In regression, the variable predicted is called the     regression variable     independent variable     dependent variable     predictor

bex Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 3.136512 0.964065 0.985521 0.971252 0971252 Given the above regression statistics, what is the value of the coefficient of determination? 0.964065 3.136512

Regression analysis is a powerful and commonly used tool in business research. One important step in regression is to determine the dependent and independent variable(s). In a bivariate regression, which variable is the dependent variable and which one is the independent variable? What does the intercept of a regression tell? What does the slope of a regression tell? What are some of the main uses of a regression? Provide an example of a situation wherein a bivariate regression would be a good choice for analyzing data. Justify your answers using examples and reasoning.

A company hires you to develop a linear regression forecasting model. Based on the company's historical sales information, you determine the intercept value of the model to be 1,500. You also find the slope value is -25. If after developing the model you are given a value of X = 8, which of the following is the resulting forecast error using this model if the actual sales is 1250?

The number of auto accidents in Athens, Ohio is related to the regional number of regisgtered automobiles in thousands (X1) alcholic beverage sales in $10,000 (X2) and rainfall in inches (X3). Furthermore the regression formula has been calculated as:             y=a+b1X1+b2x2+b3X3 where  y= number of automobile accidents a=  8.0  b1= 3.5 b2=5.0 b3= 2.4  For the given values of X1,X2, and X3, the expected number of accidents will be ( round your responses to one decimal place)                 X1           X2              X3            # of accidents                  6.0           7.0             0.0               [__]

In multiple regression analysis, testing the significance of individual regression coefficients is based on     A t statistic     A z statistic     An F statistic