The following is a partial computer output of a multiple regression analysis of a data set containing 20 sets of observations on the dependent variable The regression equation is SALEPRIC = 1470 + 0.814 LANDVAL + 0.820 IMPROVAL + 13.5 AREA Predictor Coef SE Coef T P Constant 1470 5746 0.26 0.801 LANDVAL 0.8145 0.5122 1.59 0.131 IMPROVAL 0.8204 0.2112 3.88 0.0001 AREA 13.529 6.586 2.05 0.057   S = 79190.48 R-Sq = 89.7% R-Sq(adj) = 87.8%

The accompanying scatterplot shows the relationship between the age of an internet user and the amount of time spent browsing the internet per week​ (in minutes). The accompanying residual plot is also shown along with the QQ plot of the residuals. Choose the statement that best describes whether the condition for Normality of errors does or does not hold for the linear regression model. Choose the statement that best describes whether the condition for Normality of errors does or does not hold for the linear regression model. A.The residual plot displays a fan​ shape; therefore the Normality condition is not satisfied.B.The QQ plot mostly follows a straight​ line; therefore the Normality condition is satisfied.C.The scatterplot shows a negative​ trend; therefore the Normality condition is satisfied.D.The residual plot shows no​ trend; therefore the Normality condition is not satisfied.

A group of Maternal and Child Health public health practitioners are interested in the relationship between depression and a number of health outcomes. Suppose the research team gathers information on a group of participants, and constructs a multiple linear regression model looking at the relationship between depression and household income dichotomized as above and below the federal poverty line controlling for a number of potential confounders. The following is a computerized output displaying the results of their analysis.   Parameter Estimate Standard Error t Value Pr > |t| Intercept 0.2617346843 0.09209917 2.84 0.0046 Income (1/0) -.1962038300 0.04574793 -4.29 <.0001 Race (W or AA) -.0320329506 0.03900447 -0.82 0.4118 bmicontinuous 0.0051185980 0.00216986 2.36 0.0186 Alcohol (Y/N) -.0088735044 0.03090631 -0.29 0.7741   A) What are the independent and dependent variables? B) Which potential…

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A simple linear regression model was created to examine the relationship between the age of patients in years (i.e. the independent variable) and the patients' scores on a questionnaire that measures quality of life (i.e. the dependent variable). There were n=20 patients in the study, and some of the results of the regression are presented below: Estimated slope = -0.64 Standard error of the slope = 0.52 Estimated intercept = 42.0 Standard error of the intercept = 13.6 Based on these results, what would be the expected quality of life score for a patient who is 30 years old?   Question 3 options:   61.2   22.8   1260.64   29.2