6 only TH8 H foP this model ls 6.90, an d you can assume that all of the conditi

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6 only

TH8 H foP this model ls 6.90, an d you can assume that all of the conditions for linear regression to be valild question have been met. Suppose that you use this model to predict the number of seizures per week for a patient who has been at the hospital for 20 weeks. What is the predicted number of seizures per week for that patient? Answer: Question 6 Not yet answered Points out of 0.50 F Flag question What is the most likely explanation for the prediction you obtained for the previous problem? Select one: a. The relationship between weeks spent in the hospital and number of seizures per week is nonlinear. b. The linear regression model was likely developed using data on patients who did not stay at the hospital for longer than 15 weeks. Oc. The variance of the residuals was not constant. d. There were a number of influential points of high leverage in the data that skewed the linear regression model. O Question 7 In Lab # 11 you will collect data on the photosynthesis rates of goldenrod leaves measured at 8 different light Not yet intensities. Suppose you obtained the following regression output from R: answered Coefficients: Points out of 1.00 Estimate Std. Error t value Pr( ltl) Flag question (Intercept) 1.958056 0.617541 3.171 0.0193* light intensity 0.048806 0.002952 16.531 3.12e-06 Signif. codes:

Explanation / Answer

Question 6

Option C : here option C is incorrect as all the assumptions are met.

Option A : The relationship between the variables are linear as R2 = 0.99 so r would be 0.99 so that shows a very strong linear relationship.

Option D: The linear regression model is not skewed.

Option B Yes as the predicted value is infeasible so we can say that the data is developed for only stays less than 15 days

Option B is correct.

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