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



February 2013 | 288 pages | SAGE Publications, Inc
A companion website is available for this text

The purpose of this book is to provide instruction and guidance on preparing quantitative data sets prior to answering a studyÆs research questions. Preparation may involve data management and manipulation tasks, data organization, structural changes to data files, or conducting preliminary analysis such as examining the scale of a variable, the validity of assumptions or the nature and extent of missing data. The ôresultsö from these essential first steps can also help guide a researcher in selecting the most appropriate statistical tests for his/her study. The book is intended to serve as a supplemental text in statistics or research courses offered in graduate programs in education, counseling, school psychology, behavioral sciences, and social sciences as well as undergraduate programs that contain a heavy emphasis on statistics. The content and issues covered are also beneficial for faculty and researchers who are knowledgeable about research design and able to use a statistical software package, but are unsure of the first steps to take with their data. Increasingly, faculty are forming partnerships with schools, clinics, and other institutions to help them analyze data in their extensive databases. This book can serve as a reference for helping them get existing data files in an appropriate form to run statistical analysis. This book is not a replacement for a statistics textbook. It assumes that readers have some knowledge of basic statistical concepts and use of statistical software, or that they will be learning these concepts and skills concurrently throughout the course. SPSS was chosen to illustrate the preparation, evaluation, and manipulation of data. However, students or researchers who do not use SPSS will benefit from the content since the overall structure and pedagogical approach of the book focuses heavily on the data issues and decisions to be made.

 
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

Supplements

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.

Sample Materials & Chapters

TOC

MODULE 1

MODULE 5


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