SPSS Data management SPSS WORKSHOP 2.pdf

SPSS Data management SPSS WORKSHOP 2.pdf

1. DATA MANAGEMENT -
SPSS
BY
JOHN MICHAEL RAJ
BIO-STATISTICIAN
St John’s Medical College

2. BASIC STRUCTURE OF SPSS
SPSS has three windows for working with
data:
The Data Editor Window (.sav)
shows data in two forms:
Data view
Variable view
The Output Viewer Window (.spv)
shows results of data analysis
The Syntax Editor Window (.sps)
shows the syntax command script.
This is also where you can type
and run your own syntax
commands.
Note: Perform separate save procedures for the data editor (.sav), output
viewer (.spv), and syntax editor (.sps) windows.
.

3. GUIVS. SYNTAX
The GUI (graphical user-interface,
“gooey”) allows you to interact with
SPSS via images and buttons, rather
than text. You can “draw-down”
commands from menus at the top of
the window.
The Syntax window executes
commands that you enter as text.
Open a syntax window (File > Open >
Syntax), and type or paste text to call
functions.
Select specific sections of text and click
“Run Selection” to execute
commands.

4. DATA VIEW
Title Bar Menu Bar
Cell Value
Variable Name
Process Area
Tool bar

5. VARIABLE VIEW
Variable Name
Variable Type
Decimal Points
Variable Label
Value Labels
Missing Value
Specification
Variable Measure

6. :
ENTERING DATA IN SPSS
Variable View:
Data View:

7. LABELLING
▪VARIABLE LABEL
I.Descriptors for the
variables
II.Maximum 255
characters
III.Used in the output
▪VALUE LABEL
I.Value labels are
descriptors of the
categories of a
variable
II.Coding

8. MISSING VALUE
Many data sets have a few, or a
lot, of missing data points.
SPSS lets you account for missing
data in two ways:
▪system-missing (indicated by
one period in the data cell);
▪User-defined (specified by you,
User).

9. RECODE INTO DIFFERENT
VARIABLES
1.Select Transform → Recode into
Different Variables
2.Move the variable to be transformed to
the ‘Input Variable’ box.
3.Give new name to the variable to be
transformed and click change.
4.Click “old and new values” →Set the
values and click Add → Continue.
5.Click OK.
The new variable recoded
from an old variable is added
to the data
Recoding allows a researcher to
create a new variable with, for
example, a different set of
parameters

10. COMPUTING THE NEW VARIABLE
1.Select Transform →
Compute.
2.Enter the name of variable
to be computed as
‘Target Variable’.
3.Enter the expression of
new variable in
‘Numerical Expression’.
4.Click OK.

11. DATA ORGANIZATION:
•‘Sort Cases’ helps us to arrange the values in ascending / descending order
•‘Select Cases’ helps us to carry out analysis on cases selected based on
conditions
•‘Split File’ helps us to organize, compare and analyze data within groups based
on variable(s)

12. 1.Select Data → Select Cases.
2.Click ‘If condition satisfied’
3.Click ‘If’.
4.Type the numerical
expression.
5.Click Continue
6.Click OK.
SELECT CASES

13. SORT CASES
▪Sort cases by variables: Data Sort Cases
▪You can use Sort Cases to find missing.

14. SPLIT FILE
▪Go to Data → Split File
▪Move the variable which splits
the data
▪Select Compare groups and
Sort file by grouping variables
▪Click OK

15. MERGING DATASETS
▪Add new variables (merge)
▪Add new cases (append)
▪Both datasets must be open at the same time
▪Select one dataset to be the “master”
▪The second dataset will be the source of the new cases or new
variables
▪BOTH datasets must have the same unique case (or record)
identifier.