(1) Click twice quickly with the left-side of the mouse on the SPSS icon. This gets you into SPSS for Windows. You will see something that looks like a spreadsheet titled Newdata. The rows (numbers) are cases, i.e., subjects; the columns are the variables (VAR).
(2) First you must define the variables. Move your mouse pointer to the first column and make sure that it is on the word VAR. Click twice quickly with the left-side of the mouse. (Alternatively, you may select Define Variable... from the Data menu.) Enter a variable name that is eight characters or less in the Variable Name box (e.g., Usage). The default variable name VAR00001 is highlighted so that you will be able to write over it. [Note: SPSS variable names are a maximum of eight alphanumeric characters; they must begin with an alphabetical character.] You will see four "Change Settings" buttons on the screen: Type... (to define the type of the variable), Labels... (to define variable and category labels), Missing Values... (to define a code for missing data), and Column Format... (width of column and alignment). Type allows you to define the type of data the variable represents, such as numeric, dollar, date, etc. If your data is numeric, you can specify the number of digits after the decimal point. For the Usage variable you may use the numeric type with 0 decimal places and change the width from 8 to 2. The Usage variable is a single digit (a 1, 2, 3, or 4 will be used to represent level of usage) and a field of two columns is more than adequate for this variable.
Labels allows you to define long descriptive labels for your variables and/or various values in your data. These labels will appear on your output. For example, for the Usage variable, you can use the Variable Label: Coffee usage. To define optional value labels, enter a value (say, 1) and then enter a value label (Heavy user). Click the Add button. Then you will be able to enter the remaining value labels (2, medium user, 3, light user, 4, nonuser). When you are finished, click Continue.
Missing Values. If there are missing values in your data, you can define codes for them. For example, if -1 is your code for a missing value, click on Discrete Missing Values and type -1 in the first box. (Alternatively, you may wish to use the number 9 as your missing value code.)
Click on column 2 of the spreadsheet and repeat step (2). Define all the variables in this manner. (Use the mouse to bring the mouse pointer to any column or row of the spreadsheet.)
(3) Bring the mouse pointer to row 1 and the first column and enter the data by pressing the Enter key. Now enter all the data into the datafile. To save your data, choose Save As from the File menu. Insert your own disk in the a: drive. Choose the a: drive. Give your data file a name, for example, a:coffee.sav and click OK. When you come back to the computer another day and wish to use the datafile you saved: Get into SPSS and choose File - Open - Data and open your file (remember that your file is in the a: drive).
Now you are ready to use SPSS procedures to analyze your data.
(4) Under the Statistics menu, choose Summarize and then choose Frequencies. You are presented with all your variables. Highlight each variable you wish to analyze, then click on the > button to add them to a box called Variables. Click on the Statistics button to select the statistics you wish to see, e.g., mean, median, mode, standard deviation, etc and click Continue. When you click OK, the results appear in the Output window. This window will keep the results of all the analyses you will run. The Frequencies procedure gives you the summary measures you request and also presents the frequency distributions. If you only wish to see the descriptive statistics themselves, choose Statistics - Summarize - Descriptives.
(5) To do a t-test, Choose Statistics - Compare Means - Independent Samples T test. Add test variables to the indicated box, e.g., aroma, intent, overall, price. Add a grouping variable to the indicated box, e.g., sex, then click on the Define Groups button. Specify the value 1 (e.g., if 1 represents males) as Group 1 and the value 2 (if 2 represents females) as Group 2. Click Continue. Then click OK to run the procedure.
(6) To perform a correlation, choose Statistics - Correlate - Bivariate. Choose the variables you wish to correlate and click OK.
(7) To perform crosstabs, choose Statistics - Summarize - Crosstabs. Decide on your row variables, your column variables. Click on the Statistics button to choose, say, Chi-square and Cramer's V statistics, then click Continue. Click the Cells button to get the observed and the expected frequencies. When you are ready, click OK to run the crosstabs procedure.
(8) To perform a regression, choose Statistics - Regression - Linear. Highlight the dependent variable and click on the > button to add it to a box called Dependent. Highlight the independent variable and click on the > button to add it to a box called independent. The Method should read Enter. Click OK to run.
(9) To perform a One-way ANOVA, choose Statistics - Compare Means - One-Way ANOVA. Highlight the dependent variable(s) and click on the > button to add it to a box called Dependent List. Highlight the group variable and click on the > button to add it to a box called Factor. You can also click on the Post Hoc... box to perform multiple comparisons. Click OK to run.
(10) To print your output, select Print from the File menu. To print your input data file, select Print from the File menu after switching back to the input window [see (11) to learn how to switch from one window to another].
(11) To go from the Output window to the Input data (Newdata) window (or vice versa) do one of the following: (a) either click on the visible portion of the window you would like to get to. You will note that one window almost, but not quite, overlaps the other. Or, (b) choose the Window menu and click on Newdata to get to the input file or Output to get to the output file. To see them both, side by side, click on Tile. Cascade means that the windows overlap; this is the default.
(12) To draw graphs, choose Graphs from the menu. You will note that you have a choice of various types of graphs including Bar... (barchart), Histogram..., and Scatter... To get a barchart, select Bar... from the Graph menu. Click inside of the rectangle with word Simple next to it and then click on the Define box. Insert the variable you wish to analyze into the Category Axis box by highlighting it and then clicking on the > button. If you wish, you can add titles and subtitles to the chart by clicking on Titles. Click OK to run (click Continue and then OK if you are in the Title box). Your output will appear in something called a Chart Carousel. To get a scattergram, choose Graphs - Scatter... and define the Y Axis and X Axis variables as above. Click OK to run.
(13) To recode your original variables, choose Transform - Recode... To compute a new variable from the original variables use Transform - Compute...
To randomly select cases, choose Data - Select Cases...
To calculate Cronbach's alpha coefficient, choose Statistics - Scale - Reliability Analysis. For quality control charts, choose Graphs - Control...
Sample Questionnaire:
(1) About how many cups of coffee do you drink in a normal day?
___more than 5 cups (heavy user)
___between 3 and 5 cups (medium user)
___about 1 or 2 cups (light user)
___about 0 (non user)
(2) Please try Brand X coffee and rate it on each of the following:
TASTE: ___excellent ___very good ___good ___fair ___poor
AROMA: ___excellent ___very good ___good ___fair ___poor
OVERALL ___excellent ___very good ___good ___fair ___poor
(3) Please indicate the chance that you would buy Brand X coffee?
DEFINITELY WOULD BUY ___ ___ ___ ___ ___ ___ ___ DEFINITELY WOULD NOT BUY
(4) How much would you be willing to pay for an eight ounce jar of Brand X coffee? _______________
(5) The following are necessary for classification purposes:
SEX: ____Male ____Female
AGE: __________
The SPSS variable names one might use for this questionnaire are: USAGE, TASTE, AROMA, OVERALL, INTENT, PRICE, SEX, AGE.
Sample Data:
1 4 5 4 6 1.08 1 28
1 2 2 3 2 2.45 2 41
2 1 1 1 1 3.00 2 57
2 4 4 4 6 1.78 1 31
3 4 5 4 6 2.06 2 40
3 3 5 4 5 1.88 1 39
4 4 3 4 4 2.95 2 48
4 2 2 3 2 2.78 1 38