This procedure tests if the data follows a multi-nominal distribution with certain proportions.
1. Choose ProcessMA > Basic Statistics > Chi-square Goodness-of-fit Test.
2. In Data in, choose how your data is stored.
· If your data in stored in a single column:
- In Variable, select the column containing the raw categorical data.
· If your data in stored in summarised data:
- In Observed counts, select the column containing observed counts for each category.
- In Category names, select the column containing the category names.
3. In Proportions, choose the type of proportion.
· Choose Equal proportions if you want to assume equal proportions across categories.
· Choose Specific (input column) if you want to select the column containing proportions for each category.
· Choose Specific (enter data) if you want to enter the proportions for each category.
4. Check Plot obs. & exp. values, to display a bar chart of observed and expected values.
5. Check Plot Chi-Square contribution, to display a bar chart of each category’s contribution to the chi-square value.
6. Check Sort Chi-Square contribution, to sort the above bar chart in descending order.
7. Click OK.
Note To select a column of data into a textbox, double-click on any of the column names shown in the list on the left of the dialog box while in the textbox.
Variable: Text or numeric; At least 2 distinct categories.
Observed counts: Integer.
Category names: Text or numeric; Must have the same column length as observed counts.
Specific (input column): Numeric; Between 0 to 1; Number of proportions must have be equals to number of categories.
Specific (enter data): Numeric; Between 0 to 1; Number of proportions must have be equals to number of categories; Separated by commas(,).
You want to assess if the new student’s interests in the different faculties are similar to the previous year. You have collected data on 300 new student’s interest.
1. Open worksheet ProcessMA > Tools > Data Files > Stat.xls.
2. Choose ProcessMA > Basic Statistics > Chi-square Goodness-of-Fit Test.
3. In Variable, select I – Interest.
4. In Proportions, select Specific (enter data) and enter 0.6, 0.3, 0.1.
5. Click OK.
Interpretation
For a desired a = 0.05, since p = 0. 003 < a, we can reject H0 and conclude that the interest in different faculties for the new students is different from the previous year..