Search 00 '1 14%il:.|' Checkpoint Module 3 Question 1 Seamerplou Sumerplot a Rndlnn Tut Scum lzdlng 1'- n Scar-2 Scamerplalc Reading Tm Seam 12 I3 14 '5 Yuri Sirlo- Purcha- Which one of the four scatterplots above shows a relationship with a strong non linear pattern? A. r Scatterplot A Scatterplot B r' r Scatterplot C r B. C. D. Scatterplot D Search 00 '1 14%\": Question 2 acumerplaa A Sumerplot a nding TIIIBnan Rudlng Tut amn: Scamrplot D Rndlnu Tan Econ 12 I3 14 Yuan Sim:- Purchas- Which one of the four scatterplots above shows two variables with a strong negative linear association? A. F Scatterplot A B. C. D. Scatterplot D Scatterplot B Scatterplot C l" r. r. Search 00 '1 14%ll:.|' Question 3 acumerplaa A Sumerplot a Rnlng TIIIBnan Rudlng Tut amn: Somerplot C Scamrplot D Rndlnu Tan Econ 12 I3 14 Yuan Sim:- Purchas- Whieh one of the four scatter-plots above matches the following description: \"For children who are age 10 17, there is a strong positive linear association between a child's age and his/her reading test score?\" A. Scatterplot A Scatterplot B B. C. Scatterplot C D. Scatterplot D \fSearch out 1- '1 14%ll:.|' Question 6 The scatterplot below shows Olympic gold medal performances in the long jump and the high jump from 1900 to 1988. Each point shows the long jump distance that won the gold medal and also the height that won the high jump for the same year. The correlation between the two kinds of jumps is 0.89. Olympic Gold Medal Performances 13' a) .c U .E o. E 3 .1: E' I 80 85 Long jump (inches) What would be a reasonable explanation for this high correlation? A. r The athletes' age is a lurking variable explaining the association between long jump and high jump performance. Long jumpers have improved their performance and this has inspired the high jumpers to improve their performance. i" . . Athletes have gotten better over time and performance 1mprovements have occurred in both events over time. Question 7 The next scatterplot shows Olympic gold medal performances in the long jump from 1900 to 1988. The long jump is measured in meters. The regression equation is predicted long jump = 7.24 + 0.014 (year since 1900). Search 0- --:::- '1 14%ll:.|' 20 BO 80 100 120 veer since 1900 What does the slope of the regression line tell us? A. (I Each year the winning Olympic long jump performance is expected to increase 7.24 meters. B. F Each year the winning Olympic long jump performance is expected to increase 0.014 meters. C. f\" Each time the Olympics are held (generally every four years), the long jump gold medal winner will denitely achieve a 0.014 meter increase over the previous gold medal winner. D. r. Each time the Olympics are held (generally every four years), there is a predicted 1.4% increase in long jump performance. Question 8 Again, the scatterplot below shows Olympic gold medal performances in the long jump from 1900 to 1988. The long jump is measured in meters. 20 so an 100 120 ' War since mm For the regression line predicted long jump 2 7.24 + 0.014 (year since 1900), what does the 7.24 tell us? F 7.24 meters is the predicted value for the long jump in 1900. F 7.24 meters is the actual value for the long jump in 1900. A. B. C. r\" 7.24 is the minimum value for the long jump from 1900 to 1988. D. (I. 7.24 meters is the predicted increase in the winning long jump distance for each additional year after 1900. Search 0- --:::- '1 14%ll:.|' Question 9 Again, the scatterplot below shows Olympic gold medal performances in the long jump from 1900 to 1988. The long jump is measured in meters. 20 40 BO 30 100 120 veer since 1900 For this linear regression model, I2 = 0.90. What does this mean? The maximum long jump was around 90 inches. Each year the winning long jump distance increased by 90%. 90% of the variation in long jump distances is explained by the regression line. The data ends around 1990. Question 10 The Olympics were not held in 1940 because of World War II. If the Olympics had happened in 1940, how could you estimate the gold medal winning distance in the long jump for that year? A. P Plug 40 into the regression equation: predicted long jump = 7.24 + 0.014 (40). B. r Plug 1940 into the regression equation: predicted long jump = 7.24 + 0.014 (1940). Question 11 The standard error 56 for this linear model for Olympic gold medal performances in the long jump from 1900 to 1988 is about 0.2. In terms of estimating long jump distances, what does this mean? r . . A. On the average, estimates Will be up to 0.2 meters too short. On the average, estimates will be either be 0.2 meters too short or too long. r. r 20% of the error in the estimates is explained by the regression line. r\" B. C. D. 4% of the error in the estimates is explained by the regression line. Search 00 '1 14%ll:.|' Question 12 Scatterplot of Ave. Daily New Savings Accounts vs Rate O Muhmmwmm Ava. Dally New Sav. Account: (3.. 0.0% 0.6% 1.2% 1.8% 2.4% 3.0% 3.6% 4.2% Rate Each month a bank adjusts the initial interest rate it offers to customers who wish to open a new high-yield savings account. The bank wants to determine if there is a relationship between the initial interest rate and the average daily number of new savings accounts. The bank plans to use the interest to predict the average number of new savings accounts opened in a month. Which one of the following statements is correct? F . . A. Both the Interest rate and the average daily number of new accounts are explanatory variables. P Both the interest rate and the average daily number of new accounts are response variables. Average daily number of new accounts is the response variable. Interest rate is the explanatory variable. i" Interest rate is the response variable. Average daily number of new accounts is the explanatory variable. Search 00 '1 14%ll:.|' Question 13 Scatterplot of Ave. Daily New Savings Accounts vs Rate O Ava. Dally New Sav. Account: 0 <3 Rate