Question: LUCHILICINE Standardized Unstandardized Coefficients Coefficients Model B Sid Error Beta Sig (Constant) 25164,951 5538.973 4.543 000 q21_Initial Q21_Initial 886 .081 455 10.981 000 amount of

 LUCHILICINE Standardized Unstandardized Coefficients Coefficients Model B Sid Error Beta Sig(Constant) 25164,951 5538.973 4.543 000 q21_Initial Q21_Initial 886 .081 455 10.981 000

LUCHILICINE Standardized Unstandardized Coefficients Coefficients Model B Sid Error Beta Sig (Constant) 25164,951 5538.973 4.543 000 q21_Initial Q21_Initial 886 .081 455 10.981 000 amount of investment ($) a. Dependent Variable: q28_loss Q28_2 Total Eron investment Net loss ($) The following regression output (click on the "Regression Output Exam 3.png" file below) on net loss (DV) and amount of initial investment (IV) in dollars was obtained from victims of the Eron Ponzi scandal in British Columbia, Canada. Use the SPSS Regression output below and answer the following questions: A. What is R2 for this regression analysis and what does it mean? B. For the equation Y -bX + a, in the SPSS output, what are the values for a AND b? C. Is the linear relationship between net loss and initial investment significant (please provide a "yes" or "no" answer and the significance value)? D. Explain the relationship between net loss and initial investment of Eron victimsModel Summary Adjusted R Std, Error of Model R R Square Square the Estimate 1 455 207 .205 101048.689 a Predictors: (Constant). q21_Initial Q21_Initial amount of Investment ($) Coefficients Standardized Unstandardized Coefficients Coefficients Model B Std, Error Beta Sig (Constant) 25164.951 5538.973 4.543 1000 q21_Initial Q21_Initial .886 081 455 10.981 000 amount of investment ($) a. Dependent Variable: q28_loss Q28_2 Total Eron investment Net loss ($) The following regression output (click on the "Regression Output Exam 3.png" file below) on net loss (DV) and amount of initial investment (IV) in dollars was obtained from victims of the Eron Ponzi scandal in British Columbia, Canada. Use the SPSS Regression output below and answer the following questions

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