Using SPSS - University of Mary Hardin–Baylor

Download Report

Transcript Using SPSS - University of Mary Hardin–Baylor

SPSS Basics I
Dr. Isaac Gusukuma
Department of Social Work, Sociology and Criminal Justice
Dr. Trent Terrell
Department of Psychology
NOTE: Accessing Workshop Handouts
Log on to your computer.
Go to: http://answers.umhb.edu/technology/miscellaneous
Open and save to Desktop:
SPSS Instructions.pptx
SPSS Workshop – Data Analysis Guide.docx
Client Satisfaction Codebook.docx
SPSS Workshop 2012 Data.xlsx
SPSS Workshop 2012 Data.sav
Learning Objectives
•
•
•
•
•
Opening SPSS, Uploading and Saving files
Loading an Excel spreadsheet into SPSS
Setting up an SPSS data file
Conducting Frequencies
Conducting a Chi-square Goodness of Fit test
Opening SPSS
Note: UMHB is licensed for 30 users at one time.
• Click Windows “Start” button
• Click “All Programs”
• Click “IBM SPSS Statistics”
• Open “IBM SPSS Statistics 19”
IBM SPSS Statistics 19 Dialogue Box
If interested, Run
the Tutorial, later.
Click “Cancel”
Loading an Excel file into SPSS
1. Click the “Open data
document” icon in the
upper left corner
2. “Open Data”
dialogue box, go to
the location of the
excel file you want to
open.
3. Change “Files of
type” to “Excel”
4. Highlight the
Excel file you want
to open.
5. Click “Open”
6. “Opening Excel Data Source” dialogue box will open. Click “OK”
letting SPSS know that the first row in the Excel data file are the
variable names.
SPSS opens a “Data Editor” screen, like that below.
This is your Excel data converted to an SPSS data file.
First row in the Excel
spreadsheet becomes
the “header” or
variable name in SPSS.
• Note the red arrow.
There are two (2)
views, the Data View
and the Variable
View. Click the tabs
to see what these
two views look like.
• The next step is
setting up SPSS for
your data.
• You will use the
“Variable View” to
do this.
• In Variable View look at the column headings, “Name,” “Type,” etc.
• Click on a cell and you will be able to edit the information in it, e.g. if you don’t
like “id” as the name for the first variable, you can highlight the cell and type in
“Ident”
• Some cells (Type, Decimals, Values, Missing) have pull down menus.
• Click on the cells to get a feel for ways to edit the information for each variable.
• Using the Codebook, edit the description and values for the variable that
need the information. (The first couple variable will take some time, but
once you get the idea, it moves very quickly.)
• Verify the “Name” for each of your variables. They will be in the order that
you had them in the first row of your Excel data file.
• Under “Type” keep it “Numeric.” Note: that you can change to currency,
date, etc. that could be useful for other types of calculations.
• “Width” the default is “8” which is OK. With Excel width is “11” or “12”
• “Decimals” default is “2”
• “Label” enter the “Variable Label” from your Codebook. You may want to
later edit this label. Shorter labels (two or three words) are best.
• Using your Codebook, open the dialogue box for “Value Labels” (see
below). The numeric value is typed into the “Value” box, then type the
name of that response in the “Label” line.
• Click “Add” and it will move the number and label down, see “1=Poor”
• Click “OK” when all values are entered.
Note: If you have
variables with the
same Value Labels
(i.e., questions with
same Likert scale), you
can copy the value
labels from a
previously entered
variable and paste it
into other cells. You
can highlight more
than one cell and paste
to several at one time.
• “Missing Values” informs SPSS which numbers to ignore when doing
computations. By telling SPSS that “99” is missing, it will exclude this and
other Missing Values from statistical computations.
• Open the “Missing Values” dialog box. Click “Discrete missing values” and
enter up to three missing values. Common values used: 97, 98, 99 for “N/A”
(not answered/not applicable), “Don’t Know,” etc.
• Click “OK”
Your data
file is now
set up.
Frequencies
Junk in. Junk out.
How to tell if your data file is “clean” or if there
are data entry errors.
Cleaning up your data file to be “error free.”