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Part 2: Based on the material taught in this course, which of the following is the most appropriate alternative hypothesis to determine if number of patients in the ER at time of admitting has a statistically significant linear relationship with length of stay in the ER? O Ha : "d # 0 O Ha : B1 / 3.59 Ha : B1 0 O Ha : B1 = 3.59Part 5: The researchers calculate a 95% confidence interval for the regression slope to be (2.09, 5.09). What is the best way to interpret this interval? We are 95% confident that the sample regression slope lies between 2.09 and 5.09. We are 95% confident that the true regression slope lies between 2.09 and 5.09. 95% of patients waited between 2.09 and 5.09 minutes for each additional patient in the ER at the time they were admitted O There is a 95% chance the true regression slope lies between 2.09 and 5.09A research team set out to estimate how long a patient would stay in the Emergency Room (ER) of their hospital based on the number of other patients already in the ER at the time of admission. They used least-squares regression to calculate the following from their sample data: Y - 176 + 3.59X. In this equation Y represents the length of stay (in minutes) in the Emergency Room and X represents the number of patients already in the Emergency Room at the time a new patient is admitted. Use this information for all parts. Question 17 1 Part 1: Which is the response variable, and why? O Number of patients, because it is being used to predict length of stay O Length of stay, because it is being used to predict number of patients O Number of patients, because it is the variable being predicted O Length of stay, because it is the variable being predicted.Part 3: Based on the data, the researchers decide to reject their null hypothesis. How should they state their conclusion? There is insufficient evidence to say that there is a linear relationship between length of ER stay and number of patients already in the ER at the time a new patient is admitted There is sufficient evidence to say that true slope of the regression line is not 3.59. There is sufficient evidence to say that there is a linear relationship between length of ER stay and number of patients already in the ER at the time a new patient is admitted There is sufficient evidence to say that there is NO linear relationship between length of ER stay and number of patients already in the ER at the time a new patient is admittedPart 4: Predict a patient's length of stay in the ER, if there were 10 other patients there at the time a patient was admitted. What is the predicted length of stay in minutes? (Round to the nearest whole minute)Part 6: Which of the following requirements must be met before using the results of the confidence interval? (Check all that apply) Examine a scatterplot to see if there is a linear relationship between length of stay and number of patients )Check that the largest residual is no more than 4 times the smallest residual Examine a QQ plot of the residuals to see whether the error term (E) is normally distributed Check that you have a sample size, n, greater than 30 Examine a residual plot to see whether the variance of the error term is constant for all values of number of patients