Running the analysis

1. To run a Bayesian Independent - Sample analysis, from the menus choose: Analyze > Bayesian Statistics > Independent Samples Normal

   

2. In the Bayesian Independent - Sample Inference dialog, select Current Salary [salary] as the Test Variables(s) value and then select Gender [gender] as the Grouping Variable value. A grouping variable defines two groups for the unpaired t-test.
3. Use the Define Groups settings to define two groups for the t-test by specifying two values for the selected string variable (Current Salary [salary]).
   • In the Define Groups section, enter f for the Group 1 value and m for the Group 2 value.
4. Select Characterize Posterior Distribution as the Bayesian Analysis. The Bayesian inference is made from a perspective that is approached by characterizing posterior distributions. You can investigate the marginal posterior distribution of the parameter(s) of interest by integrating out the other nuisance parameters, and further construct Bayesian confidence intervals to draw direct inference.
5. Click Priors and define the following prior distribution settings:

   

   1. Select Variance known as the Data Variance setting and enter 10000000 as the Group 1 variance and 300000000 as the Group 2 variance.

      The values coincide with the observed variance values for both groups.

   2. Select Normal as the Prior on mean conditional on variance setting, and enter the following values:
      • Location Parameter: Group 1 = 20000; Group 2 = 22500

        The values coincide with the observed mean difference of $2500.

      • Scale Parameter: Group 1 = 10000; Group 2 = 15000

        That values coincide with observed variance of $25000.

6. Click Run Analysis.

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