1. Starting the Program
2. Data Files and Formats
3. Windows
   • Data (data view tab and Variables tab)
   • Output
   • Syntax
4. Menus and Dialogue Boxes

1. One row per independent source of data
2. One column per variable
3. Variable Name, Type, Width, Label, Value Labels, Scales of Measurement, etc...

1. Select
2. Split File
3. Weight Cases
4. Transform/Compute New Variable
5. Recode (into Same or into Different)

1. Frequencies
2. Descriptives

1. Histogram, Bar graph, Line Graph, etc...

What is SPSS?

SPSS is software that describes, displays, and analyzes data
SPSS can be accessed:
...in this classroom
...in the Schroeder 344 computer lab
...in the Milner Library computer lab
...at home if you buy SPSS at the bookstore

Visit the SPSS home page.

General Procedures in SPSS

Starting the Program

To start the SPSS Program: Click the "Start" button (lower-left hand of screen on Windows) Move cursor over to "Programs" & then over to "SPSS for Windows"



The program will open an empty datafile window. There are many other windows in SPSS, many of which will be described in this brief tutorial. The datafile window is where your data is stored.



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SPSS Data Files & Format

• Working with existing files
  If you already have a datafile with data stored in it you should open that datafile.

  To open data file dialog window: click on "File,"
  click on "Open" (This provides opportunity to acces previously created data files) double click on desired file

  

  To save a file you use the"Save" file and "Save As" commands

• Creating a new file
  To create a new file you'll need to know what variables are in your data set because you will need to define each one. You'll use the variable view window (part of the data window) to define your variables.

  A few things to note:

  There are two "views." The data view is the spread sheet into which you'll enter the data. The variable view is the spread sheet that specifies the characteristics of the varables in the data view (e.g., numbers or words or dollars, how many decimal places, etc.)

  Columns correspond to variables
  Rows correspond to cases (i.e. indivduals)

  SPSS will try to "format" the column based on the first thing that you type in. So

  • if you type in a number, but then later decide to use the column for words, then you'll need to go to the "variable view" to change the format to string
  • if you type in a word (e.g., a last name) that is short, SPSS will set the "width" of that column equal to the number of letters in the word. Then if for the next case you want to type in a longer word, you'll need to go to the "variable view" and change the setting.
  
  
• Importing files into SPSS
  insert something on importing text files (including those on the textbook CD-ROM)

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  SPSS Windows

  • Data (data view tab and Variables tab) - this is where you keep your data and specify the characteristics of your variables.
    The DATA VIEW
    The VARIABLE VIEW

  • Output - this is where the results of your analyses are presented
    
  • Syntax - this window allows you more control over the analyses that you run. Some things can't be done with the menus alone.
    
  • Chart Editor -- This editor allows you to edit charts and graphics. To get to this window, you double click on the figure in the output file.
    

Data Entry

This is generally just a matter of typing in the numbers. However SPSS does give you the option of three different ways of entering data: by variable, by case or subject, by block.
• Entering data by variable: click on the first empty cell under the first variable, type the number (or word), press the Down-arrow key or the Enter key. Continue until completed with that variable, and then scroll up to the top of the file and enter data for the next variable, etc.
• Enter data by case or subject: click on the first empty cell for the first subject under the first variable, then type the first number/word, press the Right-arrow key or TAB key. Continue until all data for that case is entered. Then scroll back to the first column and enter data for the next subject, etc.
• Enter data by block: To automatically switch to the next variable at the top of the file (when you finish entering data for one variable, or switch to the next case at the left of the file when you finish entering data for one subject or case), first highlight as many rows as you have subjects and as may columns as you have variables. This is done by clicking and dragging the mouse. When you have highlighted the block of cells that you want to enter, all cells will be highlighted except the upper left cell. In this cell you will enter the first variable. Type the number (or word) that goes in the upper left cell and press Enter if you want to go down (to enter by variable) or TAB if you want to go to the right (to enter by case or subject). Continue to input numbers until you reach the end of the row or column.

