SPSS - Chi-square test for Goodness of Fit

Sample data - Most important factor in auto purchase (n= 100): 

STEP 1: Define variable name, label, and values

Open
SPSS and choose Type in data. Start by naming the variable of interest. Click the Variable View sheet tab.  Type the variable name (8 characters max) in the Name column. Specify variable type, width, and number of decimals. You have the option of typing a more descriptive variable name (255 characters max) in the Label column.  Click on the values cell and then the gray box in the right corner of the cell.  A Values dialog box opens.  Label the categories of the variable (e.g., for "Factor", "1.00 = Cost", "2.00 = Styling", etc.).  Click the Add button after defining each value. 

STEP 2: Input the data into SPSS

 Make sure to click back into Data View.  The data are frequencies, not scores. SPSS looks for the  frequency of  each score in the column. If you want SPSS to see a frequency of 30 for cost, you must type 30 "1's" in that column. If your variable has 4 categories as the data above, you must enter 1's, 2's, 3's, and 4's, for the frequency in each respective category.  Type all data pertaining to one variable in one column.

STEP 3: Select the statistical procedures

Go to the Analyze menu and select Nonparametric Test and then select Chi-square.

STEP 4: Select the variables

Inside the chi-square subcommand box, select the variable column to analyze (VAR0001, for example) by using the arrow keys to move the variable name into the right box. If your null hypothesis states that the expected frequencies are equal, check that this box is selected and click OK. If your null hypothesis states that the expected frequencies are compared to another population, you must enter these proportions in the Expected Values box. You can enter these as percentages, as PASW will automatically calculate expected frequencies for you. Be sure to use the Add key to enter each of the expected frequencies to the list. When ready to proceed, click OK button. The observed and expected frequency tables, along with the chi-square statistic will be displayed in your output window.

STEP 5: Look up the critical value of chi-square OR look at the significance level on the output and make a conclusion regarding Ho.