SOFTWARE FOR RESEARCHERS: MODULE 2: THE SPSS ENVIRONMENT

MODULE 2:

2.1 Overview of SPSS for Windows

SPSS for Windows consists of five different windows, each of which is associated with a particular SPSS file type. This document discusses the two windows most frequently used in analysing data in SPSS, the Data Editor and the Output Viewer windows. In addition, the Syntax Editor is briefly discussed.

2.2 Starting SPSS

To start SPSS, go to the Start icon on your Windows computer. You should find an SPSS icon under the Programs menu item then double click it. It will open a dialog box as shown in fig. 2.1, in the dialog box click type in data, then click OK. This will open a standard explorer window (shown in fig. 2.2) that allows you to browse your computer and find the file you want but what if you want to open something other than a data file, for example a viewer document containing the results of your last analysis. You can do this by selecting Open another type of file) and either selecting a file from the list or selecting More Files … and browsing your computer. If you’re starting a new analysis (as we are here) then we want to type our data into a new data editor. Therefore, we need to select Type in data (by again clicking on the appropriate) and then clicking on ok. This will load a blank data editor window.

Fig. 2.1

Fig. 2.2

2.2.1 THE DATA EDITOR

SPSS data editor window is SPSS main window (shown in fig. 2.3). This is the only window that’s always open whenever we run SPSS. It’s recognised by red icon in its left top corner. The data editor has two tabs in the left bottom corner: we can click data view for inspecting our data values. Alternatively, variable view shows information regarding the meaning of our data.

Fig.2.3

2.2.2 SPSS Syntax Editor Window

Another important window in the SPSS environment is the Syntax Editor (shown in fig 2.4). In earlier versions of SPSS, all of the procedures performed by SPSS were submitted through the use of syntax, which instructed SPSS on how to process your data. More recent versions contain pull-down menus with dialog boxes that allow you to submit commands to SPSS without writing syntax. This SPSS for Windows tutorial focuses on the use of dialog boxes to execute procedures; however, there are at least two reasons why you should be aware of SPSS syntax, even if you plan to primarily use the dialog boxes. First, not all procedures are available through the dialog boxes. Therefore, you may occasionally have to submit commands from the Syntax Editor. Second, the Syntax Editor is a useful way to save a log of what you have done, and to re-run what you have done at a later date. The dialog boxes available through the pull-down menus have a button labelled Paste, which will print the syntax for the procedure you are running in the dialog box environment to the Syntax Editor. Thus, you can easily generate SPSS syntax without typing in the Syntax Editor.

Fig. 2.4

2.2.3 OUTPUT VIEWER

This is the window that contains all output we generate (shown 2.5). The most typical output items are tables and charts that describe patterns in our data. An output viewer opens automatically when we generate output its recognized by a purple icon. Note the output viewer window has two sections: the left pane and the right pane shows the actual output. The outline shows a that the output items such as headings and tables are organised according to a tree structure. Output items can be selected at once by clicking the book icon of this branch. All items under a branch can be hidden by clicking the minus icon shown in the outline. For deleting items, select them and press the delete button on your keyboard. All contents of the output viewer can be saved as an SPSS Output file. Recent SPSS versions use ‘.spv’ (SPSSViewer) file extension. In older versions, ‘spo’(SPSS Output) is used instead.

Fig. 2.5

2.2.3.1 SPSS Output Files Limitation

SPSS output files are rarely used for reporting results. A major reason is that they can’t be opened by be recipients who don’t have SPSS installed on their computers. As I suggested you probably don’t want to report by saving and sharing your output file(s). so you can simply copy and paste output items from SPSS Output Viewer window in your report or under file click export is export output. An advantage of this is that it works by means of syntax at some point, the corrected output will be exported automatically as well.

2.3 SPSS Menu

Below is a brief reference guide to each of the menus and some of the options that they contain. This is merely a summary and we will discover the wonders of each menu as we progress through this tutorial.

ü File: This menu allows you to do general things such as saving data, graphs or output. Likewise, you can open previously saved files and print graphs data or output. In essence, it contains all of the options that are customarily found in File menus.

ü Edit: This menu contains edit functions for the data editor. In SPSS it is possible to cut and paste blocks of numbers from one part of the data editor to another (which can be very handy when you realize that you’ve entered lots of numbers in the wrong place). You can also use this to select various preferences such as the font that is used for the output. The default preferences are fine for most purposes.

ü View: This menu deals with system specifications such as whether you have grid lines on the data editor, or whether you display value labels (exactly what value labels are will become clear later).

ü Data: This menu allows you to make changes to the data editor. The important features are, insert variable which is used to insert a new variable into the data editor (i.e. add a column); insert cases which is used to add a new row of data between two existing rows of data; split file which is used to split the file by a grouping variable and, select cases which is used to run analyses on only a selected sample of cases.

ü Transform: You should use this menu if you want to manipulate one of your variables in some way. For example, you can use recode to change the values of certain variables (e.g. if you wanted to adopt a slightly different coding scheme for some reason) .The compute function is also useful for transforming data (e.g. you can create a new variable that is the average of two existing variables). This function allows you to carry out any number of calculations on your variables.

ü Analyse: The fun begins here, because the statistical procedures lurk in this menu. Below is a brief guide to the options in the statistics menu that will be used during the course of this tutorial (this is only a small portion of what is available):

Descriptive Statistic: This menu is for conducting descriptive statistics (mean, mode, median, etc.), frequencies and general data exploration. There is also a command called crosstabs that is useful for exploring frequency data and performing tests such as chi-square, Fisher’s exact test and Cohen’s kappa.
Compare mean: This is where you can find t-tests (related and unrelated –and one-way independent ANOVA.

