Would you say the correlation is positive or negative?positiveO negative(c) Use a calculator to verify thatΣ* Ex=61, ExComputer. (Round your answer to four decimal places.)0.9802Need Help?cloudy= 1007,x2 = 1007, Σy = 634, ΣMaster ItAs x increases from 3 to 23 months, does the value of rimply that y should tend to increase or decrease? Explain yO Given our value of r, y should tend to decrease as x increases.Given our value of r, y should tend to increase as x increases.Given our value of r, we can not draw any conclusions for the behavior of y as x increases.O Given our value of r, y should tend to remain constant as x increases.Q Search=14mmm90,298, and Exy = 9,315.hp9|99+X

Given Information: ∑x=61 ∑x2=1007 ∑y=634 ∑y2=90298 ∑xy=9315

Answered: Would you say the correlation is…

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 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
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=ax+b a=-0.794 b=31.311 r²=0.9801 r=-0.99 Use this to predict the number of situps a person who watches 8 hours of TV can do (to one decimal place)
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 = 26.699 -0.639*x R² = 0.5 r = -0.704 Predict the number of situps a person who watches 6 hours of TV can do (round your answer to three decimal places).
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=ax+b a=-1.34 b=36.954 r2=0.966289 r=-0.983 Use this to predict the number of situps a person who watches 5 hours of TV can do (to one decimal place)
A professor believed that there is a correlation between people’s weights and number of times they eat out. He recorded a group of students’ weights (measured in lbs.) and the number of times they ate out last week. The r value was 0.90. We can tell that the correlation between students’ weights (measured in kilogram) and the number of times they ate out last week is: Bigger than 0.9 0.90 Smaller than 0.9 We cannot tell ( don't hand writing solution)
Ocean currents are important in studies of climate change, as well as ecology studies of dispersal of plankton. Drift bottles are used to study ocean currents in the Pacific near Hawaii, the Solomon Islands, New Guinea, and other islands. Let x represent the number of days to recovery of a drift bottle after release and y represent the distance from point of release to point of recovery in km/100. The following data are representative of one study using drift bottles to study ocean currents. x days 75 79 35 91 203 y km/100 14.2 19.1 5.8 11.2 35.4 (a) Verify that Σx = 483, Σy = 85.7, Σx2 = 62,581, Σy2 = 1978.69, Σxy = 10982.3, and r ≈ 0.94895. Σx Σy Σx2 Σy2 Σxy r (b) Use a 1% level of significance to test the claim ρ > 0. (Use 2 decimal places.) t critical t (c) Verify that Se ≈ 4.1118, a ≈ 0.7378, and b ≈ 0.1698. Se a b
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=ax+b a=-1.075 b=27.958 r2=0.919681 r=-0.959 Use this to predict the number of situps a person who watches 12 hours of TV can do (to one decimal place)

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