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.

Module 9: Quantifying Missing Data and Diagnosing Their Patterns

Module 9: Quantifying Missing Data and Diagnosing Their Patterns

Data Files for This Module

  • module9_autism.sav
  • module9_autism_final.sav

Key Learning Objectives

The student will learn to

  • quantify the missing data in cases, in variables, and across the entire data set
  • evaluate the nature and pattern of missing data by creating and examining a variable that contains dummy codes
  • use statistical procedures to evaluate the relationship between the ...
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