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SPSS Step by Step Summary Year 1 and 2 Psychology Erasmus Uni
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All SPSS-Steps needed for Year 1 and 2 in Psychology Erasmus University. SPSS step by step
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SPSS – Step by Step Summary - Alphabetic Order – Bachelor 2 – Psychology – Erasmus UniBar charts
1 – Graphs
2 – Legacy Dialogs
3 – Bar
4 – Choose Simple Bar Chart, Clustered Bar Chart or Stacked Chart
5 – Bring variable to ‘Category Axis’
6 – For Clustered Bar Chart or Stacked Chart, bring second variable to ‘Define
Clusters by’
Bivariate/correlation: compare two variables, look at correlations
1- Analyse
2- Correlate
3- Bivariate
4- Drag variables you want to correlate to 'Variables'.
5- Correlation Coefficient: select 'Pearson' - OK.
6- If needed: double click on output and
open Pivot -Pivoting trays.
7- Place stats column in the Green Layer.
Calculate Mean, S.E. of the mean
1-Transform
2 - Recode into Different Variables
3 - Select original variable in the large field
4 - Choose name for new variable under 'Output variable'
5 - Click 'change', and Old and New Values.
6 - Don't forget to click 'Add' every time.
7 - OK – OK
Compare means: comparing groups on descriptive St. (mean, medians, SD)
1- Analyse
2- Compare Means
3- Means
4- Dependent list – place quantitative variables
5- Layer 1 of 1: put the groups you want to compare with
6- Options: Select descriptive statistics that you want, click ‘next’
if want to ad other categorical value
7- Output Report compares descriptive statistics
Compute variables: if you want to transform values in your data set, to add,
multiply, divide, data (express age in months instead of years)
1- Transform
2- Compute variable
3- Type in new title in Target variable
4- Choose variable and move to Numeric Expression
pg. 1
, 5- In case of change from months to years: type in *12 behind variable
6- Click ok – end of Data view: result of transformation
Count values within cases: count how many values occur within a case (with
multiple variables with similar values) (e.g., how many people scored 4)
1- Transform
2- Count values within cases
3- Target variable is the new variable/the count
4- Target label is more descriptive
5- Choose variable(s) to count (e.g., for each variable how many 4)
6- Define value: what value do you want to count?
Range: between 0 through 1 or just a value and add
7- Continue – OK
8- Data view: at the end there’s a new variable that added all the numbers
Chi square for goodness of fit: test if distribution on a single categorical
variable matches our expectation.
1- Analyse
2- Nonparametric Tests
3- Legacy Dialogues
4- Chi-square
5- Drag variables to 'Test Variable List'
6- If needed: go to 'Expected Values' and select 'Values' e.g., if expecting 20% to
be unhappy and 80% to be happy, first enter 20 - then add - then 80 - then add
once more.
7- OK.
Crosstabs/Chi-Square test of independence: can be used to display
relationship between
2 categorical variables (ordinal & nominal) (calculates %)
1- Analyse
2- Descriptive statistics
3- Cross tabs
4- Add variable in row and in column
5- Click cells – click observed, row, column and total
6- Always click on Statistics →Chi-square and then Continue
each time.
7- Always click on Cells → Percentages → Select Row or Column, then Continue and
OK each time.
8- Output gives cross tab
In Chi-square table, only look at the Pearson Chi-Square statistics.
Descriptive statistics:
1- Analyse
2- Descriptive statistics
3- Descriptive
pg. 2
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