Desktop User Guides > Reporter > Applying statistical tests
 
Applying statistical tests
You can run statistical tests on your tables to show whether differences in the distribution of counts in tables are statistically significant or whether they are merely due to chance. The following table lists the tests that are available.
Name
Description
This test looks at the variables on the side and the top of a table and tests whether they are independent. For example, it can be used to show whether or not variations in political opinions depend on the respondent's age.
This test looks at the rows of a table independently and compares pairs of columns, testing whether the proportion of respondents in one column is significantly different from the proportion in the other column. The proportion is the count in the cell divided by the base for the column.
This test looks at means that are presented in a row of a table and compares pairs of columns, testing whether the mean in one column is significantly different from the mean in the other column.
This test looks at the variables on the side and top of a table with two rows and two columns and tests whether they are independent. It is suitable for use in a subset of the tables for which the chi-square test is available.
This test deals with each row independently and compares the proportions in four columns at a time to test whether the difference between the values in the first pair of columns is significantly different from the difference between the values in the second pair of columns.
This test deals with each column independently and compares pairs of rows to see whether the figures in each pair differ significantly from one another.
This is not a separate statistical test in its own right; instead, it applies the column proportions or column means test to a combination of variables that you select, to provide a detailed breakdown of results by combinations of individual categories within the selected variables.
This test compares the means of two variables, computes the difference between the two variables for each case, and tests to see if the average difference is significantly different from zero.
Statistics properties
The following table identifies the properties supported by each statistical test.
Chi-square/Fisher
Column proportions (/prod diff)
Column means (/prod diff)
Net difference
Paired Preference
T-Test
SigLevel
No
Yes
Yes
Yes
Yes
 
SigLevelLow
No
Yes
Yes
Yes
Yes
 
MinBase
No
Yes
Yes
Yes
Yes
 
SmallBase
No
Yes
Yes
Yes
Yes
 
ShowLSD
No
Yes
Yes
No
No
 
UseQFormula
No
Yes
Yes
No
No
 
UseContinuity Correction
No
Yes
No
No
No
 
See also
Requesting statistical tests
Adding a statistical test
Diagnostics information
p values
Weighted data and the effective base
Overlapping data
Hierarchical data
Selecting columns to test
Setting the significance levels
Minimum base and small base values in statistical tests