Consider the following table of data.234y 1111.1(a) Calculate the correlation coefficient.(b) Sketch a graph of the data.(c) Based on how closely the data fits a straight line, is youranswer to part (a) surprising? Discuss the extent to whichthe correlation coefficient describes how well the data fit ahorizontal line.

Answered: Image /qna-images/answer/e83e6485-1b19-4fb8-81ba-6d4885ef89ea.jpg

Answered: Consider the following table of data. 2…

Calculus: Early Transcendentals

8th Edition

ISBN:9781285741550

Author:James Stewart

Publisher:James Stewart

Chapter1: Functions And Models

Section: Chapter Questions

Problem 1RCC: (a) What is a function? What are its domain and range? (b) What is the graph of a function? (c) How...

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The data below was collected from manufacturer advertisements of their vehicles horsepower (x) and highway gas mileage (mpg=y). Use this data to answer the following questions. horsepower 146 250 340 350 390 190 220 mpg 33 28 15 17 11 35 42 1. Find the p-value to determine if there is a linear correlation between horsepower and highway gas mileage (mpg). Record the p-value below. Round to four decimal places.p-value==2. Is there a linear correlation between horsepower and highway gas mileage (mpg)? 3. If there is a linear correlation, write the correlation coefficient below. Otherwise, leave it blank. Round your final answer to four decimal places. Be careful with your sign.r=r= 4. If there is a linear correlation, write the regression equation below. Otherwise, leave it blank. Round all numbers to four decimal places.ˆy=y^=5. Using the data shown above, predict the the highway gas mileage (mpg) for a car that has a horsepower of 225. Round your final answer to two decimal…
Let x be the average number of employees in a group health insurance plan, and let y be the average administrative cost as a percentage of claims. x 3 7 15 32 75 y 40 35 30 26 18 (a) Make a scatter diagram of the data and visualize the line you think best fits the data. Flash Player version 10 or higher is required for this question. You can get Flash Player free from Adobe's website. (b) Would you say the correlation is low, moderate, or strong? positive or negative? strong and negative moderate and negative strong and positive low and negative low and positive moderate and positive (c) Use a calculator to verify that Σx = 132, Σx2 = 6932, Σy = 149, Σy2 = 4725, and Σxy = 2997. Compute r. (Round your answer to three decimal places.)r = As x increases, does the value of r imply that y should tend to increase or decrease? Explain. Given our value of r, we cannot draw any conclusions for the behavior of y as x increases. Given our value of r, y should tend to…
Part A: What is the most likely value of the correlation coefficient of the data in the table? Based on the correlation coefficient, describe the relationship between time and surface area of the lake. [Choose the value of the correlation coefficient from −1, −0.98, −0.5, −0.02.] Part B: What is the value of the slope of the graph of surface area versus time between 15 and 20 days, and what does the slope represent? Part C: Does the data in the table represent correlation or causation? Explain your answer.
The numbers of pass attempts and passing yards for seven professional quarterback for a recent year are listed in the table below. Round all answers to the nearest 1000th. Pass attempts (x) 449 565 528 197 670 351 218 Passing Yards (y) 3265 4018 3669 1141 5177 2362 1737 Calculate the sample correlation coefficient, r. Describe the type of correlation coefficient and interpret the correlation in the context of the data. Find the equation of the regression line for the data. Use the regression equation to predict the average number passing yards if the pass attempts are 250.
Which of the following is the most appropriate equation to model the data? ŷ = –10.89x + 0.85 ŷ = –0.85x + 10.89 ŷ = 10.89(0.85)x ŷ = 0.85(10.89)x
A random sample of college students was surveyed about how they spend their time each week. The scatterplot below displays the relationship between the number of hours each student typically works per week at a part- or full-time job and the number of hours of television each student typically watches per week. The correlation between these variables is r = –0.63, and the equation we would use to predict hours spent watching TV based on hours spent working is as follows: Predicted hours spent watching TV = 17.21 – 0.23(hours spent working) Since we are using hours spent working to help us predict hours spent watching TV, we’d call hours spent working a(n) __________________ variable and hours spent watching TV a(n) __________________ variable. The correlation coefficient, along with what we see in the scatterplot, tells us that the relationship between the variables has a direction that is _________________ and a strength that is ______________________. According to the…
Use the data in the table, which shows the average annual salaries (both in thousands of dollars) for public school principals and teachers in the U.S. for 11 years. Apply what you have learned in the previous tab to complete this graded lab questions. 1. Repeat the steps from tab #1 using this data to construct a scatter plot graph and calculate the correlation coefficient R. (Recall the corelation coefficient is R and not R Teachers y Principalsx 77.8 43.7 78.4 43.8 80.8 45.0 R= 80.5 45.6, 2. Does the R value represent a positive, negative or no correlation between the salaries ol the teachers and principals? As teacher salaries increase, what happens to prinicipal salaries? 10 11 81.5 45.9 84.8 48.2 12 13 87.7 49,3 3. Write the equation of the regression line for the data below. The equation is y= 14 91.6 51.3 52.9 Teachers y 15 16 95.7 54.4 COD 54.2 =D0.5873x-2.0s07o R=0.995, 17 95.7 4. Use the regression equation that you found in exercise #3 to predict the average annual salary…
A veterinarian collects data about puppies in her practice. She makes a scatterplot with their age in days on the horizontal axis and weight in ounces (oz) on the vertical axis and sees that the scatterplot is football shaped. The average age of the puppies is 42 day, with an SD of 7 days. The average weight is 25 oz, with an SD of 5 oz. The correlation is moderately strong, with r = 0.7. 4. (a) The age of two puppies differ by 20 days. The difference in their weight is predicted to be oz. (b) The baseline prediction for the weight of puppies ignores their age and just uses the information from all puppies. The baseline predicted weight is oz and the RMS error for this prediction is o. (c) Suppose we converted the units of age from days to weeks. The average age is now weeks, with an SD of weeks. The correlation between age in weeks and weight in oz is now r =
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Below is the actual data on the speed a person walks or runs in miles/hour and the calories the person burns per lap. Find the linear equation of best fit for this data. Compare the model to the data. Does the model seem to fit the data? Explain. What is the significance of the y-intercept? What is the slope and what does it mean? What is the x-intercept and what does it mean? What is the correlation coefficient and what does it mean? Speed (mph) Calories/lap 1 42 2 31 3 27 4 41 5 40 6 40 7 39 8 38 r answers to the nearest hundredth. The y-intercept means that if a person runs at ----------mph they will burn__________ per lap. The slope means that for each mph you increase your speed, you will burn an additional------------calories pay lap
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Direction: Answer the problem below. Show your solution. Mr. David runs to keep himself physically fit. He wants to know if there is a relationship between the time elapsed and the kilometers he ran. Kilometers ran Time (in minutes) (X) (Y) 1 10 90 2 10 60 3 16 150 4 16 90 5 21 160 21 180 a. Calculate the Pearson correlation coefficient and regression line based on the data below, b. Draw a scatter plot. Activate Windows N Go to PC settings to activate Windows.

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