Transitioning from Statview

These are some tips to help you transition from Statview to SPSS.These were originally written as footnotes to a previous version of this guide, put throughout the guide; here they are all in one page. Apologies if a few are confusing because they are missing their reference points.

Note 1 - Introduction to Footnotes

Certain aspects of SPSS can be confusing if you are used to using StatView. Your habits will dictate that you should do things the StatView way, which might make certain tasks in SPSS LESS intuitive than they would be for someone who has a clean slate. Check these notes for information about particularly confusing differences between the two programs.

Note 2 - The Data Editor

In Statview, you are accustomed to seeing one dataset which includes all the information. That is, each variable has a column in which you specify everything about the variable at the top, then enter the data below. In SPSS, these two functions are separated into the two parts of the editor: the data view and the variable view (take a look at Figures 2.1 and 2.3). The variable view is what will seem confusing to you at first. It replaces the heading at the top of each column in which you specify what kind of variable you're working with, what the variable is called, and so on. Instead, each variable gets a horizontal line, and each column is a different feature such as name, type, number of decimals, etc. So if you have 3 variables, your variable view will have three horizontal lines worth of information.

The data view is more like what you're used to. Once you've defined your variables in the variable view, you enter the actual data (numbers, gender, or whatever you're entering) in the same way you would in Statview. Each variable has a column, and each horizonal line is a different participant.

Note 3 - Categorical Variables

SPSS's way of defining categorical variables will seem somewhat bizarre to a veteran StatView user. Recall that in Statview, when you are selecting TYPE for a categorical variable, you simply pick "Category" and then go on your merry way of defining the groups contained in the variable. In SPSS, you choose "String" as the variable type (I imagine you might have initially panicked when you did not see "Category" as one of your choices) then go to a different column, VALUES, to define the different choices for the category. In addition to specifying the different category choices (in the case of gender, "male" and "female"), SPSS wants you to assign a value to each. So you might pair "1" with male and "2" with female; it is arbitrary what you pick.

Note 4 - Inserting New Cases and Variables Between Existing Cases or Variables

Doing this is equivalent to clicking the "Apple" button after placing the mouse between a row or column in a Statview dataset. Both of these allow you to create a new column (i.e., insert another variable in your dataset.)

Note 5 - Entering Data

Personally, I recommend first entering and setting all your variables using the "Variable View." Then, switch SPSS to "Data View" and enter your data just as you would in Statview.

Note 6 - Recreating a Computed Variable

Unlike Statview, there is no easy way to access or alter your computed formulas once they have been created in SPSS. If you make a mistake, you have to recreate the computation rather than altering the existing formula. Furthermore, unlike Statview, SPSS DOES NOT UPDATE COMPUTED VARIABLES WHEN THE DATA SET CHANGES. Make sure your formula is correct and that your data set is complete before you compute a formula. In the event that you make changes to your raw data, you MUST also recreate any computed variables.

Note 7 - Missing Variables

In Statview, there was a formula which allowed the user to create a sum while ignoring missing data points. SPSS does this automatically when you use the SUM( ) function. In other words if Point A is 5 and Point B is missing, the computed sum will be 5. While this function is sometimes quite useful, it also means that it is often in your best interest to replace missing values before running any analysis or computing new variables.

Note 8 - Manipulating Variables

If you're familiar with Statview, you might expect to see something in this section about compacting variables. SPSS has an entirely different procedure for repeated measures ANOVA which is discussed here.

Note 9 - SPSS Cheat Sheet

This is a cheat sheet for Statview veterans which will help you find your favorite analytical tools in the SPSS "Analyze" menu based on its name in the Analysis browser from good ole' Statview.

Note 10 - Excluding Data Using "Select Cases"

In Statview, this is the "Criteria" feature. In SPSS, however, the same process is known as a filter. Once you have created a filter, it can be saved just like a criteria. To create a filter, follow the instructions for "select cases".

Note 11 - Making a Correlation Graph

For Statview veterans, this is likely one of the least intuitive procedures in SPSS. I recommend reading through this section carefully.

Note 12 - Paired-Sample T-Tests

The t-value for this analysis appears at the far right of the SPSS viewer window, so you will probably have to scroll over to see it.

Note 13 - Repeated Measures ANOVA

In Statview, you have to create a compact variable to run a repeated measures ANOVA. In SPSS, there is no need to do so. You will indicate which variables are to be used for the repeated measures ANOVA test once you have selected the procedure. At that point, the procedure is very similar to what one does in StatView.

Note 14 - Output Window

This is similar to Statview. Remember that the "View" window was also saved separately from the data set used to create it. An advantage to using SPSS, however, is that once the output from SPSS has been saved, you no longer need the original data set to open it as you did with Statview.