fits the followingQ1) Determine the parameters a and b so that f(x)data in the least-squares sense.aebx%3D1.22.84.35.46.87.9y7.516.138.967.0146.6266.2Q2) Given the data points (0,7), (2,11), (3,28) use Lagrange's method to determineУ(1).

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Answered: Q1) Determine the parameters a and b so…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

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We use the form ŷ = a + bx for the least-squares line. In some computer printouts, the least-squares equation is not given directly. Instead, the value of the constant a is given, and the coefficient b of the explanatory or predictor variable is displayed. Sometimes a is referred to as the constant, and sometimes as the intercept. Data from a report showed the following relationship between elevation (in thousands of feet) and average number of frost-free days per year in a state. A Minitab printout provides the following information. Predictor Coef SE Coef T P Constant 315.27 28.31 11.24 0.002 Elevation -31.812 3.511 -8.79 0.003 S = 11.8603 R-Sq = 96.8% Notice that "Elevation" is listed under "Predictor." This means that elevation is the explanatory variable x. Its coefficient is the slope b. "Constant" refers to a in the equation ŷ = a + bx. (a) Use the printout to write the least-squares equation. ŷ = + x (b) For each 1000-foot increase in elevation,…
We use the form ŷ = a + bx for the least-squares line. In some computer printouts, the least-squares equation is not given directly. Instead, the value of the constant a is given, and the coefficient b of the explanatory or predictor variable is displayed. Sometimes a is referred to as the constant, and sometimes as the intercept. Data from a report showed the following relationship between elevation (in thousands of feet) and average number of frost-free days per year in a state. A Minitab printout provides the following information. Predictor Coef SE Coef T P Constant 316.62 28.31 11.24 0.002 Elevation -30.516 3.511 -8.79 0.003 S = 11.8603 R-Sq = 96.2% The printout gives the value of the coefficient of determination r2. What is the value of r? Be sure to give the correct sign for r based on the sign of b. (Round your answer to four decimal places.) What percentage of the variation in y can be explained by the corresponding variation in x and the least-squares…
We use the form ŷ = a + bx for the least-squares line. In some computer printouts, the least-squares equation is not given directly. Instead, the value of the constant a is given, and the coefficient b of the explanatory or predictor variable is displayed. Sometimes a is referred to as the constant, and sometimes as the intercept. Data from a report showed the following relationship between elevation (in thousands of feet) and average number of frost-free days per year in a state. A Minitab printout provides the following information. Predictor Coef SE Coef T. Constant 317.97 28.31 11.24 0.002 Elevation -28.572 3.511 -8.79 0.003 S = 11.8603 R-Sq 94.2% %3D Notice that "Elevation" is listed under "Predictor." This means that elevation is the explanatory variable x. Its coefficient is the slope b. "Constant" refers to a in the equation ŷ = a + bx. (a) Use the printout to write the least-squares equation. %3D (b) For each 1000-foot increase in elevation, how many fewer frost-free days are…
Complete Table 3 and find the values of A and B for the straight line that provides the best least-squares fit to the data Table 3 y xy 1 2 3 7 4 9 5 12 Ex = Ey = Σxy Ex² =
Suppose Wesley is a marine biologist who is interested in the relationship between the age and the size of male Dungeness crabs. Wesley collects data on 1,000 crabs and uses the data to develop the following least-squares regression line where X is the age of the crab in months and Y is the predicted value of Y, the size of the male crab in cm. Y = 8.2052 + 0.5693X What is the value of Ý when a male crab is 21.7865 months old? Provide your answer with precision to two decimal places. Interpret the value of Ý. The value of Ý is the probability that a crab will be 21.7865 months old. the predicted number of crabs out of the 1,000 crabs collected that will be 21.7865 months old. the predicted incremental increase in size for every increase in age by 21.7865 months. the predicted size of a crab when it is 21.7865 months old.
Simulate the solution of the given problem using Excel such that when the given five data points (x and y values) are changed, a new equation is formed. 1. By the method of least squares, fit a line y = a + bx to the points 0 2 y -1 -1 2 9 3 10 5 14
Find the least squares approximating squares error for the points (1.1), (4.3). line and the least (2, 2), (3.2), and
I need the right answer to d, e, and f ASAP, please.
Consider the following. x 1 2 3 4 y 4 6 9 13 (a) Find an equation of the least-squares line for the data. (Give each answer correct to 3 decimal places.)y = x +(b) Draw a scatter diagram for the data and graph the least-squares line.
2. The Mach number of a moving object is the ratio of its speedto the speed of sound. The following table shows the speeds of a jet aircraft, in terms of Mach numbers, and the time tafter it starts to accelerate. Find the least- squares line of s as a function of t. t(min) 0.00 s(Mach Number) 0.88 0.60 0.97 1.20 1.03 1.80 1.11 2.40 1.19 3.00 1.25
kindly asnwer it 5.5.1(a)
The following data is given: x -2 -1 0 1 2 y 1.5 3.2 4.5 3.4 2 Determine the coefficients a and b in the function y=a/(x2+b) that best fit the data. (Write the function in a linear form, and use linear least-squares regression to determine the value of the coefficients.) Once the coefficients are determined make a plot that shows the function and the data points.

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Q1) Determine the parameters a and b so that f (x) = aebx fits the following data in the least-squares sense. 1.2 2.8 4.3 5.4 6.8 7.9 y 7.5 16.1 38.9 67.0 146.6 266.2