I only have one try for each of these questions. Please be sure of your answers please!
Question 1 of 20 View Policies Current Attempt in Progress From the following scatter plot, we can say that between y and x there is 0 perfect negative correlation O virtually no correlation 0 positive correlation 0 negative correlation 0 perfect positive correlation Question 2 of 20 View Policies Current Attempt in Progress According to the following graphic, X and Y have 0 strong positive correlation 0 strong negative correlation 0 weak negative correlation 0 moderate negative correlation O virtually no correlation Question 8 of 20 View Policies Current Attempt in Progress For the following scatter plot and regression line, at x = 34 the residual is 0 positive 0 zero 0 negative 0 unknown 0 imaginary Question 11 of 20 View Policies Current Attempt in Progress The following residuals plot indicates O a nonconstant error variance 0 a nonlinear relation 0 the sample is biased O the simple regression assumptions are met 0 a random sample Question 15 of 20 > View Policies Show Attempt History Current Attempt in Progress X Your answer is incorrect. If the coefficient of determination was 0.49, then the correlation coefficient would be O 0.49 O -0.49 O 0.7 O 0.7 or -0.7 O -0.7Question 16 of 20 0 / 1 E View Policies Show Attempt History Current Attempt in Progress X Your answer is incorrect. In the regression equation, y = 5.23 + 2.74x, and n = 24, the mean of x is 12.56, SSxx = 55.87 and Se = 10.71. A 90% prediction interval for y when x = 11 is O (12.56, 55.87) O (30.00, 40.74) O (16.21, 54.53) O (35.37, 70.74) O (2.74, 5.23)Question 1 of 20 View Policies Current Attempt in Progress According to the following graphic, X and Y have . 90 80 70 1400 1600 1800 2000 'X 0 strong positive correlation 0 weak negative correlation O moderate negative correlation O virtually no correlation 0 strong negative correlation Question 13 of 20 - / 2.5 E View Policies Current Attempt in Progress Louis Katz, a cost accountant at Papalote Plastics, Inc. (PPI), is analyzing the manufacturing costs of a molded plastic telephone handset produced by PPI. Louis's independent variable is production lot size (in 1,000's of units), and his dependent variable is the total cost of the lot (in $100's). Regression analysis of the data yielded the following tables. Coefficients Standard Error t Statistic p-value Intercept 3.996 1.161268 3.441065 0.004885 X 0.358 0.102397 3.496205 0.004413 Source df SS MS F Regression 1 9.858769 9.858769 12.22345 Se = 0.898 Residual 11 8.872 0.806545 r2 = 0.526341 Total 12 18.73077 The correlation coefficient between Louis's variables is O -0.73 O 0.00 O -0.28 O 0.73 O 0.28Question 16 of 20 > - /2.5 View Policies Current Attempt in Progress If a scatter plot of variables X and Y shows a trend that can be summarized to a large degree by a straight line with slope 0.8 and y-intercept 0.2 (i.e., Y = 0.2 + 0.8X), then the correlation coefficient between X and Y is O 0.8, and there may be a causal relation between X and Y, but not necessarily O 0.8, but there is no causal relation between X and Y O 0.8, and there is a causal relation between X and Y (either X causes Y or Y causes X) O 0.2, but there is no causal relation between X and Y O 0.2, and there is a causal relation between X and Y (either X causes Y or Y causes X) Save for Later Attempts: 0 of 1 used Submit AnswerQuestion 18 of 20 - l 2.5 E View Policies Current Attempt in Progress A runner tracks her average weekly mileage while marathon training along with her marathon nish times. given by the table below. Classify the correlation between two variables. Marathon Time Weekly Mileage (mins) 55 223 63 215 67 205 77 205 85 204 82 202 74 207 Q There is a weak positive correlation between the variables. 0 There is a strong positive correlation between the variables. 0 There is a strong negative correlation between the variables. 0 There is a weak negative correlation between the variables. Question 20 of 20 - / 2.5 View Policies Current Attempt in Progress The data in the table below represent number of months spent training (x) and finish times in minutes (y) for a 5K footrace. Calculate a 95% prediction interval for the predicted finish time in minutes(y) for a participant who trains for 3.5 months. X 2 3 3 3 4 4 5 5 5 6 y 28.7 24.8 26 30.5 23.8 24.6 23.8 20.4 21.6 22 O (24.049, 27.061) O (23.649, 27.661) O (21.017, 30.293) O (23.449, 27.861) Save for Later Attempts: 0 of 1 used Submit
