http://csass.ucsc.edu/short%20courses/index.html SPSS WORKSHOP What: Part 1 Handout for “Introduction to SPSS” Workshop Part 1 Topics: Data entry, including transforming and computing variables Frequency tables and descriptive statistics Simple graphs Contingency Table Analysis (lambda, gamma, chi-square, etc.) Part 2 Topics: T Tests ANOVA Correlation Regression Questions? Please email Yvonne Y. Kwan at [email protected]Written and presented by Yvonne Y. Kwan, UCSC CSASS Statistics Consultant
Transcript
http://csass.ucsc.edu/short%20courses/index.html
SPSS WORKSHOP!What: Part 1 Handout for “Introduction to SPSS” Workshop Part 1 Topics: Data entry, including transforming and computing variables Frequency tables and descriptive statistics Simple graphs Contingency Table Analysis (lambda, gamma, chi-square, etc.) Part 2 Topics: T Tests ANOVA Correlation Regression Questions? Please email Yvonne Y. Kwan at [email protected]
Written and presented by Yvonne Y. Kwan, UCSC CSASS Statistics Consultant
Introduction to SPSS - UCSC CSASS Workshop!1. Enter an abbreviated name for your variable—one that you can recognize and isn’t too long to keep
track of. SPSS variable names cannot have symbols or spaces. Let’s use “DIVISION” for our first variable.
! C. Under “Type,” leave it as numeric.
1. If you were to have a string variable that is not to be coded with a number, click on “Numeric” and a box with an ellipsis will appear. Click on the ellipsis and select “String.” You may indicate the number of characters your string variable can have. The character length is also indicated as “Width” in the main “Variable View” window.
2. If you were to have other variable types, you can select the other options: comma, dot, scientific notation, date, dollar, custom currency, and restricted numeric (integer with leading zeros). If these mean nothing to you, go ahead and ignore it.
D. Under “Width,” the default of “8” should be fine unless you think that your numerical data will have more than 8 numeric characters (example: 100,000,000; 200,000,000, 123,456,789). If you do, you can increase the width as necessary.
E. Under “Decimals,” the default of “2” should be fine unless you think that your numerical data will need more than two decimals. Increase as necessary (example: 1.234, 2.1234).
F. Under “Label,” you can enter the exact survey question or a brief description of the variable. You may use spaces and symbols. For example, “Student’s Division”
G. Under “Values,” you can enter the values associated with your numerical data. If your scores were interval/ratio you wouldn’t have to define the values because each score would be self-evident. (example: 33 means 33 years old)
! 1. Click on the box that says “None” and a box with an ellipsis will appear. Click on the ellipsis. A
“Value Labels” window will open. 2. In the “Value” window, enter a numeric code in your dataset that defines your variable. In our case,
we have 1 through 5. a) Value: 1
3. In the “Label” box, enter a description/definition for the numeric code a) Label: Arts. Press “enter” or click “Add”
4. Finish entering the value labels for all of your codes for that variable a) Value: 2; Label: Humanities. Press “enter” or
click “Add” b) Value: 3; Label: Physical & Biological
Sciences. Press “enter” or click “Add” c) Value: 4; Label: Social Sciences. Press “enter”
or click “Add” d) Value: 5; Label: Baskin Engineering. Press
“enter” or click “Add”
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Introduction to SPSS - UCSC CSASS Workshop5. If you have missing data, assign a numeric value to them. For our purposes, we have “Missing” and 1
“Not Applicable” values. You can decide on which values to assign, but for our purposes, we will use 88 for “Not Applicable” and 99 for “Missing.” a) Value: 88, Label: Not Applicable. Press “enter” or click “Add” b) Value: 99, Label: Missing. Press “enter” or click “Add” c) Click “OK.”
6. If you make a mistake or want to edit your labels, you may click on the label in the Value Labels box and then click remove. You may also relabel the numeric value and click change. Click “OK” to save the changes.
H. Under “Missing,” you can enter the values associated with missing data. 1. Click on the box that says “None” and a box with an ellipsis
will appear. Click on the ellipsis. A “Missing Values” window will open.
2. The default “No missing values” is selected. 3. Since we only have two types of missing values, click on
“Discrete missing values.” a) Enter 88 and 99 in the available fields.
4. If you were to have a range of missing values and one discrete missing value, select “Range plus one optional discrete missing value” and enter the values.
I. Under “Columns,” the default is 8. This represents how many columns wide you would like the variable to be presented in the “data view.” For our purposes, leave the default as 8 so the variable will appear easily.
J. Under “Align,” you can change the presentation so that the scores/values of the data for the variable are left/right justified or centered.
