SPSS Cheat Sheet

SPSS Cheat Sheet

This contains some of the most common SPSS procedures for basic data analysis.

Data Cleaning

Missing Data Counts

  1. Analyse >> Descriptive Statistics >> Frequencies
  2. Select the variable(s)
  3. Click Continue and then OK

Missing data counts will be at the top of the resulting output.

Edit Variable Name

  1. Transform >> Recode into Same Variables...
  2. Select the variable to transform and move it into the right column.
  3. Click Old and New Values...
  4. Under Old Value, enter either a specific value you would like to replace or a set of values you would like to replace.
  5. Under New Value, enter what the replacement value should be.
  6. Click Add under New Value.
  7. Click Continue and then OK.

Create a Variable

  1. Transform >> Compute Variable...
  2. Click Type and Label... to set the variable type, then click Continue.
  3. Enter the value for the variable. If it is a string, include the value in quotes.
  4. Or just enter a formula for the variable based on the existing variables.
  5. Click“OK.

Delete a Variable

  1. Right-click on the column header
  2. Click Clear.

NOTE: This does not produce a syntax in the Output window. The syntax for deleting a variable is here, in case you are saving your syntax:

  • DELETE VARIABLES [list of variables, separated by spaces].

Drop observations based on some condition (Keep observations meeting the opposite)

  1. Data >> Select Cases... >> Select If condition is satisfied >> If...
  2. Enter the condition based on which observations you would like to keep, then click Continue.
  3. Select Delete unselected cases.
  4. Click OK.

You can specify multiple conditions at the same time by separating them with AND or OR.

Merging datasets

  1. Data >> Merge Files >> Add Variables...
  2. Note that the datasets you are merging must already be saved as SPSS (.sav) format files. In addition, the variables you are matching on must have the same name across datasets.
  3. Select An external SPSS statistics data file, browse for your file, and select it.
  4. Select Match cases on key variables, click on the matching variable, and add it to Key Variables.
  5. Click OK.

Appending datasets

  1. Data >> Merge Files >> Add Cases...
  2. Note that the datasets you are merging must already be saved as SPSS (.sav) format files. In addition, the variables you are matching on must have the same name across datasets.
  3. Select An external SPSS statistics data file, browse for your file, and select it.
  4. All variables already in both datasets will appear in Variables in New Active Dataset, and variables not in both datasets will be in Unpaired Variables. Move all unpaired variables you want into the right column.
  5. Click OK.

Descriptive Statistics

Central tendency: mean, median, and mode (for continuous variable)

  1. Analyze >> Descriptive Statistics >> Frequencies
  2. Select the continuous variable(s)
  3. Uncheck Display frequency tables
  4. Click Statistics... and check the desired central tendency measures
  5. Click Continue and then OK

Central tendency: mode and frequency table (for categorical variable)

  1. Analyze >> Descriptive Statistics >> Frequencies
  2. Select the categorical variable(s)
  3. Check Display frequency tables
  4. Click Format and select Descending counts
  5. Click Continue and then OK

The top item in the frequency table is the mode. Note that if multiple categorical variables are selected, a separate frequency table will be created for each variable.

Variability: Standard deviation, variance, and range (for continuous variable)

  1. Analyze >> Descriptive Statistics >> Descriptives
  2. Select the continuous variable(s)
  3. Click Options and select the desired measures of spread
  4. Click Continue and then OK

Common Analyses

Correlations

Pearson correlation:

  1. Analyze >> Correlate >> Bivariate
  2. Select Pearson under Correlation Coefficients box, select the variables, click OK

Spearman correlation coefficient:

  1. Analyze >> Correlate >> Bivariate
  2. Select Spearman under Correlation Coefficient box, select the variables, click OK

Linear Regression

Simple Linear Regression:

  1. Analyze >> Regression >> Linear
  2. Enter IV and DV, Click OK

Multiple Linear Regression:

  1. Analyze >> Regression >> Linear
  2. Select IVs and DV, Click OK

T-Test

Single-Sample T-test:

  1. Analyze >> Compare Means >> One-Sample T-test
  2. Enter variables, click OK

Independent Samples T-test:

  1. Analyze >> Compare Means >> Independent Samples T test
  2. Enter DV (Test Variable) and IV (Grouping variable), Define Groups, and enter the values of the two levels of the IV, click continue, click OK

Paired Samples T-Test:

  1. Analyze >> Compare Means >> Paired Samples T Test
  2. Click on two paired variables to move to Current Selections area, then click right arrowto move to Paired Variables Section, Click OK

ANOVAs

Oneway ANOVA:

  1. Analyze >> Compare Means >> One-Way ANOVA
  2. Enter IV in Factor box, Enter DV to Dependent List box, click Options >> Descriptive to get means in output Click continue, click OK

Factorial Anova (2x2, 2x2x3, etc.):

  1. Analyze >> General Linear Model >> Univariate
  2. Select DV for Dependent Variable blank and IVs for the Fixed Factors box, click OK

Repeated Measures ANOVA:

  1. Analyze >> General Linear Model >> Repeated Measures
  2. Enter factors and number of levels >> click Add >> once all factors are entered click define
  3. Define variables using the arrows, click OK

Mixed-Design ANOVA:

  1. Follow same steps as repeated measures
  2. Add between-subjects factor to “Between-Subjects Factor” box, click OK
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