10-10-81-61110-.....sider the scatterplot given above. Which of the following could be the value of r?A. 0.998B. 0.213C. -0.236D. 0.875iven that the regression line has a slope of -0.525 and a y-intercept of -0.379, find the slope-intercept equation of the regression line.Jse the regression line to predict the y-value for the x-value of 1.231. (Round to three decimal places).I om ConfidentI am ValuedI am StrongI om beautifulI Om Smart-OM WORTH TT

Solution The given scattered plot has the upward trend,so the slope and correlation must be…

Answered: the scatterplot given above. Which of…

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. 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
Different patients are randomly selected and measured for pulse rate and body temperature. Using technology with x representing the pulse rates and y representing temperatures, we find that the regression equation has a slope of -0.007 and a y-intercept of 95.6. a. What is the equation of the regression line? b. What does the symbol y represent? a. Choose the correct answer below and fill in the answer boxes to complete your choice. (Type integers or decimals. Do not round.) OA. The equation is Inx=+(y. OB. The equation is Iny=( OC. The equation is y=+x OD. The equation is x=+y b. The symbol y represents value of the actual the mean a predicted ▼ C
The data provided give the number of standby hours based on total staff present, X₁, and remote hours, X₂. Perform a multiple regression analysis using the data provided and determine the VIF for each independent variable in the model. Is there reason to suspect the existence of collinearity? Click the icon to view the data. Determine the VIF for each independent variable in the model. | VIF ₂2 = VIF₁ = (Round to three decimal places as needed.) Is there reason to suspect the existence of collinearity? OA. No. The VIF for each independent variable is less than 5. B. Yes. The VIF for each independent variable is greater than 5. OC. No. The VIF for each independent variable is greater than 5. OD. Yes. The VIF for each independent variable is less than 5. wwwwwww Table of Data Standby Total Staff Hours Present 245 330 274 358 195 197 117 153 115 275 200 236 336 339 321 303 286 329 352 323 Remote Hours 417 655 524 385 349 350 388 153 278 479 Print Done
Using the weights (lb) 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. The site to your captio V.UVITU. D. The slope is -0.00749 and the y-intercept is 58.9. c. What is the predictor variable? ... OA. The predictor variable is highway fuel consumption, which is represented by x. OB. The predictor variable is highway fuel consumption, which is represented by y. C. The predictor variable is weight, which is represented by x. OD. The predictor variable is weight, which is represented by y. d. Assuming that there is a significant linear correlation between weight and highway fuel consumption, what is the best predicted value for a car that weighs 2994 lb? The best predicted value of highway fuel consumption of a car that weighs 2994 lb is (Round to one decimal place as needed.) mi/gal.
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.
Find the regression equation, letting the first variable be the predictor (x) variable. Find the best predicted Nobel Laureate rate for a country that has 78.4 Internet users per 100 people. How does it compare to the country's actual Nobel Laureate rate of 1.7 per 10 million people? X Click the icon to view the data. Find the equation of the regression line. ŷ=+x (Round the constant to one decimal place as needed. Round the coefficient to thre Data table Internet Users Per 100 80.1 79.2 78.4 45 82.9 38.4 89.5 88.8 79.1 83.3 52.7 76.5 57.1 79.4 93.1 94.8 64.5 57.7 67.3 94.1 84.6 86.6 78.5 Nobel Laureates 5.5 24.4 8.7 0.1 6.1 0.1 25.4 7.6 9 12.8 1.9 12.6 3.3 1.5 11.3 25.5 3.1 1.9 1.7 32 31.3 18.8 10.8
Different patients are randomly selected and measured for pulse rate and body temperature. Using technology with x representing the pulse rates and y representing temperatures, we find that the regression equation has a slope of-0.019 and a y-intercept of 99.6. a. What is the equation of the regression line? b. What does the symbol y represent? a. Choose the correct answer below and fill in the answer boxes to complete your choice. (Type integers or decimals. Do not round.) O A. The equation is x = O B. The equation is In y = x. O C. The equation is In x = O D. The equation is y = X. b. The symbol y represents value of Click to select and enter your answer(s). 3:45 PM P Type here to search 4/16/2021 12 ho num Ik 17 prt scr insert esc %23 24 & backspace 2 3 4 6. 7 81 6. tab W E R 2. enter A D F H. K 3. 00 %#M
Use B = -15.812961, and ₁ = 0.096300 to determine the equation of the estimated regression line. (Round your numerical answers to four decimal places.) ŷ =
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=-0.993 a=29.135 r2=0.463761 r=-0.681 Use this to predict the number of situps a person who watches 6 hours of TV can do. Round to one decimal place.
A regression analysis was performed to determine if there is a relationship between hours of TV watched per day (x) and number of sit ups a person can do (y ). The results of the regression were: y=ax+b a=-1.33 b=25.138 r2=0.712336 r=-0.844 Use this to predict the number of sit ups a person who watches 10 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
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=-1.127 a=25.258 r2=0.695556 r=-0.834 Use this to predict the number of situps a person who watches 8 hours of TV can do. Round to one decimal place.

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