, 242 Tables, black and white; 340 Line drawings, black and white; 287 Halftones, black and white; 627 Illustrations, black and white
  • Ilmumisaeg: 23-Jul-2025
  • Kirjastus: Routledge
  • ISBN-10: 1032579951
  • ISBN-13: 9781032579955
Teised raamatud teemal:

An Introduction to Applied Statistics offers a comprehensive and accessible foundation in applied statistics, empowering students with the essential concepts and practical skills necessary for data-driven decision-making in today's world.



An Introduction to Applied Statistics offers a comprehensive and accessible foundation in applied statistics, empowering students with the essential concepts and practical skills necessary for data-driven decision-making in today's world. Thoroughly covering key topics – including data management, probability fundamentals, data screening, descriptive statistics, and a broad spectrum of inferential analysis techniques – this indispensable guide demystifies statistical concepts and equips students to confidently apply statistical analysis in real-world contexts.

With a systematic, beginner-friendly approach, the author assumes no prior knowledge, making complex statistical foundations accessible to students from a variety of disciplines. Concise, digestible chapters build statistical competencies within a practical, evidence-based framework, minimizing technical jargon to facilitate comprehension. Now in its latest edition, the book is fully updated with SPSS v29.0 instructions and screenshots, ensuring compatibility with the most recent software developments. It also includes expanded content on addressing nonrandom sampling issues, such as case weighting, and delves into advanced topics like factor analysis, logistic regression, cluster analysis, and discriminant analysis, catering to the evolving needs of students and professionals alike.

An invaluable resource for introductory quantitative research methods courses in psychology, social sciences, business, and marketing, this text combines practical examples, online resources, and an approachable format to support both learning and application.

Key Features:

  • Concise Chapters Integrating Real-World Applications: Seamlessly blends statistical skills with practical scenarios, illustrating the flexible use of statistics in evidence-based decision-making.
  • Accessible Presentation: Offers practical explanations of statistical procedures with minimal technical jargon, enhancing understanding and retention.
  • Foundational Preparation: Early chapters are designed to equip students for advanced statistical procedures, building a strong foundational knowledge.
  • Step-by-Step SPSS Instructions: Provides detailed SPSS v29.0 guidance with screenshots to reinforce comprehension and hands-on skills.
  • Real-World Exercises with Answers: Includes practical exercises complete with solutions to facilitate active learning and application.
  • Comprehensive Instructor Resources: Offers extensive teaching support with chapter PowerPoints and test banks to enhance the educational experience.

Arvustused

Dr. Vieiras book is comprehensive, clear, and has great examples to illustrate the concepts. -- Clayton W. Barrows, Professor Emeritus of Hospitality Management, University of New Hampshire, USA

This is a textbook that attempts to bridge areas of content that are traditionally addressed independently: a. the conceptual knowledge of technical information; b. the real-world application of such technical knowledge; and c. a leading software tool that assists a researcher in applying the conceptual knowledge of technical information to a real-world context. Vieira seems to have used the feedback he received from his students over several decades to successfully build a bridge across these three content areas. This textbook and its approach are a welcome addition for making the process of learning statistics in the social sciences a lot smoother and a lot more relevant to students. -- Michael G. Elasmar, Associate Professor and Director of the Marketing Communication Research graduate program, Boston University, USA

Professor Vieira combines a straightforward approach to applied statistics with the most accessible statistical package, SPSS. His non-technical, clear, and concise writing style makes An Introduction to Applied Statistics a valuable handbook and reference for students and practitioners as well as an effective text for introductory statistics courses. -- John Lowe, Associate Dean Emeritus for Undergraduate Programs, Simmons University, USA

This book serves students being introduced to quantitative research as well as research professionals seeking to add to their statistical analysis and quantitative reasoning skills. Its emphasis on providing the reasons and prerequisites for using a statistical procedure make it valuable as a book-shelf reference as well as a textbook. Integration of relevant exercises to be carried out with SPSS enhances understanding of general statistical concepts with a body of hands-on experience, and that combination results in a very valuable skill set that will serve the reader well for years. -- James H. Watt, Professor Emeritus, University of Connecticut, USA Dr. Vieiras book is comprehensive, clear, and has great examples to illustrate the concepts. -- Clayton W. Barrows, Professor Emeritus of Hospitality Management, University of New Hampshire, USA

