1 Acup of soup is left on a countertop to cool. Thecable below gives the temperatures, in degreesFahrenheit, of the soup recorded over a 10-minuteperiod.Time in Minutes () Temperature in F()180.2165.8146.3135.4127.7110.52.8.10Write an exponential regression equation for thedata, rounding all values to the nearest thousandth.

We have to find exponential regression equation

1 A cup of soup is left on a countertop to cool. The table below gives the temperatures, in degrees Fahrenheit, of the soup recorded over a 10-minute period. Time in Minutes (3) Temperature in F () 180.2 165.8 146.3 135.4 127.7 110.5 2 4. 10 Write an exponential regression equation for the data, rounding all values to the nearest thousandth.

1 A cup of soup is left on a countertop to cool. The table below gives the temperatures, in degrees Fahrenheit, of the soup recorded over a 10-minute period. Time in Minutes (3) Temperature in F () 180.2 165.8 146.3 135.4 127.7 110.5 2 4. 10 Write an exponential regression equation for the data, rounding all values to the nearest thousandth.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

} According to Airline Company guideline, the average total weight of passenger is no more than 190 pounds. An investigator wants to assist whether the average weight of passengers flying on a small plane exceed the AC guideline (passenger weight including shoes cloth and carry-on). Suppose that a random sample of 51 passengers showed an average total weight of 200 pounds with a sample standard division of 59.5 pounds assume that the passengers' total weights are normally distributed. i. What are the appropriate null and alternative hypothesis? ii. Perform a hypothesis test at 5% significance level, write an appropriate conclusion. iii. For a significance level of 1%, compare the conclusion with part ii
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=-0.773 b=24.3 r2=0.5776 r=-0.76 Use this to predict the number of situps a person who watches 10 hours of TV can do (to one decimal place)
Data was recorded for the temperature, in degrees Celsius, of a cup of coffee over a 30-minute period. Given the regression equation, In(Temp) = 4.20 0.023(Time), what is the predicted temperature after 3 minutes? 33.45 °C 62.24 °C 65.17 °C 66.69 °C
A regression was run to determine if there is a relationship between hours of study per week (x) and the final exam Scores (y). The results of the regression were: y=ax+b a=6.179 b=28.96 r²=0.937024 r=0.968 Use this to predict the final exam score of a student who studies 4 hours per week, and please round your answer to a whole number.
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)
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= -0.889 b=32.071 r2=0.505521 r= -0.711 Use this to predict the number of situps a person who watches 5 hours of TV can do (to one decimal place)
For half-life demonstration, plot ln(half-lives) in the x-axis vs ln(no. of “tails-up” coins) in the y-axis. Perform linear regression to obtain the value of the slope, the value of the y-intercept, and the correlation coefficient r. What is the significance of these values?
A regression was run to determine if there is a relationship between hours of TV watched per day, x, and number of sit-ups, y, a person can do in a minute. The results of the regression were: y=ax+b a=-1.255 b=21.239 Use this to predict the number of sit-ups a person who watches 11.5 hours of TV can do in a minute. Round to the nearest whole number.
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).
The linear regression equation for predicting systolic blood pressure from age is: y = 54 + 1.6*x Find the residual for a person who is 32 years of age with a systolic blood pressure of 103.9 (round your answer 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=-1.324 b=23.586 r2=0.887364 r=-0.942 Use this to predict the number of situps a person who watches 11.5 hours of TV can do (to one decimal place)