Write an exponential regression equation for the following data, rounding all coefficients to the nearest thousandth. Screenshot 2022-08-01 12.43.38 PM.pngOX3610Write an exponential regression equation for the following data, rounding allcoefficients to the nearest thousandth.1417210 Q Q234 0y475402321243193153140Titis•C:(8) ▼ 12:43

Solution: The curve to be fitted is y=aebx taking logarithm on both sides, we get…

Answered: Write an exponential regression…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

See similar textbooks

Similar questions

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=-1.375 b=26.852 r2=0.395641 r=-0.629 Use this to predict the number of situps a person who watches 14 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=ax+b a=-0.818 b=21.295 r2=0.49 r=-0.7 Use this to predict the number of situps a person who watches 7.5 hours of TV can do (to one decimal place)
Using the regression formula with a slope = .704 and an intercept = .719, what would the predicted college GPA be for a student whose current high school GPA = 3.2?
Draw the regression line for the following equation: Y = -3 + (1) X Show your calculation for a low and high value on the predictor value.
Please only answer “d” and “e” as I already have the other parts filled out. Thank you!
Use exponential regression to extrapolate the value of y when x = 6. Round your answer to the nearest whole number. X y ¹2 77 -1 65 0 56 1 47 2 40 3 34 (Record your answer in the numerical response box from left to right.)
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=-1.223 b=30.332 r²-0.389376 r=-0.624 Use this to predict the number of situps a person who watches 9.5 hours of TV can do (to one decimal place)
Use the data below for the PHONES questions that follow. Data compiled from the CIA World Factbook, https://www.cia.gov/. The number of cell phones in use in a country can be approximated from the number of main lines in use in that country by using the regression equation yhat=25+3x which had an R² of about 90%. (The numbers here are millions. For example, "1.2" would represent 1.2 million or 1,200,000.) PHONES 1 At the time the data was collected, the USA had about 314 million cell phones in use and about 150 million main lines in use. What was the residual for the USA? Enter a number of millions. For example, if your answer is 2.85 million enter "2.85". Do not enter anything else such as symbols or words.
Find the linear regression line for the following table of values. You will need to use a calculator, spreadsheet, or statistical software. Then, use the equation to estimate the value of y when x is 9. • Round the values of a and b in the regression equation to the nearest hundredth, then use the equation to solve for y when x = 9. Round the final answer to the nearest hundredth, if necessary. X 0 1 2 3 4 5 6 7 y 3.67 5.24 7.04 10.31 9.83 11.04 14.68 15.02 Ih
Holy...I’m stuck on these. I really don’t know how to do them. I added a picture of the questions
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%3ax+b a=-1.219 b=29.882 r2=0.727609 r=-0.853 Use this to predict the number of situps a person who watches 11 hours of TV can do (to one decimal place)
The regression line, y = 23.4 -0.07x, passes the horizontal axis at 334.3 -0.07 O -23.4 0.07 23.4 O-334.3

SEE MORE QUESTIONS

Recommended textbooks for you

Advanced Engineering Mathematics

Advanced Math

ISBN:

9780470458365

Author:

Erwin Kreyszig

Publisher:

Wiley, John & Sons, Incorporated

Numerical Methods for Engineers

Advanced Math

ISBN:

9780073397924

Author:

Steven C. Chapra Dr., Raymond P. Canale

Publisher:

McGraw-Hill Education

Introductory Mathematics for Engineering Applicat…

Advanced Math

ISBN:

9781118141809

Author:

Nathan Klingbeil

Publisher:

WILEY

Advanced Engineering Mathematics

Advanced Math

ISBN:

9780470458365

Author:

Erwin Kreyszig

Publisher:

Wiley, John & Sons, Incorporated

Numerical Methods for Engineers

Advanced Math

ISBN:

9780073397924

Author:

Steven C. Chapra Dr., Raymond P. Canale

Publisher:

McGraw-Hill Education

Introductory Mathematics for Engineering Applicat…

Advanced Math

ISBN:

9781118141809

Author:

Nathan Klingbeil

Publisher:

WILEY

Mathematics For Machine Technology

Advanced Math

ISBN:

9781337798310

Author:

Peterson, John.

Publisher:

Cengage Learning,

Basic Technical Mathematics

Advanced Math

ISBN:

9780134437705

Author:

Washington

Publisher:

PEARSON

Topology

Advanced Math

ISBN:

9780134689517

Author:

Munkres, James R.

Publisher:

Pearson,

SEE MORE TEXTBOOKS

Write an exponential regression equation for the following data, rounding all coefficients to the nearest thousandth. x 3 6 10 14 17 21 23 Y 475 402 321 243 193 153 140