One of the primary feeds for beef cattle is corn. The following table presents the average price (in dollars) for a bushel of corn and a pound of ribeye steak for 6 months.Corn Price (S/bu) Ribeye Price (S1b)6.3512.876.2013.305.8211.856.1812.646.0012.296.5714.16The least-squares regression line for predicing the ribeye price form the corn price is y = 2.8678x - 4.8904, and the correlation coefficient is r= 0.9280. Use this information toanswer the questions below.a. Predict the ribeye price in a month when the corn price is $6.40 per bushel. Round to the nearest cent.Ribeye price = $%3Db. Interpret the correlation coefficient by completing the following statement. "As the corn price increases, the price of ribeye

For the given data Find the required blanks

Answered: One of the primary feeds for beef…

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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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. LOADING... Click here to view the weight and gas mileage data. Question content area bottom Part 1 (a) Find the least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable. ModifyingAbove y with caretyequals=negative 0.00756−0.00756xplus+(44.844.8) (Round the x coefficient to five decimal places as needed. Round the constant to one decimal place as needed.) Part 2 (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. For every pound added to the weight of the car, gas mileage in the…
show how to do it on a TI-84 please and thank you From the data, find the least-squares regression line. What type of correlation is there? Study Hours Test Score 0 20 1 35 2 50 4 47.5 4 65 5 72.5 5 75 6 67.5 6 92.5 7 85 7 90 8 95 5 70 y=9.051+24.765x.y=9.051+24.765x. There is positive linear correlation. y=24.765−9.051x.y=24.765-9.051x. There is negative linear correlation. y=24.765+9.051x.y=24.765+9.051x. There is positive linear correlation. y=−24.765+9.051x.y=-24.765+9.051x. There is negative linear correlation y=9.051−24.765x.y=9.051-24.765x. There is negative linear correlation.
Two measures of a baseball player's effectiveness as a hitter are the number of hits he makes in a season and thenumber of times he "bats in" a run (knows as "Runs Batted In" or RBIs). Can we predict a batter's RBIs from hisMajor League Baseball batters in 2017.hits? Below is numerical and graphical output from a computer regression of RBIs on Hits for 12 randomly selected Major League Baseball batters in 2017. Assume that the conditions for inference have been satisfied.(a) Do these data provide convincing evidence that there is a linear relationship between RBIs and Flits for MajorLeague Baseball batters in 2017? (b) Construct a 95% confidence interval for the slope of the population regression line for predicting RBIs from Hits.
#3. What is the least squares regression line for the following set of data? y-hat = 2.18x + 27.74 y-hat = 2.14x + 27.44 y-hat = 1.94x + 26.24 y-hat =1.86x + 26.28
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. LOADING... Click here to view the weight and gas mileage data. Question content area bottom Part 1 (a) Find the least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable. ModifyingAbove y with caretyequals=enter your response herexplus+(enter your response here) (Round the x coefficient to five decimal places as needed. Round the constant to one decimal place as needed.)
Is It Getting Harder to Win a Hot Dog Eating Contest?Every Fourth of July, Nathan’s Famous in New York City holds a hot dog eating contest. The table below shows the winning number of hot dogs and buns eaten every year from 2002 to 2015, and the data are also available in HotDogs. The figure below shows the scatterplot with the regression line. Year Hot Dogs 2015 62 2014 61 2013 69 2012 68 2011 62 2010 54 2009 68 2008 59 2007 66 2006 54 2005 49 2004 54 2003 45 2002 50 Winning number of hot dogs in the hot dog eating contest Winning number of hot dogs and buns Click here for the dataset associated with this question. (a) Is the trend in the data mostly positive or negative? Positive Negative (b) Using the figure provided, is the residual larger in 2007 or 2008?Choose the answer from the menu in accordance to item (b) of the question statement 20072008 Is the residual positive or…
In baseball, two statistics, the ERA (Earned Run Average) and the WHIP (Walks and Hits per Inning Pitched), are used to measure the quality of pitchers. For both measures, smaller values indicate higher quality. The following computer output gives the results from predicting ERA by using WHIP in a least-squares regression for the 2017 baseball season. Variable DF Estimate SE T Intercept 1 -5.0 0.26 - 19.3 WHIP 1 6.8 0.14 47.4 Which of the following statements is the best interpretation of the value 6.8 shown in the output? ERA is predicted to increase by 6.8 units for each 1 unit increase of WHIP. WHIP is predicted to increase by 6.8 units for each 1 unit increase of ERA. For a pitcher with 0 units of WHIP, the ERA is predicted to be approximately 6.8 units. For a pitcher with 0 units of ERA, the WHIP is predicted to be approximately 6.8 units. Approximately 6.8% of the variability in ERA is due to its linear relationship with WHIP.
The data below represents commute times (in minutes) and scores on a well-being survey. Complete parts (a) through (d) below. Commute time (in minutes), x 5, 20, 25, 40, 60, 84, 105 Well-being index score, y 69.1, 67.8, 67.1, 66.3, 66.0, 64.3, 62.3 Find the least-squares regression line treating the commute time, x, as the explanatory variable and the index score, y, as the response variable. y=___x + ____ (round to three decimal places as needed).
The calories and sugar content per serving size of ten brands of breakfast cereal are fitted with a least squares regression line with computer outputs:
A pediatrician wants to determine the relation that exists between a child's height, x, and head circumference, y. 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. Click the icon to view the children's data. Data table (a) Find the least-squares regression line treating height y =x+ (O (Round the slope to three decimal places and round the d Height (inches), x Head Circumference (inches), y O. 28 17.6 24.5 17.1 25.75 17.1 25.75 17.5 24.25 17.0 27.75 17.7 26.5 17.3 27.25 17.6 26.5 17.3 26.5 17.5 27.75 17.6 Print Done Help me solve this View an example Get more help - Media - Clear all Check answer
A researcher records data on 7 adult pairs' heights (in inches) to compare the physical characteristics of brothers and sisters. Brother Sister 71 69 68 64 6 65 67 63 70 65 71 62 66 62 Mean 68.4285 64.2857 SD 2.2253 2.4299 r=0.4050 What would the least-squares regression equation be for predicting the brother's height from the sister's? A. brother's height = 0.037+44.58 * sister's height B. brother's height = 44.58 + 0.371* sister's height C. brother's height = 20.71 + 0.029 * sister's height D. brother's height = 3.28- 40.68 * sister's height If the sister's height is the same as the mean (64.2857 inches), what would the brother's predicted height be A. 68.4285 (the same as the mean as well) B. 62.1234 C. 70.8990 D. None of the above. Which of the following would be correct? A. The pair of means, (68.4285, 64.2857), lies on the linear regression line. B. The effectiveness of the linear regression model is about 16%, C. The effectiveness of the linear regression model is 10096. D. Both…
The following table represents the average price (in dollars) for a dozen eggs and a gallon of milk for five years. Dozen Eggs 1.14 1.29 1.28 1.31 1.36 Gallon of Milk 3.25 3.12 3.15 3.26 3.33 Determine the least-squares regression line. Select one: O a. ĝ = 0.1978r - 2.9926 O b. ý = 2.9926r +0.1798 O c. û = 2.9926r – 0.1798 O d. ŷ = 0.1978r + 2.9926

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