SPSS On-Line Training Workshop |
 In this Tutorial: defining variables creating templates
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Menus Available in the Data Editor Window The data editor window is the default window when you run SPSS. The data worksheet works just like a spreadsheet, where a column represents a variable and a row represents a case or an observation. Many tasks in SPSS are performed by selecting appropriate "Pull-down" menus. The menus in the Data Editor window include:
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In this on-line
workshop, you will find many movie clips. Each movie clip will demonstrate some specific
usage of SPSS. These clips can be accessed either by clicking on their names, above,
or by clicking on the camera 
icon
in the tutorials below.
Data Input/Save (File Menu)
There are four ways for data input in SPSS. These are provided under the File Menu. By clicking on the File Menu in the Data Editor Window, you can select one of the following four ways of data input:
 | New: An empty worksheet will appear for users to enter data
into the worksheet. This works just like entering data into a spreadsheet.
click here to watch:
Getting Started
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| Open: Allows users to open an existing SPSS data file (with
extension .sav) that is saved in a floppy or hard drive. It also allows users to
open many other types of files such as text file (with extension .dat or .txt), or an
Excel file saved in version 4.0 or earlier.
click here to watch: Reading Data Files
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| Database Capture: Allows users to capture data from various
database and Excel files saved as version 5.0 or later. It allows users to select
variables to be analyzed.
click here to watch:
Reading Data Files
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| Read Text Data: Allows users to read text file with
extension (.dat or .txt).
click here to watch:
Reading Text Data
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To save a newly created data set, go to the file menu, then follow the
instructions to save your data.
To save and update an existing data set, simply move the cursor to File Menu and
select save or save as.
| Select save to keep the existing name |
| Select save as to change to a different name |
Once a data set is saved using Save or Save As, the data is saved as an SPSS file with the extension .sav. To open the .sav file later, simply use Open in the File Menu. Note that you can save your data in text or ASCII format by selecting the appropriate file type.
Defining Variables and Value Labels (Data Menu)
A. How to define Variable labels, and Value Labels for SPSS 9.0 :
One important step in creating an SPSS data set is to define variable labels and value labels for a given variable. The following movie clip will demonstrate how to create variable labels and value labels, and how to create templates for variables having the same value labels for SPSS 9.0.
In SPSS 9.0, to define a variable, assign value labels or make templates, you must first click on the menu item "Data". From the resulting submenu, you can choose to define the variable or make a template. (Templates can be used to define multiple variables.)
click here to watch: Defining Variables
B.
How to define
variable labels and value labels in SPSS 10.0:
Once the data set is created, and the Data Editor Window
is active. The Menu Bar at the bottom of the window shows two menus: Data
View and Variable View.
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Click on the Data View, you see the data sheet. | ||||||||||||||
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Click on the Variable View, you see a sheet of information defining each variable. This includes
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Creating Templates for Value Labels in SPSS 9.0(Data Menu)
(NOTE: In SPSS 10.0, you can easily do this by copy and paste in the Variable View Window. There is no need for creating such templates.)
Often data consists of many variables which share the same value labels. For an example, the survey of information technology conducted in the Spring, 1999 at CMU consists of fourteen items concerning the level of difficulty when using information technology in a classroom. The choices are
1. No problem at all
2. Some problem
3. Moderate
4. Serious problem
5. Not Applicable
The data recorded for the items are numerical, as shown above. To define value labels for each item, one can define the value labels for each item, separately. Alternatively, one can create a Template that consists of the corresponding value labels, and then assign the value labels defined in the Template to all the items. This is very handy if you have many variables that share the same value labels.
click here to watch: Defining Variables
Split File/Select Cases (Data Menu)
In data analysis, we sometimes need to analyze data for each category of a variable. For example, we may want to compute descriptive statistics for Male and Female groups, separately. In SPSS, before the analysis can be performed, you SPLIT the file by the variable GENDER. This is done by going to "Data" (on the menu bar) and select SPLIT FILE.
Sometimes, you would like to select only a specific group of cases for analysis. In SPSS, before the analysis can be performed, you SELECT CASES. This is done by going to "DATA" (on the menu bar) and then SELECT CASES.
click here to watch: Select / Split files
Sort Cases/Merge Files/Transpose (Data Menu)
Sorting cases is a common tool in data manipulation, where data are sorted based on key variables.
Merge Files allow users to merge two existing SPSS files (with extension .sav) by adding cases or adding variables. In pre/post test data, or data that is collected over several time periods, merge files by variables is handy. In situation where data are entered by more than one individual, merge files by cases will be useful.
Transpose is used when we need to make variables (in columns) as cases (in rows) and make cases as variables.
click here to watch: Sort / Merge Files
Variable Transformation (Transform Menu)
Variable transformation is used very often in data analysis. This includes not only data transformation of an existing variable such as log transformation, but also include creating new variables, redefining values of a variables and so on. Two most commonly used tools are Compute and Recode under the Transform Menu.
Compute allows users to create a new variable or modify an existing variable. Recode allows users to redefine the values of an existing variable, and save into the same variable column or save as a new variable. This is particularly useful when we need to collapse categories, or to transform a continuous variable into a categorical variable. For example, in the Technology Survey study, the level of difficulty are defined from 1 to 5 with 5 being Not Applicable. When analyzing the level of difficulty, we need to redefine the value 5 as missing; otherwise, the average level of difficulty is not appropriate. To do this, we go to Transform Menu, select Recode and choose Recode into different variable.
click here to watch: Transformation
Statistical Techniques Available in SPSS (Analyze Menu)
SPSS is a comprehensive statistical package. It is capable of performing many statistical data analyses and report the summary. The procedures available in SPSS are under the Analyze Menu. The results from performing any analysis are displayed in the OUTPUT Editor Window. Details about how to manipulate the Output Editor is given in the Output Editor Window page. In this training workshop, we will not be able to cover all of the statistical techniques available in SPSS. Instead, we will focus on the following:
| Reports |
| Descriptive statistics, frequency, crosstabulation |
| Two sample comparison - independent t and paired t |
| Correlation and regression |
| Analysis of variance |
| Repeated Measure Analysis |
| Nonparametric methods |
| Factor analysis |
| Reliability analysis |
Each of these techniques will be demonstrated using projects. Details about the projects and corresponding movie clips are given in the Project page. The following clips will give you a quick glance of some data analysis procedures:
click here to watch: Overview of SPSS
click here to watch: Getting Started
click here to watch: Statistical Procedures
Graphic Tools (Graph Menu)
Graphic tools are always important in data analysis. SPSS has most of the common tools needed for data analysis. Under the Graph Menu, you can find two types of graphical tools.
| Interactive Graphs can be modified interactively. |
| Regular graphical tools can be modified as well. |
There may be some difference in appearances between these two types of graphics for the same type of graph. For example, you will see Bar chart in both Interactive Graph and Regular Graph. The appearances are somewhat different. Try both to see which one is best for your analysis.
The graphs are kept in the Output Editor Window. Details on how to manipulate the graphs are given in the Output Window and Chart Editor Window .These windows can be selected as the Active window by going to "Window" (on the menu bar) and select the intended editor window. The following clips will give you a quick glance of graphical tools:
click
here to watch: Overview of SPSS
click here to watch: Getting Started
©1999 Dr Carl Lee, Dr Felix Famoye, Central Michigan University. Joyce Sharp, student assistant. All rights reserved.
