Average Daily Temperature For the period November 1, 2013 through February 21, 2014, of interest was to use the average daily low temperature in degrees Fahrenheit in a city to predict the number of days children in that city missed from school due to weather closings. A random sample of 37 cities was selected and the data is displayed in the scatterplot below. 25- 20 15 Days of School Missed 10 5 0 10 15 20 25 30 35 40 45 50 Average Temperature1 point 5 Based on the information provided, which of the following are correct statements? SELECT ALL TRUE STATEMENTS! Days of school missed is the dependent variable. Average temperature is the response variable. Days of school missed is the independent variable. Days of school missed is a lurking variable. Average temperature is a lurking variable. Average temperature is the explanatory variable. 3 points 5 Consider the scatterplot. Use this scatterplot to describe completely the relationship between the average temperature and the number of days of school missed. 4-31UivleEE 12pt v Paragraph V ' El EH (50 5| 3 2 points Consider the scatterplot above. Write the value that you guess the correlation coefficient r is equal to (no calculations are necessary). BIUAA TX E x2 Xz 12pt Paragraph fx 4 1 point Predicting a value of Y for a value of X which falls outside the range of the original X data is referred to as... O Outlier O Extrapolation O Residual Influential observation Lurking variable1 point One of the cities in the data set had an average temperature of 11 degrees and students did not miss any days of school. You should be able to locate this city on the scatterplot above. This city is an example of which of the following? 0 Outlier Extrapolation Residual O O Lurking variable 0 O Inuential observation 2 points ' The regression line that gives the linear relationship between the average temperature and the number of days of school missed is predicted number of days of school missed =18.16 - 0.42(average temperature). Suppose in Richmond the average temperature during this period was 24 degrees Fahrenheit. Use the regression line to predict the number of days of school missed for a city with an average temperature of 24 degrees seBIUgvlexE 12pt v Paragraph v Ev IZI EB 6 5 1 point The regression line that gives the linear relationship between the average temperature and the number of days of school missed is predicted number of days of school missed =18.16 - 0.42(average temperature). Which of the following is the correct interpretation of the t); of this regression line? 0 If the average temperature is 0.42, then the predicted number of days of school missed is 18.16 days. If the average temperature increases by 1 degree, then the predicted number of days of school missed decreases by 0.42 days. If the average temperature increases by 1 degree, then the predicted number of days of school missed increases by 18.16 days. If the number of days of school missed increases by 1 day, then the predicted average temperature decreases by 0.42 degrees. If the number of days of school missed decreases by 0.42 days, then the predicted average temperature increases by 18.16 degrees. 00000 If the number of days of school missed increases by 1 day, then the predicted average temperature increases by 18.16 degrees. a 1 point ' The regression line that gives the linear relationship between the average temperature and the number of days of school missed is predicted number of days of school missed =18.16 - 0.42(average temperature). Which of the following is the correct interpretation of the intercep_t of this regression line? 0 00000 If the average temperature is 0 degrees, then the predicted number of days of school missed is 0.42 days. If the number of days of school missed is 0 days, then the predicted average temperature is 18.16 degrees. If the average temperature is 0.42, then the predicted number of days of school missed is 18.16 days. If the number of days of school missed is 0 days, then the predicted average temperature is 0.42 degrees. If the average temperature is 0 degrees, then the predicted number of days of school missed is 18.16 days. If the number of days of school missed decreases by 0.42 days, then the predicted average temperature increases by 18.16 degrees. Suppose in Richmond the average temperature during this period was 24 degrees Fahrenheit, and during the period students missed 9 days of school due to the weather. If one computed the difference between the observed 9 days of school missed due to bad weather and the predicted number of days of school missed for a city with an average temperature of 24 degrees using the regression line stated above, this difference is referred to as which of the following? (Note: this is a denition question, not a calculation question). Extrapolation Outlier Residual Lurking variable OOOOO Inuential observation 1 point Some cities have more snow removal equipment than others, and hence the number of days of school missed due to bad weather may be different from city to city depending on the amount of snow removal equipment that they own. In this scenario, the amount of snow removal equipment that a city owns is which of the following? Dependent variable Residual Lurking variable Independent variable OOOOO Outlier Correlation Coefficients Consider the following list of possible correlation coefficients. Use this list to answer questions 11 through 13. (A) r= -1.05 (B) r = -0.98 (C)r = -0.64 (D) r = -0.36 (E) r = 0.04 (F) r = 0.63 (G) r = 0.93 (H) r = 1.4211 1 point Which of the choices reveals the strongest correlation between the two variables? O A O B OOOOOO Innmon 12 1 point1 point 5 Which of the choices reveals the weakest correlation between the two variables? 0 A O B O c O D O E O F O G O H 1 point 5 Which of the choices matches the relationship revealed in the scatterplot below? A B c D E F G H O O O O O O O O Six Person Data Sample A researcher collects data for a sample of six people, and records X and Y, as below. Use this data to complete questions 14 and 15. The last three columns are provided to help in case you decide to complete question 15 by hand. i I E I3 a 1 1o 1 100 10 3 7 9 49 21 5 3 25 9 15 3 4 64 16 32 1o 1 100 1 1o 12 _1 1 3? 26 343 1_i'6 100 The scatterplot is given below.Use this scatterplot to describe completely the relationship between X and Y. Y 12 10 6 0 2 4 6 8 10 12 XCalculate the correlation coefficient between X and Y. You may do the calculation by hand or with the calculator, partial credit will only be given if work is shown. BIYA A E E x X2 E 12pt Paragraph GO fx