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Agenda. Organizing Data Coding Data reduction Exercise: Managing data in SPSS. Coding. Moving from questions posed to respondents to data for analysis Assigning codes (usually numbers) to raw research materials Questionnaires Closed-ended responses Open-ended responses Archival material.

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Presentation Transcript
agenda
Agenda
  • Organizing Data
    • Coding
    • Data reduction
  • Exercise: Managing data in SPSS
coding
Coding
  • Moving from questions posed to respondents to data for analysis
  • Assigning codes (usually numbers) to raw research materials
    • Questionnaires
    • Closed-ended responses
    • Open-ended responses
    • Archival material
slide4
Each column is one variable

Each row is one case (e.g., respondent)

data reduction
Data reduction
  • Reducing information available in raw data by grouping respondents into fewer categories
    • Grouping age into ranges (under 18, 19-29, 30-39, etc.)
  • Reduced data do not convey as much information
    • Knowing someone is “under 18” does not convey actual age
why reduce data
Why reduce data?
  • May be easier to analyze
  • May be appropriate to given research question
    • Values above or below some threshold (e.g., a poverty line)
    • Type concepts (e.g., young, middle, older age)
  • May be only reasonable approach
    • Content analysis
    • Distribution strongly suggests categories
reliable coding
Reliable coding
  • Use considerable care
  • Minimize number of “translation” steps
  • Double check all entered data
    • Random record checks
    • Double-entry
    • Close scrutiny of distributions, missing data
  • Remember: Noisy data will increase

Type II error

managing data
Managing data
  • Most use specialized computing packages (SPSS, SAS, BMDP, etc.)
    • Data entered into matrix
    • Variables and values fully labeled
    • Data re-coded as necessary for analysis
    • Data carefully inspected for univariate properties
  • Introduction to SPSS
    • Workshops: Organizing data, descriptive statistics, measuring relationships
    • Sample data available on course website
for thursday
For Thursday
  • Descriptive statistics
  • Norusis
    • Review Ch. 4-5
    • Read Ch. 6
  • Workshop schedule
    • Today (organizing data, descriptives)
    • None Thursday
    • Tuesday, Nov. 29 (descriptives, relationships)
    • Thursday, Dec. 1 (“third variables”)
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