Answered: A set of X and Y scores has SSX = 8,…

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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For the data in the table, find the regression equation and then use it to answer the questions below. Here, x gives a student's annual family income (in $1000's), and y is the student's SAT score. Round the slope and y-intercept to two decimals, then do not round your answer. Income SAT ($1000's) Score 62 940 66 950 75 960 77 980 78 990 79 1010 82 1020 86 1080 90 1090 100 1100 a. What is the predicted score for a student whose annual family income is $115,000? 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
A set of X and Y scores has SSX = 26, SSY = 10, and SP = 42. What is the slope for the regression equation? Round your answer to 2 decimal places.
In the regression equation Y = 85.65 + 0.70X1 - 3.43X2, the intercept is a. 0.70 b. -3.43 c. 1 d. 85.65
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
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 = 0.25
For the relationship between Calories and Carbs, here is the equation of the line of best fit: Regression Equation: Calories = 2.36 + 4.432 Carbs What would you predict for the number of Calories if a cereal had 28 Carbs?
The arm span and foot length were both measured (in centimeters) for each of 20 students in a biology class. The computer output displays the regression analysis. Which of the following is the best interpretation of the coefficient of determination r2? About 37% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 65% of the variation in foot length is accounted for by the linear relationship formed with the arm span. About 63% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 63% of the variation in foot length is accounted for by the linear relationship formed with the arm span.
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were: y=a+bx b=-0.997 a=20.107 r2=0.950625 r=-0.975 Use this to predict the number of situps a person who watches 0.5 hours of TV can do.Round to one decimal place.
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…
Solve for the y-intercept and the slope. Form the equation of the regression line that describes the relationship between the two variables. Predict the profit of the fashion boutique business when the store measures 3,800 square feet. Explain the result.
A regression analysis was performed to determine if there is a relationship between hours of TV watched per day () and number of sit ups a person can do (y). The results of the regression were: y=ax+b a=-1.153 b=22.899 r2=0.649636 r=-0.806 Use this to predict the number of sit ups a person who watches 8 hours of TV can do, and please round your answer to a whole number.
Find the intercept (b0) for the regression equation for the following values. Round to 3 decimal places. Intercept xi yi 33 180 25 170 50 200 65 172 57 160 27 165

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A set of X and Y scores has SSX = 8, SSY = 15, and SP = 40. What is the slope for the regression equation?​ Select one: a. ​ 2 b. ​ 4 c. ​ 5 d. ​ 3

A set of X and Y scores has SSX = 8, SSY = 15, and SP = 40. What is the slope for the regression equation? Select one: a. 2 b. 4 c. 5 d. 3