What we will do today
  • Today, we are not going to be talking about 
   any advanced statistics.
  • We will learn how to get to know our data and 
   prepare it for the analysis.
  • The example we are using is a dataset from 
   Qualtrics, but most of this applies to any 
   quantitative data. Feel free to use your own 
   data! 
             Overview
   1. SPSS Interface
   2. A First Look at the Data
   3. Measurement Levels
   4. Descriptive Statistics
   5. Data Cleaning 
    1. Select Cases
    2. Missing Values
    3. Recoding
    4. Computing
  6. General Tips
         Interface
  In the Data View, variables are columns and 
  rows are cases - respondents or in content 
  analysis, units of analysis
  This is more like a spreadsheet
                                  Interface
      In the Variable View, the rows are the variables 
      and the columns contain different kinds of 
      information about it:
      •   “Name” is a unique identifier
      •   “Label” is a more detailed description
      •   “Values” are labels for what the values mean
      •   “Missing” is the values that are not included in analysis
      •   “Type” tells SPSS how to use the data, if it is numeric or 
          string, which means the values are text (always check before 
          analysis)
      A First Look at the Data
  • First thing to do is to look at the variables, in 
   Variable View. 
  • Important questions:
   –Are the names and labels clear? 
   –What about value labels? Do you know which end 
    of the scale is high and which is low?
   –For experiments: Do you know which condition 
    the participant was in?