Consider the Standardized Beta values, what purpose does this value have when interpreting a regression model, and what does it explain?

Tables and Figures Table 1: OLS Model Summary for LogPay Analysis Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .886a .785 .729 .832 a. Predictors: (Constant), DisNSG, Post, Female, CharlsScore, Vent Table 2: Parameter Estimate Tables for LogPay Analysis Coefficients Unstandardized Coefficients Standardized Coefficients Model B Std. Error Beta Sig. 1 (Constant) 10.02 .495 238.005 .000 Post 1.54 .038 .085 2.584 .038 Vent 2.59 541 .170 12.222 .001 CharlsScore 029 .042 -.001 -.842 .059 Female 444 055 -.401 1.558 .024 DisNSG 550 .730 1.001 3.297 .611 a. Dependent Variable: LogPay HCM.820 - Informatics and Data Analysis