A data set is given below.(a) Draw a scatter diagram. Comment.on the type of relation that appears to exist between x and y.(b) Given that x 3.5000, s, = 2.5884, y = 4.3167, s, = 1.9467, and r= -0.9546, determine the least-squares regression line.(c) Graph the least-squares regression line on the scatter djagram drawn in part (a).1.66.0 6.7 5.4 3.1 2.2 2.556y(a) Choose the correct graph below.O AOB.Oc.OD.Ay0-There appears to beV relationship.(b) ý =x+ (O(Round to three decimal places as needed.)(c) Choose the correct graph below.O AOB.Oc.OD.

For the given data Find Regression equation and scatter plot

Answered: A data set is given below. (a) Draw a…

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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A study of fuel economy for various automobiles plotted the fuel consumption vs. speed. A LSRL was fit to the data. Here is the residual plot from this least-squares fit. What does the pattern of the residuals tell you about the linear model? 3. 2
Seven North American Green Frogs (Rana clamitans) had their jumping distance recorded (in mm) multiple times in a laboratory. The mean jumping distance for these frogs along with their length (measured from snout to vent in miMillimeters) are presented in the table below. Length of Frog 52 68 37 65 77 81 59 Mean Jumping Distance 546 673 415 659 793 814 563 (a) Determine the linear regression model that will best predit the mean jumping distance of a North American Green Frog based on the frog's length. (b) How well does the linear regression model fit this sample data? (c) Use the linear regression model to predict the mean jumping distance of a North American Green Frog that is 48 mm in length. No excel, please.
3B please help me with the solution and answer. This is for my reviewer only thank you
Use correlation coefficients to determine which of the given sets of data is best fit by its associated regression line and which is fit worst. a. ((6, 8), (3, 14), (7, 6)) b. ((5, 6), (6,5), (7, 6)) c. ((5, 5), (10, 0), (7, 7.1)) Select the data set with the best fit. O ((6, 8), (3, 14), (7, 6)) ((5, 6), (6, 5), (7, 6)) ((5, 5), (10, 0), (7, 7.1)) Select the data set with the worst fit. O ((6, 8), (3, 14), (7, 6)) ((5, 6), (6, 5), (7, 6)) ((5, 5), (10, 0), (7, 7.1)) Is it a perfect fit for any of the data sets? Yes No
Consider the set of points (0,9),(1,5),(6,3) and (9,2). In this set of points, the age of a dolphin is the first part of each ordered pair and the second part is the number of tricks that the dolphin learned in a month. So, the 6 year-old dolphin learned 3 tricks in the month. Write the least squares regression line for this data. Use the line to estimate how many tricks a 4 year-old dolphin could learn. Then find r and r2. Explain what r2 means.
An engineer wants to determine how the weight of a gas-powered car, x, affects gas mileage, y. The accompanying data represent the weights of various domestic cars and their miles per gallon in the city for the most recent model year. Complete parts (a) through (d) below. (a) Find the least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable. y=nothingx+(nothing) (Round the x coefficient to five decimal places as needed. Round the constant to one decimal place as needed.) (b) Interpret the slope and y-intercept, if appropriate. Choose the correct answer below and fill in any answer boxes in your choice. (Use the answer from part a to find this answer.) A. A weightless car will get nothing miles per gallon, on average. It is not appropriate to interpret the slope. B. For every pound added to the weight of the car, gas mileage in the city will decrease by nothing mile(s) per gallon, on…
The weight (in pounds) and height (in inches) for a child were measured every few months over a two-year Using technology, what is the slope of the least-squares regression line and what is its interpretation? period. The results are given in the table. The slope is 1.98, which means for each additional 35 inch in height, the child's weight will increase by 1.98 Weight (x) 8. 12 18 24 30 32 37 40 30 32 33 36 38 pounds. Helght (v) 22 23 26 35 The slope is 1.98, which means for each additional inch in height, the child's weight is predicted to increase by 1.98 pounds. The slope is 0.50, which means for each additional pound in weight, the child's height will increase by 0.5 inches. The slope is 0.50, which means for each additional pound in weight, the child's height is predicted to increase by 0.5 inches.
3. In a study of 1991 model cars, a researcher computed the least-squares regression line of price (in dollars) on horsepower. He obtained the following equation for this line. Price = -6677 + 175 × Horsepower
estion 7 of 15 Suppose the manager of a gas station monitors how many bags of ice he sells daily along with recording the highest temperature each day during the summer. The data are plotted with temperature, in degrees Fahrenheit (°F), as the explanatory variable and the number of ice bags sold on as the response variable. The least squares regression (LSR) line for the data is y = -114.05 +2.17x. On one of the observed days, the temperature was 82 °F and 66 bags of ice were sold. Determine the number of bags of ice predicted to be sold by the LSR line, ŷ, when the temperature is 82 °F. Enter your answer as a whole number, rounding if necessary. ice bags Using the predicted value you just found, compute the residual at this temperature. residual = ice bags DOLL
(b)
Weight (pounds), x Miles per Gallon, y 3769 18 3937 15 2662 24 3612 18 3347 20 2917 24 3640 17 2668 24 3381 18 3880 17 3286 19
A pediatrician wants to determine the relation that exists between a child's height, x, and head circumference, v. She randomly selects 11 children from her practice, measures their heights and head circumferences, and obtains the accompanying data. Complete parts (a) through (g) below. A Click the icon to view the children's data. (a) Find the least-squares regression line treating height as the explanatory variable and head circumference as the response variable. y=x+ (D (Round the slope to three decimal places and round the constant to one decimal place as needed.) (b) Interpret the slope and y-intercept, if appropriate. First interpret the slope. Select the correct choice below and, if necessary. in the answer box to complete your choice. O A. For every inch increase in height, the head circumference increases by (Round to three decimal places as needed.) in., on average. O B. For a height of 0 inches, the head circumference is predicted to be (Round to three decimal places as…

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