This is a textbook that attempts to bridge areas of content that are traditionally addressed independently: a. the conceptual knowledge of technical information; b. the real-world application of such technical knowledge; and c. a leading software tool that assists a researcher in applying the conceptual knowledge of technical information to a real-world context. Vieira seems to have used the feedback he received from his students over several decades to successfully build a bridge across these three content areas. This textbook and its approach are a welcome addition for making the process of learning statistics in the social sciences a lot smoother and a lot more relevant to students. -- Michael G. Elasmar, Associate Professor and Director of the Marketing Communication Research graduate program, Boston University, USA

Professor Vieira combines a straightforward approach to applied statistics with the most accessible statistical package, SPSS. His non-technical, clear, and concise writing style makes An Introduction to Applied Statistics a valuable handbook and reference for students and practitioners as well as an effective text for introductory statistics courses. -- John Lowe, Associate Dean Emeritus for Undergraduate Programs, Simmons University, USA

This book serves students being introduced to quantitative research as well as research professionals seeking to add to their statistical analysis and quantitative reasoning skills. Its emphasis on providing the reasons and prerequisites for using a statistical procedure make it valuable as a book-shelf reference as well as a textbook. Integration of relevant exercises to be carried out with SPSS enhances understanding of general statistical concepts with a body of hands-on experience, and that combination results in a very valuable skill set that will serve the reader well for years. -- James H. Watt, Professor Emeritus, University of Connecticut, USA

PART I: GETTING STARTED
1. An Introduction to Applied Statistics
2.
Statistics: Descriptive, Inferential, and Correlational
3. Data and Types of
Variables
4. SPSS 29 Statistics Data Management Basics Preparing Data for
Analysis; PART II: SAMPLING CONSIDERATIONS
5. Sampling Strategies
6. Sample
Size
7. Sources and Types of Statistical Error
8. Missing Data; PART III:
DATA SCREENING, DESCRIBING, AND PROBABILITIES
9. Describing Categorical
Variables
10. Basic Probabilities for Categorical Variables
11. The Concepts
of Data Distribution, Probability Values, and Signicance Testing
12. Numeric
Variables: Data Screening and Removing Outliers; PART IV: STATISTICAL
ANALYSIS Categorical Variables
13. Chi-Square Goodness of Fit Test: Comparing
Counts in a Single Variable With Two or More Categories
14. Chi-Square Test
of Independence: Comparing Counts Between Two Variables Each With Two or More
Categories
15. Chi-Square Test of the Same Sample: Comparing Counts of the
Same Sample Measured Twice Using a Categorical Variable Numeric Variables
16.
t-Test: Comparing a Single-Sample Mean to a Specic Value
17. t-Test:
Comparing Two Independent Samples Variable Means
18. Analysis of Variance
(ANOVA): Comparing More Than Two Independent Samples Means to Test for
Differences Among Them
19. Paired t-Test: Comparing the Means of the Same
Sample Measured Twice Using a Numeric Variable Association and Regression
20.
General Linear Model Repeated Measures: Comparing Means of the Same Sample
Measured More Than Twice Using a Numeric Variable
21. Bivariate Correlation:
The Association Between Two Variables
22. Linear Regression
23. Logistic
Regression Data Reduction
24. Factor Analysis: From Data Reduction to Latent
Variables
25. Classification Using Cluster Analysis; APPENDICES Appendix A:
Glossary Appendix B:
Chapter Statistical Exercise Solutions Appendix C:
Statistics Flow Chart
Edward T. Vieira, Jr., a professor of marketing and statistics at Simmons University's School of Management for over two decades, brings a wealth of experience as both an academic and a former marketing and business consultant to multinational corporations across North America and Europe. His extensive body of work includes numerous books, book chapters, and articles published in peer-reviewed journals and presented at international conferences.