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Lawrence E.K., Adams K.A. Student Study Guide With IBM SPSS. Workbook for Research Methods, Statistics, and Applications

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Lawrence E.K., Adams K.A. Student Study Guide With IBM SPSS. Workbook for Research Methods, Statistics, and Applications
2nd Edition. — SAGE Publications, 2018. — 376 p. — ISBN: 978-1544318677.
Do you want more practice with research methods and statistics outside of class?
Then the Student Study Guide With IBM SPSS Workbook for Research Methods, Statistics, and Applications, Second Edition, is for you. Written by Kathrynn A. Adams and Eva K. Lawrence, this study guide accompanies the new second edition of Research Methods, Statistics, and Applications and provides instructions for performing statistical calculations in IBM SPSS along with additional exercises to reinforce concepts in the text. It follows the main text chapter by chapter to provide for easy assigning and studying.
Step-by-step directions for IBM SPSS Data Analysis and Interpretation are included with practice exercises to facilitate competence in using the program as well as interpreting and writing up results.
Answers to odd-numbered questions are provided so students can obtain quick feedback.
The Your Research section helps readers develop their own research topics.
Learning outcomes tied to relevant chapters in the text reinforce key concepts for review.
Thinking Like a Researcher
Building a Solid Foundation for Your Study Based on Past Research
The Cornerstones of Good Research: Reliability and Validity
Basics of Research Design: Description, Measurement, and Sampling
Describing Your Sample
Beyond Descriptives: Making Inferences Based on Your Sample
Comparing Your Sample to a Known or Expected Score
Examining Relationships Among Your Variables: Correlational Design
Examining Causality
Independent-Groups Designs
Dependent-Groups Designs
Factorial Designs
Nonparametric Statistics
Focusing on the Individual: Case Studies and Single N Designs
How to Decide? Choosing a Research Design and Selecting the Correct Analysis
Answers to Odd-Numbered Questions and Data Analysis Practices
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