How to Identify the Notation for the Mean and Variance of a Discrete Random Variable
How to Calculate Geometric Probabilities
How to Set Up a Hypothesis Test: Null versus Alternative

How SPSS (Statistical Package for the Social Sciences) Works

The developers of the Statistical Package for the Social Sciences (SPSS) made every effort to make the software easy to use. This prevents you from making mistakes or even forgetting something. That's not to say it's impossible to do something wrong, but the SPSS software works hard to keep you from running into the ditch. To foul things up, you almost have to work at figuring out a way of doing something wrong.

You always begin by defining a set of variables, and then you enter data for the variables to create a number of cases. For example, if you are doing an analysis of automobiles, each car in your study would be a case. The variables that define the cases could be things such as the year of manufacture, horsepower, and cubic inches of displacement. Each car in the study is defined as a single case, and each case is defined as a set of values assigned to the collection of variables. Every case has a value for each variable. (Well, you can have a missing value, but that's a special situation described later.)

Variables have types. That is, each variable is defined as containing a specific kind of number. For example, a scale variable is a numeric measurement, such as weight or miles per gallon. A categorical variable contains values that define a category; for example, a variable named gender could be a categorical variable defined to contain only values 1 for female and 2 for male. Things that make sense for one type of variable don't necessarily make sense for another. For example, it makes sense to calculate the average miles per gallon, but not the average gender.

After your data is entered into SPSS — your cases are all defined by values stored in the variables — you can run an analysis. You have already finished the hard part. Running an analysis on the data is much easier than entering the data. To run an analysis, you select the one you want to run from the menu, select appropriate variables, and click the OK button. SPSS reads through all your cases, performs the analysis, and presents you with the output.

You can instruct SPSS to draw graphs and charts the same way you instruct it to do an analysis. You select the desired graph from the menu, assign variables to it, and click OK.

When preparing SPSS to run an analysis or draw a graph, the OK button is unavailable until you have made all the choices necessary to produce output. Not only does SPSS require that you select a sufficient number of variables to produce output, it also requires that you choose the right kinds of variables. If a categorical variable is required for a certain slot, SPSS will not allow you to choose any other kind. Whether the output makes sense is up to you and your data, but SPSS makes certain that the choices you make can be used to produce some kind of result.

All output from SPSS goes to the same place — a dialog box named SPSS Viewer. It opens to display the results of whatever you've done. After you have output, if you perform some action that produces more output, the new output is displayed in the same dialog box. And almost anything you do produces output.

  • Add a Comment
  • Print
  • Share
blog comments powered by Disqus
How to Calculate Standard Deviation in a Statistical Data Set
Business Statistics For Dummies Cheat Sheet
Business Statistics: Modeling Asset Returns with Normal Distribution
How to Calculate a Confidence Interval for a Population Mean with Unknown Standard Deviation and/or Small Sample Size
How to Simulate Spinning Spinners on the TI-84 Plus
Advertisement

Inside Dummies.com