You run a regression analysis on a bivariate set of data (n = 99). With * = 41.3 and y = 23.1, you obtain the regression equation y = 2.589x - 83.826 with a correlation coefficient of r = 0.789. You want to predict what value (on average) for the response variable will be obtained from a value of x 140 as the explanatory variable. What is the predicted response value? y = 446.3 x (Report answer accurate to one decimal place.)
You run a regression analysis on a bivariate set of data (n = 99). With * = 41.3 and y = 23.1, you obtain the regression equation y = 2.589x - 83.826 with a correlation coefficient of r = 0.789. You want to predict what value (on average) for the response variable will be obtained from a value of x 140 as the explanatory variable. What is the predicted response value? y = 446.3 x (Report answer accurate to one decimal place.)
You run a regression analysis on a bivariate set of data (n = 99). With * = 41.3 and y = 23.1, you obtain the regression equation y = 2.589x - 83.826 with a correlation coefficient of r = 0.789. You want to predict what value (on average) for the response variable will be obtained from a value of x 140 as the explanatory variable. What is the predicted response value? y = 446.3 x (Report answer accurate to one decimal place.)
You run a regression analysis on bivariant data set of n=99. Please see photo
Definition Definition Statistical method that estimates the relationship between a dependent variable and one or more independent variables. In regression analysis, dependent variables are called outcome variables and independent variables are called predictors.
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