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Essential First Steps to Data Analysis

Essential First Steps to Data Analysis
Scenario-Based Examples Using SPSS

December 2012 | 288 pages | SAGE Publications, Inc
Carol S. Parke's Essential First Steps to Data Analysis: Scenario-Based Examples Using SPSS provides instruction and guidance on preparing quantitative data sets prior to answering a study's research questions. Such preparation may involve data management and manipulation tasks, data organization, structural changes to the data files, or conducting preliminary analysis. Twelve research-based scenarios are used to present the content. Each scenario tells the "story" of a researcher who thoroughly examined their data and the decisions they made along the way. The scenario begins with a description of the researcher's study and his/her data file(s), then describes the issues the researcher must address, explains why they are important, shows how SPSS was used to address the issues and prepare data, and shares the researcher's reflections and any additional decision-making. Finally, each scenario ends with the researcher's written summary of the procedures and outcomes from the initial data preparation or analysis.

Section 1. The Sample
Module 1. Checking the Representativeness of a Sample
Module 2. Splitting a File, Selecting Cases, Creating Standardized Values and Ranks
Section 2. Nature and Distribution of Variables
Module 3. Recoding, Counting, and Computing Variables
Module 4. Determining the Scale of a Variable
Module 5. Identifying and Addressing Outliers
Section 3. Model Assumptions
Module 6. Evaluating Model Assumptions for Testing Mean Differences
Module 7. Evaluating Model Assumptions for Multiple Regression Analysis
Section 4. Missing Data
Module 8. Determining the Quantity and Nature of Missing Data
Module 9. Quantifying Missing Data and Diagnosing its Patterns
Section 5. Working with Multiple Data Files
Module 10. Merging Files
Module 11. Aggregating Data and Restructuring Files
Module 12. Identifying a Cohort of Students


Student Study Site

The student site features:

· Data Files: Each module is accompanied by data files that are used as examples in the analyses that are presented.

Having different research studies presented rather than using the same context throughout the text helps keep the material more interesting for the reader, as well as helping students generalize their learning across different research contexts.

Julie Alonzo
University of Oregon

The ‘real world’ scenarios captivate the reader but also provide pertinent context to see just how it relates to the content area at hand in each module.

Kyle M. Woosnam
Texas A&M University

The strength of the text is in how the author identifies the goals of the analysis under discussion and then steps the reader through the tasks necessary to realize those goals.

Claude Rubinson
University of Houston-Downtown

There are not many texts on data preparation in the field, so I believe this text would provide a unique contribution. …I agree wholeheartedly with the preface, that the other guides are simple “how-to” books that do not effectively connect students with real examples that can serve as a guideline in their own analysis experiences.

Carrie L. Cook
Georgia College & State University

A key strength of this text is that it focuses on the practical aspects of MANAGING research data rather than statistical programming or statistical analysis.

Amy B. Jessop
The University of the Sciences in Phiadelphia

I like that the book is written with cases/stories—I think that especially for counseling/psych students, these stories are going to help them contextualize the ideas more so than they would without these stories. I also like that the book give the students example write-ups. I think that is a priceless addition to any textbook about conducting statistical tests.

Karen H. Larwin
Youngstown State University
Key features
  • This is not simply a "how-to" book; instead, it is a practical book that focuses on critical thinking, allowing readers to understand why a researcher would want (or need) to take these initial steps to data analysis.
  • Written summaries at the end of each scenario provide readers with examples of how a researcher communicates and summarizes issues, decisions, and findings in words.
  • "Asides" from the researcher offer more information to the reader (for example, indicating why a particular choice was made or optional routes that could have been taken), allowing the reader to get further inside the researcher's thoughts, and adding additional nuances to the scenario.
  • Included SPSS tips help the reader understand the use of SPSS more fully. Certain procedures, and various options within them, are explained in further detail.
  • Learning objectives at the beginning of each scenario offer the reader an at-a-glance way to determine the major content covered within the scenario.
  • Extensions at the end of each scenario provide starting points for further discussion of the research or statistical concepts included in the scenario, or suggestions for additional practice of what was learned. These are useful both for the student and for the instructor.
  • A research-based approach to presenting the content places the data analysis and preparation in a real-world context. As an added benefit, this may create a springboard for specific discussions of students' and instructor's own data sets. This often leads to in-depth discussions and likely interactions about very practical issues.

Sample Materials & Chapters




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