uestion Completion Status:PQUESTION 8Refer to the data in the table below.−3-2-1.500.522.5-1-1.50.500.52.5y23Palja: Make a scatter plot and determine which type of model best fits the data.Part b: Find the regression equation.Part c: Use the equation from Part b to determine y when x = 7.For the toolbar, press ALT+F10 (PC) or ALT+FN+F 10 (Mac).BIUS ParagraphArialXEt PClick Save and Submit to save and submit. Click Save All Answers to save all answers.a10ptDELL343!

Answered: Refer to the data in the table below.…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. Height, x Stories, y 519 (a) x = 500 feet (c) x = 810 feet (b) x = 649 feet (d) x = 732 feet 775 619 508 491 474 36 53 47 44 43 37 Find the regression equation. y=x+ O (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) Choose the correct graph below. OA. 60- 60- 60- 60- 800 Height (feet) 800 Height (feet) 800 Height (feet) Height (feet) (a) Predict the value of y for x = 500. Choose the correct answer below. A. 52 В. 40 C. 48 D. not meaningful (b) Predict the value of y for x = 649. Choose the correct answer below. A. 56 В. 48 O C. 40…
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The number of hours 6 students spent for a test and their scores on that test are shown below. Hours spent studying, x 0 Test score, y 38 Find the regression equation. 2 3 3 4 6 45 50 49 61 68 0 (a) x = 2 hours (c) x = 15 hours (b)x=4.5 hours (d) x=2.5 hours y = X + (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.)
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An instructor asked a random sample of eight students to record their study times at the beginning of a course. She then made a table for total hours studied (x) over 2 weeks and test score (y) at the end of the 2 weeks. The table is given below. Complete parts (a) through (f). x 10 13 10 18 6 15 16 21 y 93 79 81 74 85 81 85 80 a. Find the regression equation for the data points. b. Graph the regresson equation c. Describe the apparent relationship between the two variables. d. Identify the predictor and response variables. e. Identify outliers and potential influential observations. f.Predict the score for a student that studies for 17 hours.
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a. Using the pairs of values for all 10 points, find the equation of the regression line. b. After removing the point with coordinates (2,3), use the pairs of values for the remaining 9 points and find the equation of the regression line. c. Compare the results from parts (a) and (b).
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. x 11.3 8.5 y 13.4 7 3.6 2.6 2.2 2.6 0.8 11 10.2 7.4 6 5.7 6.3 4.9 * = thousands of automatic weapons y = murders per 100,000 residents Determine the regression equation in y = ax + b form and write it below. (Round to 2 decimal places) A) How many murders per 100,000 residents can be expected in a state with 10.1 thousand automatic weapons? Answer = Round to 3 decimal places. B) How many murders per 100,000 residents can be expected in a state with 9.9 thousand automatic weapons? Answer = Round to 3 decimal places.
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Refer to the data in the table below. -3 3 -4 -2 -1.5 0 0.5 2 2.5 -2 -1 -1.5 0 0.5 0.5 2.5 2 3 Palsa: Make a scatter plot and determine which type of model best fits the data. Part b: Find the regression equation. Part c: Use the equation from Part b to determine y when x = 7. 4 3