Running the analysis

  1. To run a Bayesian one sample binomial - posterior distribution analysis, from the menus choose: Analyze > Bayesian Statistics > One Sample Binomial
    Figure 1. Bayesian One Sample Inference: Binomial dialog
    Bayesian One Sample Inference: Binomial dialog
  2. In the Bayesian One Sample Inference: Binomial dialog, select Current Salary (salary) as the Test Variable(s).
  3. 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.
  4. Select Cutpoint from the Success Categories list and enter 50000 as the Value. Success categories provide options for defining conjugate prior distributions. Cutpoint uses the numerical values ≥ a specified cutoff value as cases.
  5. Click Priors and define the following Binomial priors settings:
    Figure 2. Bayesian One Sample Inference: Binomial/Poisson Priors dialog
    Bayesian One Sample Inference: Binomial/Poisson Priors dialog
    1. Enter 1 as the Shape Parameter value. The value specifies the shape parameter a0 for Beta distribution.
    2. Enter 1 as the Scale Parameter value. The value specifies the scale parameter b0 for Beta distribution.
  6. Click Run Analysis.

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