A group of students measure the length and width of a random sample of beans. They are interested ininvestigating the relationship between the length and width. Their summary statistics are displayed in thetable below. All units, if applicable, are millimeters.Mean widthStandard deviation of widthMean heightStandard deviation of heightCorrelation coefficient7.560.87713.8941.7460.837Round your answers to three decimal places.The students are interested in using the width of the beans to predict the height. Calculate the slope ofthe regression equation.Write the equation of the line of best fit that can be used to predict bean heights. Use a to representwidth and y to represent height.What fraction of the variability in bean heights can be explained by the linear model of bean height vs.width? Express your answer as a decimal.If, instead, the students are interested in using the height of the beans to predict the width, calculate theslope of this new regression equation.Write the equation of the line of best fit that can be used to predict bean widths. Use a to representheight and y to represent width.

Given table represent data for height and width of beans. Mean width: 7.56 Standard deviation…

Answered: The students are interested in using…

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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What is the dollar amount of change in sales for each new year according to the regression (slope) model? Do not use commas or $ in your answer.
The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 40 inches. Is the result close to the actual weight of 352 pounds? Use a significance level of 0.05. Chest size (inches) *Weight (pounds) 44 54 328 528 41 55 39 51 418 580 296 503 Click the icon to view the critical values of the Pearson correlation coefficient r. - What is the regression equation? x (Round to one decimal place as needed.)
H. Use the model to predict sales when the business spends $885 ($'000) in the advertisement. Does the model underestimate or overestimate sales? G. What is the value of the coefficient of determination, R2? What does R2 tell us about explained variation in y? (Refer to Coefficient of Determination LO 12-4). H. Use the model to predict sales when the business spends $885 ($'000) in the advertisement. Does the model underestimate or overestimate sales?
For the data in the table, find the regression equation. Here, x gives the number of calories in a hot dog, and y is the number of mg of sodium. Round the slope and y-intercept to two decima below. hen use your equation to answer the question Calories Sodium(mg) 100 311 110 304 120 308 130 337 140 320 160 341 170 375 180 353 190 362 200 372 Every extra 10 calories would be expected to add how many mg of sodium? Submit Question
The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 63 inches. Is the result close to the actual weight of 522 pounds? Use a significance level of 0.05. Chest size (inches) 58 50 65 59 59 48 D 414 312 499 450 456 260 Weight (pounds) Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y=+x (Round to one decimal place as needed.) What is the best predicted weight of a bear with a chest size of 63 inches? The best predicted weight for a bear with a chest size of 63 inches is pounds. (Round to one decimal place as needed.) Is the result close to the actual weight of 522 pounds? O A. This result is not very close to the actual weight of the bear. O B. This result is exactly the same as the actual weight of the bear. O C. This result is close to the actual weight of the…
We run the following regression using a sample of 148 women living in the western states. The variable wage is the hourly wage ( in USD) and educ is the number of years of education completed. wage = -3.07 + 1.52 educ Which statement best described the estimated slope coefficient? Group of answer choices A 1.52 extra years of education is predicted to increase wage by 1 USD An extra year of education is predicted to increase hourly wage by 1.52 USD A 1 percent increase in education is predicted to increase wage by 1.52 percent A 1.52 percent increase in education is predicted to increase wage by 1
Part a: 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 = 1.5.
The table shows the lengths and weights of seven muskies captured by the Department of Natural Resources in Catfish Lake in Eagle River, Wisconsin. Use the linear regression feature on a graphing calculator to determine an equation of the line that best fits the data. Round to the hundredths. Musky 1 2 3 4 5 6 7 Length (in.) 26 27 29 33 35 36 38 Weight (lb) 5 8 9 12 14 14 19
For the data in the table, find the regression equation and then use it to answer the questions below. Here, x gives the number of years of experience for nurses, and y is their annual salary (in $1000's). Round the slope and y-intercept to two decimals, then do not round your answer. Years of Salary Experience ($1000's) 2 41 4 45 8 51 9. 52 12 53 14 54 16 55 18 56 19 57 25 60 a. What is the predicted salary (in $1000's) for a nurse with 33 years of work experience? b. Is your answer to part (a) an extrapolation? O No: the value of x is within the range of the data, so the prediction is meaningful O Yes: the value of x is outside the range of data, so the prediction may not be meaningful Submit Question
Using the weights (Ib) and highway fuel consumption amounts (mi/gal) of the 48 cars listed in the accompanying data set, one gets this regression equation: y = 58 9-0.00749x, where x represents weight Complete parts (a) through (d). Click the icon to view the car data. 東 b. What are the specific values of the slope and y-intercept of the regression line? O A. The slope is 58.9 and the y-intercept is 0.007499. B. The slope is -0.00749 and the y-intercept is 58.9. O C. The slope is 58.9 and the y-intercept is -0.00749. O D. The slope is 0.00749 and the y-intercept is 58.9. c. What is the predictor variable? O A. The predictor variable is highway fuel consumption, which is represented by x. B. The predictor variable is weight, which is represented by x. O C. The predictor variable is weight, which is represented by y O D. The predictor variable is highway fuel consumption, which is represented by y. d. Assuming that there is a significant linear correlation between weight and highway fuel…
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