Tips for naming variables include

• Label all variables and values
• Make sure no value is out of range
• Let missing values be a "."
• Backup your file often
• It must be a maximum of 8 characters long
• It must begin with a letter, but after that any letters, numbers, a period, or the symbols @, #, _, or $ may be used. However, the name may not end with a period.
• All variable names must be unique; duplicates are not allowed.
• Variable names are not sensitive to upper or lower case.
• These variable names may not be used: all, ne, eq, to le, It, by, or, gt, and not, ge, with.

Changing variable characteristics

Once you have opened your file, click on the "Variable View" tab at the bottom of the window. This will take you to a similar looking spreadsheet. The difference is that each row in this spreadsheet contains the characteristics of each column in the other (data view) spreadsheet.

So the first row corresponds to the variable 'IDnumber', the second row to 'Name' (depending on how you set it up, it could also be last name or first name), the next to 'age', etc.

The columns on this spreadsheet are the characteristics of the variables. These include: name, type, width, decimals, labels, values, missing, columns, align, & measure.

Name - This is the name of the variable. Keep it to no more than 8 characters. You want to select a name for your variable that tells you what it is, so that you can identify it and differentiate it from other variables.

Type - This refers to the kind of data that is being inputed into the cells. So for example, income can be made a 'dollar' type.

Width - this is the number of characters that the data cell will allow within it. For example, for the 'names' variable, you'll want to set it pretty high, to fit the entire names in here. (note: this can also be set in the "type popup window" see above picture)

Decimals - this is the number of places after the decimal place. So for example, ID number doesn't need any numbers after the decimal place, so you can set this for zero. (note: this can also be set in the "type popup window" see above picture)

Labels - This allows you to give your variables a longer, more detailed name (not limited to 8 characters). For example, for income, you could enter a label like "income earned in 1999."

Values - these are VERY IMPORTANT for CATEGORICAL variables. When entering gender into the data file, you probably typed in Male and Female. While this looks fine, it isn't the way that gender should be inputed if you want to ever use the variable in an analysis. Gender is a categorical variable (nominal). SPSS requires that categorical variables be entered in as numbers.

So Male should be 1 and Female 2 (or visa versa, just be consistent). Then you can use the values to specify that 1 = male and 2 = female. Enter the number of the category in the 'value' field and the name of the category in the 'value label' field. Then click the 'add' button. You can get the data view spreadsheet to list categorical variables by their numbers or their labels by clicking the label button in the menu.

Missing - it isn't uncommon that for some individuals in your dataset, there may be some missing information. There are many different ways to deal with this problem. This is one way to let SPSS know how to treat missing data for each variable. For now, we will ignore this characteristic.

Columns - this specifies how wide you want the variable column to look in the data window.

Align - this specifies how the data should be aligned in a column. Your choices are centered, left, and right.

Measure - In this column, you should specify what scale of measurement the variable has been measured in. Note that interval and ratio have been combined into one "scale" type.

Data Manipulation

1. Sort The first thing that we can do is to "sort" the datafile.
   Step 1: To do this select "sort cases" under the "data" menu.

   

   Step 2: Then select "quiz1" for the sort variable field.

   

   By sorting the file you can begin to see the pattern of the distribution. For example, now it is easy to see what the lowest and highest scores are (now at the top and bottom of the column). However usually just sorting the variable isn't enough.
2. Select
3. Split File
4. Weight Cases
5. Transform/Compute New Variable

   Computing New Variables

   Creates a new variable and values for that variable based on an expression
   Computing scale totals is a common application
   Allows multiple scale items to be summed
   Individual items are not typically used in data analysis in psychology
   Choose Transform, Compute
   

   Quick overview of the Compute Process

   Enter the name of your new variable under "Target Variable"
   Enter numeric expression by typing or using calculator pad
   For quicker calculations, use "sum" function
   Separate variable names by commas
   If consecutive, use "to" (e.g., "var1 to var10")
   Use "mean" function to avoid problems with missing values
   Use it like "sum" function
   Multiply mean by number of scale items to retain original range of scores
   

   Conditional Transformations

   Purpose is to create new categorizations based on values of existing variables
   Recode Into Different Variables is one way to do this
   Compute a new variable is another way
   

   Transformation Cautions

   Remember to save data set so changes are saved on your file
   Never recode variables into same variable more than once or you'll get confused
   Be aware of how you're handling missing data
   

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   Transforming data

   Sometimes you may want to change the data. If you just need to change a few cells, then it may be easiest to do it one cell at a time. However, there are times when you may want to change a whole bunch of cells, or even entire variables. SPSS provides two options for doing this: recoding and computing.

