12.54.4213.6420.7425.636.2Using the data transformation in the nonlinear regressiondetermine the constants for the exponential regression model y = aeb

Consider the given table.The given table is as follows.

Answered: 1 2.5 4.4 2 13.6 4 20.7 4 25.6 36.2…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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Annual high temperatures in a certain location have been tracked for several years. Let XX represent the year and YY the high temperature. Based on the data shown below, calculate the regression line (each value to two decimal places).y = _________ x + ________ x y 2 14.14 3 18.16 4 20.68 5 22.3 6 22.82 7 26.64 8 29.26
Annual high temperatures in a certain location have been tracked for several years. Let X represent the number of years after 2000 and Y the high temperature. Based on the data shown below, calculate the linear regression equation using technology (each constant to 2 decimal places). X y 3 35.01 4 37.78 5 37.35 6 36.72 7 40.09 8 40.36 9 40.83 10 41.3 11 40.57 12 42.64 13 44.21 14 42.58 15 46.05 16 45.12 The equation is ĝ ŷ = X + Interpret the slope O For each additional 33.75 years, the annual high temperature will increase by 1 degree on average. O For each additional year, the annual high temperature will increase by 33.75 degrees on average. For each additional year, the annual high temperature will increase by 0.74 degrees on average. O For each additional 0.74 years, the annual high temperature will increase by 1 degree on average. Interpret the y-intercept O In 2000, the temperature was about 33.75. O In 2003, the temperature was about 33.75. O In 2003, the temperature was about…
Hi I know that you can’t answer all questions. Can you just answer question 15 please.
Hi I know that you can’t answer all questions. Can you just answer question 16 please.
Annual high temperatures in a certain location have been tracked for several years. Let X represent the number of years after 2000 and Y the high temperature. Based on the data shown below, calculate the linear regression equation using technology (each constant to 2 decimal places). x y 4 36.68 5 35.85 6 35.52 7 35.99 8 38.46 9 38.93 10 38 11 38.07 12 39.54 13 40.11 14 41.58 The equation is y^ = x + Interpret the slope For each additional 33.38 years, the annual high temperature will increase by 1 degree on average. For each additional 0.52 years, the annual high temperature will increase by 1 degree on average. For each additional year, the annual high temperature will increase by 0.52 degrees on average. For each additional year, the annual high temperature will increase by 33.38 degrees on average. Interpret the y-intercept In 2000, the temperature was about 33.38. It does not make sense to interpret the intercept in this scenario. In 2004, the…
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5. 50 29 47 33 1 46 28 42 20 3 58 21 1 42 22 The multiple linear regression equation of the table is shown below: ý = - 6.99 + 0.17x1 + 0.03r2 Use the equation to predict the value of y at ¤1 = 44.5 and x2 = 24.3 (Round to 2 decimal places)
Show a step by step proof with as much detail explaination as possible.
22 4 51 39 4 60 30 41 20 59 31 1 56 32 The multiple linear regression equation of the table is shown below: ý = 1.08 + 0.04.x1+0.01x2 %3D Use the equation to predict the value of y at 43.4 and 2 = 30.1 (Round to 2 decimal places)
Based on data, check the linear regression for multicollinearity, and identify the best regression. Based on the final regression, check for autocorrelation of residuals, and make conclusion.
using Excel
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1 2.5 4.4 2 13.6 4 20.7 4 25.6 36.2 Using the data transformation in the nonlinear regression determine the constants for the exponential regression model y = aeb