;AUTO. Complete the following table and calculate the correlation coefficient, regression equation, and coefficient of determination, RSunlighthours, xSection IV- Regression & CorrelationyхуYield (flowers), y0.3110.6180.9291.2331.543ΣΣa.Correlation coefficient, r-b.Write down the regression equation:c. Use the regression equation to predict the flower yield if the amount of sunlight is 1.1 hours..CancelDone中。

Answered: Image /qna-images/answer/c330af4d-3276-45b3-918b-067e622eb82d.jpg

Answered: Complete the following table and…

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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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 a3D-0.838 b=28.783 es 72-0.784996 r=-0.886 rences borations Use this to predict the number of sit ups a person who watches 1 hours of TV can do, and please round your answer to a whole number. gle Drive ce 365 Submit Question adent Course aluations ere to search Chp ins prt sc delete f12 f9 f10 fa f5 f6 +1 f4 backspa & $4 8. 6 3 O E R T II 5
Data were gathered and displayed on the scatter plot. 15 y 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Which of the following is the best equation to model the data? ŷ = 11.5(0.81)* Oŷ = 8.1(0.115)* Oŷ= -0.115x+8.1 Oŷ=-0.81x+11.5
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=-1.271 b=39.101 ²-0.407044 r=-0.638 Assume the correlation is significant, and use this to predict the number of situps a person who watches 14 hours of TV can do (to one decimal place) Aft
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=-1.108 b-34.092 r2-0.736164 r=-0.858 Assume the correlation is significant, and use this to predict the number of situps a person who watches 4 区 hours q TV can do (to one decimal place) 72222392 口 D
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=-1.307 b=32.392 r²=0.675684 r=-0.822 Use this to predict the number of situps a person who watches 12.5 hours of TV can do (to one decimal place)
Interpret the intercept and the coefficients of D1 and D2 in the regression above.
The regression equation is: ŷ = 67.16 + 8.417x where ŷ is the miles traveled, and x is the MPG. The sample size used was all 110 MPG records. The correlation coefficient r = 0.620. Use the information to obtain an estimate of my mileage if my MPG is 22. Is it option: a.) cannot estimate ŷ rcrit = 0.195; the correlation IS NOT significant b.) ŷ = 252.33 rcrit = 0.195; the correlation IS significant c.) ŷ = 252.33 rcrit = 0.187; the correlation IS significant d.) cannot estimate ŷ rcrit = 0.187; the correlation IS NOT significant
Data from 147 colleges from 1995 to 2005 (Lee,2008) were tested to predict the endowments (in billions) to a college from the average SAT score of students attending the college. The resulting regression equation was Y = -20.46 + 4.06 (X). This regression indicates that: a. for every one-point increase in SAT scores, a college can expect 4.06 billion more in endowments. b. most colleges have very high endowments. c. for every one-point increase in SAT scores, a college can expect 20.46 billion fewer in endowments. d. for every one-dollar increase in endowments, the college can expect a half-point increase in SAT scores.
Find Karl person's coefficient of correlation using regression coefficient byr=-0.56, bry=-0.83 Answer:
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=-0.666 b=36.053 r2=0.552049 r=-0.743 Use this to predict the number of situps a person who watches 4.5 hours of TV can do (to one decimal place)
Which of the following is the most appropriate equation to model the data? ŷ = 1.1x + 1.467 ŷ = 1.467x + 1.1 ŷ = 1.1(1.467)x ŷ = 1.467(1.1)x
A regression was run to determine if there is a relationship between hours of TV watched per day (xx) and number of situps a person can do (yy).The results of the regression were:y=ax+b a=-0.629 b=39.045 r2=0.806404 r=-0.898 Use this to predict the number of situps a person who watches 6.5 hour(s) of TV can do, and please round your answer to a whole number.

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