   Recoding

   This allows you to change the way in which you have coded a variable. For example you may want to change all of your 1's and 2's to 0's and 1's. SPSS gives you two options:

   • Recoding into the same variables
   • Recoding into different variables.

     Choose Transform, Recode from menu bar
     

     Into same variables
     Into different variables (choose new name)
     

     Recoding Into Same Variables

     Assigns new values to a variable based on the old values of a variable
     Reverse scoring is a common application
     Many scales have items worded in two directions
     All items must be scored so they are in the same direction
     Indicate old and new values, then click "Add"
     Repeat process until all values are in box
     Click "Continue"
     

     Recoding Into Different Variables

     Assigns new values to a new variable based on the old values of a variable
     Select the old variable to be recoded
     Type in the name of the new variable & click "change"
     Indicate old and new values, then click "Add"
     Repeat process until all values are in box
     Click "Continue"
     

   
   

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   Analyze Menu

   • Almost all of the analyses that SPSS runs are controlled from the Analyze menu.

     

   • Frequencies
   • Descriptives

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     SPSS will create frequency distribution tables for you. Go to the "Analyze" menu, select "Descriptive statistics", and within that sub menu select "Frequencies".

     

     SPSS will then ask you for which variable you want the table for.

     

     For quiz 1 the frequency table output should look something like this:

     

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   Graphs Menu

   • Most of the graphs and charts may be accessed with the Graphs menu.
     • Bar charts: The bar chart is used to present frequencies of scale categories where the scale is usually a nominal/categorical measure.  The x axis shows each category (in no particular order because the scale does not have an inherent order) and the y axis represents the frequency of the categories. A bar is created for each category that is shown on the x axis and its height is raised to the point on the y axis that corresponds to the frequency of that category. There should be spaces between the bars so that they do not touch each other. An example would be the number of A,B, C, D, and F grades in a class or numbers of subjects representing different ethnic groups.
     
      

     Bar charts are also useful for presenting other summary statistics, like means, for different groups. For example suppose that we wanted to know the mean on quiz 1 by the three different sections.

     

     • Histogram: The histogram is used to present frequencies of scale scores where the scale is usually either an interval or ratio measure. The x axis shows the values of the variable and the y axis shows the frequency of each score. A bar is raised from the x axis to the appropriate frequency on the y axis for each scale value shown. The bars usually touch each other.  These look similar to bar graphs except they are used more often to indicate the number of subjects or cases in ranges of values for a continuous variable, such as the number of subjects or cases in ranges of values for a continuous variable. 
     The histogram of quiz 1 is basically just a picture of the frequency distribution table.

     In this case the histogram is a little different than you might expect after comparing it to the frequency distribution table above. Why?

      Because, the above histogram is based on a Grouped frequency distribution table of quiz 1. Go ahead and group scores 10 & 9, 8 & 7, 6&5, etc. and see if now the histogram looks as you'd expect it would.

     
      
      

     • Line plot: These may be used to display trends in data and multiple line charts are often used to demonstrate ANOVA interactions (we'll get to that later). 
       
        
     • Pie chart : These, like bar graphs, are another way of displaying the number of subjects or cases within different subsets of categorical data. 

     • Box Plots : These are based on percentiles and provide a good way to display the distribution of your data. 
     • Scatterplots : (simple and overly): These are a useful way to display the nature of the relationship between variables. 

     In a scatterplot, you would simply put your two variables into the Y and X axes (for example, maybe you have test scores on two quizzes). It generally doesn't matter which variable is specified to be on the x axis and which variable is specified on the y axis. The one shown below gets even a little more complicated in that different points are represented by different colors to indicate which section that person belongs to (of 3 course sections). You should notice that each point represents a case or person and the point shows the intersection of their two quiz scores.

     Your scatterplot should look like this.

     

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   If you have any questions, please feel free to contact me at jccutti@mail.ilstu.edu.