K. Under “Measure,” you can select “Nominal,” “Ordinal,” or “Scale.” For our purposes, student’s division is nominal.
L. Under “Role,” you may select “Input,” “Target,” “Both,” “None,” “Partition,” and “Split”. “Input are the variables that can be used as input( e. g., predictor, independent variable), target are the variables used as output or target(e.g. dependent variable), both are variables that can be used as input and output, and none are variables that have no role assignment. Partition are variables that can be used to partition the data into separate samples for training, testing and validation. Split is the variable type that is included for round-trip compatibility with IBM SPSS modeler. By default all variables are assigned the Input role.” We will keep to the default. 2
M. Repeat Steps B to L to enter all of your variables. 1. If you have variables that have the same codes, you may copy and paste. 2. Click on the values. Use the copy shortcut or go to “edit” and select “copy.” Click on the box you
want to paste the values into. Use the paste shortcut or go to “edit” and select “paste.” N. At the bottom of the screen, select “Data View” to enter the scores in your dataset. O. Select Row 1 and “DIVISION” (which represents the first variable you entered). Each row represents
the scores/responses for one respondent. (Row 1 is respondent 1; Row 2 is respondent 2; etc.) Each column represents the scores for the variables.
P. Enter all of the scores for our dataset.
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! Note: SPSS interprets a period as missing data. This is important if you decide not to use a discrete value for missing 1
data or if you want to use a dataset from a different source (e.g., from a data bank).
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Introduction to SPSS - UCSC CSASS WorkshopII. Transforming Variables 3
A. Recode into Different Variables 1. You ALWAYS want to recode your variables in
different variables NOT same variables…just in case you make a mistake, you don’t want to save over your original dataset.
2. Let’s recode the GENDER variable into a dummy variable a) 0: non-woman; 1: woman
3. Click…“Transform” —> “Recode into Different Variables” 4. Select the variable you want 5. Click on the arrow to move it over to the “Numeric Variable —> Output Variable:” box. 6. On the right side under “Output Variable,” enter the name and label for the new variable you are
recoding. Since we are interested in recoding GENDER, we will use, Name: GENDERDUM and Label: Dummy Variable for Gender (woman) a) DO NOT CLICK “Change” YET.
7. Click on “Old and New Values”
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! These functions are important and useful for a multitude of reasons, including creating variables for interaction 3
(ANCOVA and Regression with Interaction).
Introduction to SPSS - UCSC CSASS Workshop8. Recall…woman is coded as 1, man is coded as 2, and other is coded as 3. 9. Under Old Value, for “Value,” enter 1. Under New Value, select “Copy old value(s)”. We want to
keep woman coded as 1. Click “Add.” 10. Under Old Value, select “Range.” Enter 2 through 3. Under New Value, for “Value,” enter 0. Click
“Add.” 11. If you have missing values, make sure you copy those values too. Take the same steps as II.A.9. Click
“Add.” Click “Continue.” 12. Now, click “Change” under “Output Variable.” 13. Click “OK” 14. The newly created variable will appear in the Data and Variable Views. 15. Make sure you go back to Variable View to define the labels for the new variable.
a) Value: 0; Label: Non-woman b) Value: 1; Label: Woman c) Value: 88; Label: Not Applicable d) Value: 99; Label: Missing
16. You can run a frequency table to make sure that everything transformed correctly. Instructions for running frequency tables are in Step III.
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Introduction to SPSS - UCSC CSASS WorkshopB. Compute a Variable Using Transformations or Computations
1. Let’s create a scale called “SUPPORT” that represents an index for support for graduate students in the program.
2. The new variable SUPPORT is calculated by adding JOBMKT and FUNDING.
3. Click…“Transform” —> “Compute Variable”. A “Compute Variable” window will appear.
4. Under “Target Variable,” enter the new variable name: SUPPORT 5. Click “Type & Label.” Under “Label,” enter “Students’ Support Index.”
a) Keep the variable “Type” as “Numeric.” b) Click “Continue”.
6. Select first variable you want to compute/transform. Select JOBMKT. Click the arrow to add the variable into the “Numeric Expression” box.
7. Click the “+” function. 8. Select the variable you want to add to the first variable. Select FUNDING. Click the arrow to add
the variable into the “Numeric Expression” box. 9. Click “OK”. 10. Note that the index goes from 2 to 10. 2 represents low support and 10 represents high support.
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Introduction to SPSS - UCSC CSASS WorkshopC. Compute a Variable Using Conditions
1. Let’s create a new variable called “MENMNT” that represents responses to MENTOR for only those who identify as “men.”
2. Click…“Transform” —> “Compute Variable”. A “Compute Variable” window will appear.
3. Under “Target Variable,” enter the new variable name: MENMNT 4. Click “Type & Label.” Under “Label,” enter “Men students’ views on mentorship”
a) Keep the variable “Type” as “Numeric.” b) Click “Continue”.