General linear model: This menu is for complex ANOVA such as two-way (unrelated, related or mixed), one-way ANOVA with repeated measures and multivariate analysis of variance (MANOVA)
Mixed model: This menu can be used for running multilevel linear models (MLMs).
Correlation: It doesn’t take a genius to work out that this is where the correlation techniques are kept! You can do bivariate correlations such as Pearson’s R, Spearman’s rho (ρ) and Kendall’s tau (τ) as well as partial correlations.
Regression: There are a variety of regression techniques available in SPSS. You can do simple linear regression, multiple linear regression and more advanced techniques such as logistic regression.
Log linear: Log linear analysis is hiding in this menu, waiting for you.
Data reduction: You’ll find factor analysis here.
Scale: Here you’ll find reliability analysis.
Non parametric Tests: There are a variety of non-parametric statistics available such as the chi-square goodness-of-fit statistic, the binomial test, the Mann–Whitney test, the Kruskal–Wallis test, Wilcoxon’s test and Friedman’s ANOVA.
Graphs: SPSS has some graphing facilities and this menu is used to access the Chart, Builder). The types of graphs you can do include: bar charts, histograms, scatterplots, box–whisker plots, pie charts and error bar graphs to name but a few.

üWindow: This menu allows you to switch from window to window. So, if you’re looking at the output and you wish to switch back to your data sheet, you can do so using this menu. There are icons to shortcut most of the options in this menu so it isn’t particularly useful.

ü Utilities: In this menu there is an option, data file comment that allows you to comment on your data set. This can be quite useful because you can write yourself notes about from where the data come, or the date they were collected and so on.

ü Add-ons: SPSS sells several add-ons that can be accessed through this menu. For example, SPSS has a program called Sample Power that computes the sample size required for studies, and power statistics.

ü Help: This is an invaluable menu because it offers you online help on both the system itself and the statistical tests. The statistics help files are fairly incomprehensible at times (the program is not designed to teach you statistics) and are certainly no substitute for acquiring a good material like this.

2.4 ICONS

There is also a set of icons at the top of the data editor window (see Figure 3.3) that are shortcuts to specific, frequently used, facilities. All of these facilities can be accessed via the menu system but using the icons will save you time. Below is a brief list of these icons and their functions:

This icon gives you the option to open a previously saved file (if you are in the data editor SPSS assumes you want to open a data file; if you are in the output viewer, it will offer to open a viewer file).
This icon allows you to save files. It will save the file you are currently working on (be it data or output). If the file hasn’t already been saved it will produce the Save Data as dialog box.
This icon activates a dialog box for printing whatever you are currently working on (either the data editor or the output). The exact print options will depend on the printer you use. By default, SPSS will print everything in the output window so a useful way to save trees is to print only a selection of the output.
Clicking on this icon will activate a list of the last 12 dialog boxes that were used. From this list you can select any box from the list and it will appear on the screen. This icon makes it easy for you to repeat parts of an analysis.
clicking on this icon enables you to go directly to a case (a case is a row in the data editor and represents something like a participant, an organism or a company). This button is useful if you are working on large data files: if you were analysing a survey with 3000 respondents it would get pretty tedious scrolling down the data sheet to find participant 2407’s responses.
clicking on this icon enables you to go directly to a variable.
clicking on this icon opens a dialog box that shows you the variables in the data editor and summary information about each one.
clicking on this enable you to search for words or numbers in your data file and output window. In the data editor it will search within the variable (column) that is currently active. This option is useful if, for example, you realize from a graph of your data that you have typed 20.02 instead of 2.02 ,you can simply search for 20.02 within that variable and replace that value with 2.02.
Clicking on this icon inserts a new case in the data editor (so it creates a blank row at the point that is currently highlighted in the data editor). This function is very useful if you need to add new data at a particular point in the data editor.
Clicking on this icon creates a new variable to the left of the variable that is currently active (to activate a variable simply click once on the name at the top of the column).
Clicking on this icon is a short-cut to the function 'split file'). There are often situations in which you might want to analyse groups of cases separately. In SPSS we differentiate groups of cases by using a coding variable and this function lets us divide our output by such a variable. For example, we might test males and females on their statistical ability. We can code each participant with a number that represents their gender (e.g. 1 = female, 0 = male). If we then want to know the mean statistical ability of each gender, we simply ask the computer to split the file by the variable Gender. Any subsequent analyses will be performed on the men and women separately. There are situations across many disciplines where this might be useful: sociologists and economists might want to look at data from different geographic locations separately, biologists might wish to analyse different groups of mutated mice, and so on.
This icon short-cut to the function 'weight cases' . This function is necessary when we come to input frequency data and is useful for some advanced issues in survey sampling.
This icon is a short-cut to the function 'value label'. If you want to analyse only a portion of your data, this is the option for you! This function allows you to specify what cases you want to include in the analysis. There is a Flash movie on the companion website that shows you how to select cases in your data file.
Clicking on this icon will either display or hide the value labels of any coding variables. We often group people together and use a coding variable to let the computer know that a certain participant belongs to a certain group. For example, if we coded gender as 1 = female, 0 = male then the computer knows that every time it comes across the value 1 in the Gender column, that person is a female. If you press this icon, the coding will appear on the data editor rather than the numerical values; so, you will see the words male and female in the Gender column rather than a series of numbers.