One of the standard curves used is harmonic decline model, that is: Q = bx/(1+ ax²) whereQ is the rate of production and x is the time, b and a are the constants of the regression model. Ifwe apply linear least squares fit for estimating b and a, what will be the value of the summationof squared errors.SSrx, Months11 16 18 2290 75 65Q, Barrels/Day1 944 10050Sr= {(y- P(x)}2-(9,- #2) ²

Given: Harmonic decline model, Q=bx1+ax2 Where Q=rate of productionx=time,b, a =constants of the…

Answered: One of the standard curves used is…

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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The equation used to predict annual cauliflower yield (in pounds per acre) is y =24,231 + 4.417x, - 4.677x,, where x, is the number of acres planted and x, is the number of acres harvested. Use the multiple regression equation to predict the y-values for the values of the independent variables. (a) x, = 36,100, X2 = 36,500 (b) x, = 37,800, X2 = 38,100 (c) X4 = 38,800, X2 = 39,000 (d) x, = 42,100, X2 = 42,200 %3D %3D (a) The predicted yield is pounds per acre. (Round to one decimal place as needed.)
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A recent study showed that the hours a person exercised in a week affected the individual'sresting heart rate. It was computed that r = -.68 and the least squares regression line was?̂ = 83-1.4x, where x is the hours exercised and y is the resting heart rate. d. What percentage of variability in resting heart rate can be explained by variability inhours exercised?
The flow rate in a device used for air quality measurement depends on the pressure drop x (inches of water) across the device's filter. Suppose that for x values between 5 and 20, these two variables are related according to the simple linear regression model with true regression line y = -0.11 + 0.097x. (a.1) What is the true average flow rate for a pressure drop of 10 in.?(a.2) A drop of 15 in.?(b) What is the true average change in flow rate associated with a 1 inch increase in pressure drop?(c) What is the average change in flow rate when pressure drop decreases by 5 in.?
A weight-loss clinic wants to use regression analysis to build a model for weight loss of a client (measured in pounds), Two variables thought to affect weight loss are client's length of time on the weight-loss program and time of session These variables are described below: Y-BO+B1'X+82'D 83'X'D+E Y-Weight loss (in pounds) X- Length of time in weight-loss program (in months) D-1 if morning session. O if not in terms of the Bs in the model, what is the difference between the weight loss of an individual who has spent 3 months in the program when attending the morning session, and an individual who has spent 2 months in the program when attending the evening session? OB1+83 OB1+82-83 OB1+82+283 O81+82+383
Select the appropriate interpretation for the slope of the linear regression equation below. Y (Dependent Variable) = Grade Point Average X (Independent Variable) = Average number of hours spent using electronic devices for entertainment purposes yhat = 4 - 0.125*X A. For every 1 hour more spent using electronic devices for entertainment per week then a person's GPA will increase on average by 0.125 points B. For every 1 GPA gained obtained by a student then on average that person will have watched 0.125 hours fewer of entertainment on electronic devices per week C. For every 1 GPA point lost by a student then on average that person will have watched 0.125 hours more of entertainment on electronic devices per week D. For every 1 hour more spent using electronic devices for entertainment per week then a person's GPA will decrease on average by 0.125 points
Construct the equation of the regression line. An editing firm compiled the following table which lists the number of pages contained in a piece of technical writing and the cost of proofreading and correcting them (in dollars). Assume there is a significant linear relationship between X and Y and construct the equation of the linear regression line. Number of Pages, x 7 12 4 14 25 30 Cost, y 128 213 75 250 446 540 a.) y^= 17.9(x) + 1.6 b.) y^= 7.1(x) + 15.4 c.) y^= 15.4(x) + 7.1 d.) y^= 1.6(x) +
Show the best fitted line on scatter diagram and Find the predicted value for each y using the exposure time and the equation obtained in part b (b. Find the equation of regression line between radiation doses on exposure time .usingleast square method)
** Based on the regression results, answer the following questions ** A sample of data is collected (from 1999 and 2000) concerning the compensation of the executives (compensation is measured in 1000’s of $’s) of a number of public companies along with other firm-specific data. The dependent variable is total compensation, CEOANN is a dummy variable =1 for an individual who is a CEO and =0 for individuals who are not CEO’s, EMPL is total employees, MKTVAL is the natural logarithm of the market value of the firm, EPSIN is earnings per share, YEAR is a dummy variable = 1 for the year 2000 and =0 for year 1999, and ASSETS is the natural logarithm of the total assets of the company. Based on the regression results, answer the following questions b) What is the estimated regression equation? c) What percentage of the variation in income in explained by the regressors? d) What is the standard error of the error term in the regression equation?
A study tests the effect of earning a Master's degree on the salaries of professionals. Suppose that the salaries of the professionals (S,) are not dependent on any other variables. Let D, be a variable which takes the value 0 if an individual has not earned a Master's degree, and a value 1 if they have earned a Master's degree. What would be the regression model that the researcher wants to test? A. S,= Po + B,D,+u, i=1, .. , n. O B. S,= Po + B, + u, i= 1, .. , n. OC. 1=6o +B1,S, + u, i= 1, .. , n. O D. 0=Bo +B, S, + u,, i= 1, .. , n. Suppose that a random sample of 160 individuals suggests that professionals without a Master's degree earn an average salary of $59,000 per annum, while those with a Master's degree earn an average salary of $80,000 per annum. The OLS estimate of the coefficient B, will be $ and that of B, will be $ Click to select your answer(s). DELL
A particular article used a multiple regression model to relate y = yield of hops to x₁ = mean temperature (°C) between date of coming into hop and date of picking and x₂ = mean percentage of sunshine during the same period. The model equation proposed is the following. y = 415.116.6x₁4.50x2+e (a) Suppose that this equation does indeed describe the true relationship. What mean yield corresponds to a temperature of 20 and a sunshine percentage of 39? (b) What is the mean yield when the mean temperature and percentage of sunshine are 19.1 and 42, respectively? You may need to use the appropriate table in Appendix A to answer this question.

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