01,0002,000Mass (kg)O Predicted: 22.86 miles per gallonResidual: -14.475 miles per gallonPredicted: 22.86 miles per gallonResidual: 2.86 miles per gallonPredicted: 20 miles per gallonResidual: -2.86 miles per gallonO Predicted: 22.86 miles per gallonResidual: 20 miles per gallonO Predicted: 22.86 miles per gallonResidual: -2.86 miles per gallonMark this and return3,0004,000Save and ExittvNextAMSubmit ovThe scatterplot below shows the relationship between mass, x, in kilograms of a car and its fuel efficiency, y, inmiles per gallon. The least-squares line is also shown on the scatterplot. The equation of the least-squares line isŷ = 37.335 -0.00965x. Find the predicted and residual gas mileage for a car that weighs 1,500 kilograms and hasa gas mileage of 20 miles per gallon.Fuel Efficiency and Mass for CarsFuel Efficiency (mpg)4030201001,000Mark this and return2,000Mass (kg)3,0004,000Save and ExitMTtvNextARSubmit

The question is about regression Given : Regression equation : y^ = 37.335 - 0.00965x Where, x :…

Answered: The scatterplot below shows the…

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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The least-squares regression equation is y=784.6x+12,431 where y is the median income and x is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.7962. Predict the median income of a region in which 25% of adults 25 years and older have at least a bachelor's degree.
study investigated how the content of vitamin A in carrots is affected by the time being cooked. In this example: X represents the amount of time, in minutes, that the carrot slices were cooked Y represents the content of vitamin A (in milligrams) in the carrot slices The least-squares regression equation for this relationship is: Y = 22.4 – 0.65X Using the regression equation, predict the vitamin A content (in milligrams) for a carrot slice that was cooked for 15 minutes. Provide your answer as a numeric value rounded to two decimal places.
Biologist Theodore Garland, Jr. studied the relationship between running speeds and morphology of 49 species of cursorial mammals (mammals adapted to or specialized for running). One of the relationships he investigated was maximal sprint speed in kilometers per hour and the ratio of metatarsal-to-femur length. A least-squares regression on the data he collected produces the equation ŷ = 37.67 + 33.18x where x is metatarsal-to-femur ratio and y is predicted maximal sprint speed in kilometers per hour. The standard error of the intercept is 5.69 and the standard error of the slope is 7.94. Construct a 96% confidence interval for the slope of the population regression line. Give your answers precise to at least two decimal places. contact us help 6:42 PM povecy polcy terms of use careers A E O 4») 18 -క90.4 58 12/14/2020 a 17 |耳即 delets prt sc insert 112 19 18 + 16 backspace f5 fA
A least squares regression model performed to predict the selling price of houses found the following equation: Pricê = 169.328+35.3Area + 0.718Lotsize - 6543Age where Price is in dollars, Area is in square feet, Lotsize is in square feet, and Age is in years. The R2 is 0.92. One of the following interpretations is correct. Which is it? Explain why. a.) Each year a house Ages, it is worth $6543 less. b.) Every extra square foot of Area is associated with an additional $35.30 in average price, for houses with a given Lotsize and Age. c.) Every dollar in price means Lotsize increases 0.718 square feet. d.) This model fits 92% of the data points exactly.
The cost of a leading liquid laundry detergent in different sizes is given below. Size (ounces) Cost ($) 16 3.59 32 4.39 64 5.19 200 10.19 Calculate the least squares line. Put the equation in the form of: ŷ = a + bx. (Round your answers to three decimal places.)ŷ = + x
Use the least squares regression model to estimate the maximum sustained wind speed in a hurricane when the pressure reading is 950 mb. Interpret the slope of the least squares regression model in the context of wind speed and atmospheric pressure. Determine the coefficient of determination and interpret its meaning in the context of wind speed and atmospheric pressure.
Biologist Theodore Garland, Jr. studied the relationship between running speeds and morphology of 49 species of cursorial mammals (mammals adapted to or specialized for running). One of the relationships he investigated was maximal sprint speed in kilometers per hour and the ratio of metatarsal-to-femur length. A least-squares regression on the data he collected produces the equation ŷ = 37.67 + 33.18x %3D where x is metatarsal-to-femur ratio and ŷ is predicted maximal sprint speed in kilometers per hour. The standard error of the intercept is 5.69 and the standard error of the slope is 7.94. Construct an 80% confidence interval for the slope of the population regression line. Give your answers precise to at least two decimal places. Lower limit: Upper limit:
An article gave data on a measure of pollution (in micrograms of particulate matter per cubic meter of air) and the cost of medical care per person over age 65 for six geographical regions of the United States. Find the equation of the least-squares line describing the relationship between y = medical cost and x = pollution. (Give the answer to two decimal places.) ŷ = Region North eBook Upper South Deep South West South Big Sky West Additional Materials Pollution Cost of Medical 30.0 922 31.8 898 32.1 975 26.8 979 30.4 959 40.0 906
A researcher want to know if there is a relationship between sleep and anxiety. The researcher randomly selected n = 5 participants and asked each to rate their sleep quality and anxiety level on a scale of 1 to 5. The data are below: Sleep X Anxiety Y 2 2 3 3 2 2 4 2 5 2 Calculate the Sum of Squares for X (SSX)
An article gave a scatter plot, along with the least squares line, of x = rainfall volume (m³) and y data on rainfall and runoff volume (n = runoff volume (m³) for a particular location. The simple linear regression model provides a very good fit to 15) given below. The equation of the least squares line is y = -2.364 + 0.84267x, ² 0.976, and s = 5.21. = x 5 12 14 17 23 30 40 47 55 67 72 81 96 112 127 y 3 9 12 14 14 24 27 45 38 46 52 71 81 100 101 (a) Use the fact that s = 1.43 when rainfall volume is 40 m³ to predict runoff in a way that conveys information about reliability and precision. (Calculate a 95% PI. Round your answers to two decimal places.) Ŷ 28.25 1x ) m³ Does the resulting interval suggest that precise information about the value of runoff for this future observation is available? Explain your reasoning. OYes, precise information is available because the resulting interval is very wide. 34.46 Yes, precise information is available because the resulting interval is very…

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