Linear Regression and Correlation.X y11.5622.9231.384-6.6653.36-4.04Compute the equation of the linear regression line in the form y = mx + b, where m is the slope and b is theintercept.Use at least 3 decimal places. (Round if necessary)y =Compute the correlation coeficient for this data set. Use at least 3 decimal places. (Round if necessary)r=Compute the P-value (Use HA: slope 0 for the alternative hypothesis.)Use at least 3 decimal places. (Round if necessary)P-value=At the alpha= 0.01 significance level, is the correlation significant?O NoOYes, significant correlationSubmit Question@2W#3E$S44R%5T6Y&7U* 0084+1(9

Solution-: We have following data: X Y 1 1.56 2 2.92 3 1.38 4 -6.66 5 3.3 6 -0.04…

Answered: Linear Regression and Correlation. X y…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Predict the average lifespan of an animal in years when the incubation/gestation time is 12 months. Animal: Nile crocodile, Aldabra giant tortoise, Lake sturgeon,Galápagos tortoise, Bowhead whale Average Lifespan (in Years):100 152 152 177 211 Incubation/ Gestation (in Months)3 8 0.25 4.7 regression equation and regression line if needed
Part and b. Thank you!
EQuestion Help 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 IA Test score,y 3 (a) x=2 hours (c) x= 12 hours (b) x = 25 hours (d) x= 4.5 hours 38 44 50 47 61 68 Find the regression equation. y = 6.269 x+ (32.48) (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) Choose the correct graph below. OD. OB. OC. O A. 80- 80- 80 80-4 0-+ Hours studying Hours studying Hours studying Hours studying 10 18 PM (E) More 10/3/2020 Click to select your answer(s)
Help?
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 Test score, y 4 (a) x = 2 hours (c) x = 13 hours (b) x= 2.5 hours (d) x = 4.5 hours 2 3 5 40 45 52 49 63 70 Find the regression equation. ý =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. O A. OB. OC. OD. 80- 80- Hours studying Hours studying Hours studying Hours studying (a) Predict the value of y for x= 2. Choose the correct answer below. O A. 52.2 О В. 49.2 ОС. 64.2 O D. not meaningful (b) Predict the value of y for x = 2.5. Choose the correct answer below. O A. 115.4 О В. 52.2…
Forest Fires and Acres Burned Numbers (in thousands) of forest fires over the year and the number (in hundred thousands) of acres burned for 7 recent years are shown. Number of fires x 58 47 84 62 57 72 69 Number of acres burned y 54 43 80 58 53 68 65 The correlation coefficient for the data is =r1 and =α0.05 . Should regression analysis be done? The regression analysis should not be done. The regression analysis should be done. Find the equation of the regression line. =y′+abx =a =b Find y′ when =x50 . =y′
Two variables are defined, a regression equation is given, and one data point is given. Study = number of hours spent studying for an exam Grade = grade on the exam GRADE= 41.0 + 3.7 (STUDY) THE DATA POINT IS A STUDENT WHO STUDIED 10 HOURS AND RECIEVED AN 81 ON THE EXAM…
Data Set: {(-3, 4), (-2, 3), (–1,3), (0, 7), (1, 5), (2, 6), (3, 1)} 1. The regression line is: y = when the 2. Based on the regression line, we would expect the value of response variable to be explanatory variable is 0. 3. For each increase of 1 in of the explanatory variable, we can expect a(n) in the response variable. 4. If x = -3.5, the y = This is an example of 5. The correlation coefficient is r = (Round to the nearest hundredth.) Check of

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