Running the analysis

  1. To run a Bayesian inference about linear regression model analysis, from the menus choose: Analyze > Bayesian Statistics > Linear Regression
    Figure 1. Bayesian Inference about Linear Regression Models dialog
    Bayesian Inference about Linear Regression Models dialog
  2. In the Bayesian Inference about Linear Regression Models dialog, select Current Salary [salary] as the Dependent variable and then select Education Level (years) [educ] and Previous Experience (months) [prevexp] as the Covariate(s) variables.
  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. Click Plots to plot covariates and factors.
    Figure 2. Bayesian Inference about Linear Regression Models dialog
    Bayesian Inference about Linear Regression Models dialog
  5. In the Bayesian Linear Regression Models: Plots dialog, select Education Level (years) [educ] and Previous Experience (months) [prevexp] as the Plot covariate(s) variables, and ensure that none of the Include plots of options are selected.
  6. Click Run Analysis.

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