- Recently A Random Sample Of 25 34 Year Olds Was Asked How Much Do You Currently Have In Savings Not Including Retire 1 (35.1 KiB) Viewed 12 times
- Recently A Random Sample Of 25 34 Year Olds Was Asked How Much Do You Currently Have In Savings Not Including Retire 2 (45.15 KiB) Viewed 12 times
- Recently A Random Sample Of 25 34 Year Olds Was Asked How Much Do You Currently Have In Savings Not Including Retire 3 (38.97 KiB) Viewed 12 times
- Recently A Random Sample Of 25 34 Year Olds Was Asked How Much Do You Currently Have In Savings Not Including Retire 4 (32.9 KiB) Viewed 12 times
- Recently A Random Sample Of 25 34 Year Olds Was Asked How Much Do You Currently Have In Savings Not Including Retire 5 (35.01 KiB) Viewed 12 times
- Recently A Random Sample Of 25 34 Year Olds Was Asked How Much Do You Currently Have In Savings Not Including Retire 6 (41.84 KiB) Viewed 12 times
Test: Review for Midterm Exam OA. Researchers initiated a long-term study of the population of American black bears. One aspect of the study was to develop a model that could be used to predict a bear's weight (since it is not practical to weigh bears in the field). One variable thought to be related to weight is the length of the bear. The accompanying data represent the lengths and weights of 12 American black bears. Complete parts (a) through (d) below. Click the icon to view the data table. Click the icon to view the critical values table. (a) Which variable is the explanatory variable based on the goals of the research? OA. The weight of the bear OB. The number of bears OC. The length of the bear (b) Draw a scatter diagram of the data. Choose the correct graph below. AWeight (kg) 180- 40+ 100 200 Length (cm) OB. Statcrunch Calculator ALength (om) 180- 40 100 200 Question 17 of 20 > Weight (kg) C (c) Determine the linear correlation coefficient between weight and length. The linear correlation coefficient between weight and length is r (Round to three decimal places as needed.) CITE OC. Aweight (kg) 1804 40 100 200 Length (cm) This test: 160 point(s) possible This question: 8 point(s) possible Q OD. AWeight (kg) 180 40+14 100 Length (cm) G Submit test Time Remaining: 01-16-53
Researchers initiated a long-term study of the population of American black bears. One aspect of the study was to develop a model that could be used to predict a bear's weight (since it is not practical to weigh bears in the field). One variable thought to be related to weight is the length of the bear. The accompanying data represent the lengths and weights of 12 American black bears. Complete parts (a) through (d) below. Click the icon to view the data table. Click the icon to view the critical values table. (b) Draw a scatter diagram of the data. Choose the correct graph below. OB. A. A Weight (kgr 1804 404 100 200 Length (cm) ALength (in) 100+ 100 Weight (kg) 200 G (c) Determine the linear correlation coefficient between weight and length. The linear correlation coefficient between weight and length is r (Round to three decimal places as needed.) (d) Does a linear relation exist between the weight of the bear and its length? The variables weight of the bear and length of the bear are than the critical value, (Round to three decimal places as needed.) KILD O C. AWeight (kg) 100- 404 100 200 Length (cm) associated because ris 2 OD. A Weight (kg) 1804 40+ 100 200 Length (cm) and the abfolute value of the correlation coefficient,
Use the given data to complete parts (a) and (b) below. ya (a) Draw a scatter diagram of the data. Choose the correct answer below. OA. B. 6 4- X 2.2 3.9 3.8 1.4 2.9 3.5 4.7 4.8 2 0- 22 12- 8- 4 4 2- Q Compute the linear correlation coefficient. The linear correlation coefficient for the four pieces of data is (Round to three decimal places as needed.) (b) Draw a scatter diagram of the data with the additional data point (10.4.9.2). Choose the correct answer below. OA. OB. O C. 124 8- n Q +++ A O c. 4- 2 5 o 12- 8 4 Q 5 4- 24 OD. AY 12+ 0- 4- +to o o S o S
Use the given data to complete parts (a) and (b) below. x yo 22 3.9 # 3.8 14 2.9 3.5 4.7 4.8 Compute the linear correlation coefficient with the additional data point. The linear correlation coefficient for the five pieces of data is (Round to three decimal places as needed.) Comment on the effect the additional data point has on the linear correlation coefficient. OA. The additional data point strengthens the appearence of a linear association between the data points. OB. The additional data point does not affect the linear correlation coefficient. OC. The additional data point weakens the appearence of a linear association between the data points. Explain why correlations should always be reported with scatter diagrams. A. The scatter diagram can be used to distinguish between association and causation. B. The scatter diagram is needed to determine if the correlation is positive or negative. OC. The scatter diagram is needed to see if the correlation coefficient is being affected by the presence of outliers. Statcrunch Calculator 10 Time Remaining: 01:15:21 Next
An engineer wants to determine how the weight of a gas-powered car, x, affects gas mileage, y. The accompanying data represent the weights of various domestic cars and their miles per gallon in the city for the most recent model year. Complete parts (a) through (d) below. Click here to view the weight and gas mileage data (a) Find the least squares regression line treating weight as the explanatory variable and miles per gallon as the response variable. (Round the x coefficient to five decimal places as needed. Round the constant to one decimal place as needed.) (b) Interpret the slope and y-intercept, if appropriate. Choose the correct answer below and fill in any answer boxes in your choice. (Use the answer from part a to find this answer.) mile(s) per gallon, on average. It is not appropriate to interpret ( OA. For every pound added to the weight of the car, gas mileage in the city will decrease by the y-intercept. B. A weightless car will get miles per gallon, on average. It is not appropriate to interpret the slope OC. For every pound added to the weight of the car, gas mileage in the city will decrease by miles per gallon, on average. OD. It is not appropriate to interpret the slope or the y-intercept. mile(s) per gallon, on average. A weightless car will get (c) A certain gas-powered car weighs 3501 pounds and gets 17 miles per gallon is the miles per gallon of this car above average or below average for cars of this weight? The estimated average miles per gallon for cars of this weight is (Round to three decimal places as needed.) miles per gallon. The miles per gallon of this car is (d) Would it be reasonable to use the least-squares regression line to predict the miles per gallon of a hybrid gas and electric car? Why or why not? average for cars of this weight.