5. Click the “If ” button. a) Select “Include if cases satisfies condition:” b) Select the variable “GENDER,” click the arrow to move it over to the box. Click “=”. Enter/
click 2. This creates the condition that the new variable only includes those who are men. Men students are coded as 2.
c) Click “Continue”. 6. In the main window, select the MENTOR variable. Move it over to the “Numeric Expression” box. 7. Click “OK”. !
!
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Introduction to SPSS - UCSC CSASS WorkshopIII. Descriptive Statistics
A. Produce Frequency Distributions 1. Click…“Analyze” —> “Descriptive Statistics” —> “Frequencies”. A “Frequencies” window will
appear. 2. Select/highlight variables you want 3. Click on the arrow to move them over to the
“Variable(s):” box. You may also drag them over.
4. Click “Statistics” 4
a) You may select any of the statistics for “Percentile Values,” “Central Tendency,” “Dispersion,” or “Distribution” you would like.
5. Click “Charts” a) You may select “Chart Type” and “Chart Values” if you would like. b) We will also go over more graphs later.
6. Click “Format” if want to order the data in the output. Click “Bootstrap” if you want to bootstrap and have those capabilities. 5
7. Click “OK” 8. The output will appear in the “Output” Window.
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! WARNING: SPSS will order whatever you ask it to. Even though you can’t get 4
meaningful statistical values for nominal variables, SPSS will do it anyway.! Depending on your version of SPSS and whether or not you’ve acquired/purchased the bootstrapping add-on, you may 5
or may not be able to do bootstrapping.
Introduction to SPSS - UCSC CSASS WorkshopB. Produce Descriptives for Ordinal and Scale variable—without Frequency Distributions
1. Click…”Analyze” —> “Descriptive Statistics” —> “Descriptives”. A “Descriptives” window will appear.
2. Select/highlight variables you want 3. Click on the arrow to move them over to the
“Variable(s):” box. You may also drag them. 4. Click “Options” and select statistics you want to order. !
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Introduction to SPSS - UCSC CSASS WorkshopC. Graphical Analysis
1. Click…“Graphs” —> “Chart Builder” 2. A Chart Builder Warning will appear. You should have already
properly defined your variable (set the correct measurement), so you can select “OK.” A “Chart Builder” window will appear.
3. Bar Chart a) Under “Gallery,” select “Bar.” Types of bar charts will
appear. Select the one you want to use. For our purposes, we will use the simple bar chart. Drag the simple bar chart to the giant white box.
b) An “Element Properties” box will appear.
c) If I wanted a simple bar chart of the count for DIVISION…under “Variables,” drag DIVISION to the X-Axis. Click “OK”. (1) To insert a title or to edit the
bar chart, double click the chart after it appears in the Output window.
(2) A “Chart Editor” window will appear.
(3) Select “Options” from the tool bar —> “Title” !
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Introduction to SPSS - UCSC CSASS Workshop4. Clustered Bar Chart
a) Under “Gallery,” select “Bar.” Types of bar charts will appear. Select the one you want to use. For our purposes, we will use the simple clustered bar chart. Drag the simple clustered bar chart to the giant white box.
b) An “Element Properties” box will appear. c) If I wanted a clustered bar chart of GENDER clustered by DIVISION…under “Variables,”
drag DIVISION to the X-Axis. Drag GENDER to “Cluster on X: set color.” Click “OK”.
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Introduction to SPSS - UCSC CSASS Workshop5. Scatter/Dot plot
a) Under “Gallery,” select “Scatter/Dot.” Types of bar charts will appear. Select the one you want to use. For our purposes, we will use the simple scatterplot. Drag the simple scatterplot to the giant white box.
b) An “Element Properties” box will appear. c) If I wanted a scatterplot for AGE and YEAR…under “Variables,” drag AGE to the X-Axis.
Drag YEAR to the Y-Axis. Click “OK”. d) If you want to add a regression line, double click the scatterplot that appears in the Output
Window, click “Elements” from the tool bar —> “Fit Line at Total.”
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Introduction to SPSS - UCSC CSASS Workshop!D. Produce Z Scores for scale variables (sometimes we also standardize ordinal variables…do whatever is
accepted in your discipline) 1. Click…”Analyze” —> “Descriptive Statistics” —> “Descriptives”. A “Descriptives” window will
appear. 2. Select/highlight variables you want. For our case,
we will use “AGE” 3. Click on the arrow to move them over to the
“Variable(s):” box. 4. Click the “Save standardized values as variables”
box. 5. The descriptives will appear in the Output. 6. A new variable called “ZAGE” will appear in the
Variable and Data Views. These values are the standardized Z scores for AGE.
7. If the variable has a missing value, no value will be produced.
!
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