Q5:A- Show that the boundary-value problem has a unique solution:= -0.1.ý=ýcosx + 2xy, 0≤x≤, y(0) = -0.3, y (7)B- Find the least squares line approximating the data in the following table:X2 46y 7 9.4 12.3

Answered: Image /qna-images/answer/087f3356-033c-4321-ad83-1e6f88f15186.jpg

Answered: Q5:A- Show that the boundary-value…

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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4. Determine the equation of the least-squares approximating line that is the best fit for the data points (2, 6), (0, 2), and (1, 1).
When the predicted overnight temperature is between 15°F and 32°F, roads in northern cities are salted to keep water from freezing on the roadways. Suppose that a small city was trying to determine the average amount of salt y (in tons) needed per night at temperature x. They found the following least squares prediction equation: y = 20,000 - 2,500x Interpet the slope. a) 2,500 tons is the decrease in the amount of salt needed for a 1 degree increase in temperature. b) 2,500 tons is the increase in the amount of salt needed for a 1 degree increase in temperature. c) 20,000 is the increase in the amount of salt needed for a 1 degree increase in temperature. d) 2,500 tons is the expected amount of salt needed when the temperatures is 0° C.
Consider the data points (2, 0), (3, 1), and (4, 5). Compute the least squares error for the given line. y = -4 + 2x Plot the points and the line. (Be sure to plot all points, even if they lie on the line.) No Solution 7 6 5 4 3 2 1 -4 -3 -2 -1 1 2 3 4 5 6 7 8 9 10 -1 -2 -3 -4 -5 -6 -7 Help Graph Layers Clear All Delete After you add an object to the graph you can use Graph Layers to view and edit its properties. Fill WebAssign. Graphing Tool
Find the best-fitting least-squares linear and quadratic approximations to the data set{(1,2),(3,4),(5,7),(7,9),(9,12)}.
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…
The model, y = Bo + B₁×₁ + ß₂×2 + ε, was fitted to a sample of 33 families in order to explain household milk consumption in quarts per week, y, from the weekly income in hundreds of dollars, x₁, and the family size, x₂. The total sum of squares and regression sum of squares were found to be, SST = 162.1 and SSE(R) = 90.6. The least squares estimates of the regression parameters are bo = -0.022, b₁ = 0.051, and b₂ = 1.19. A third independent variable-number of preschool children in the household-was added to the regression model. The sum of squared errors when this augmented model was estimated by least squares was found to be 83.1. Test the null hypothesis that, all other things being equal, the number of preschool children in the household does not affect milk consumption. Use α=0.01. Click here to view page 1 of a table of critical values of F. Click here to view page 2 of a table of critical values of F. ''1' M P2 P3 Find the critical value. The critical value is 7.60⁰. (Round to…
The model, y = Bo + B₁×1 + ß₂×₂ + ε, was fitted to a sample of 33 families in order to explain household milk consumption in quarts per week, y, from the weekly income in hundreds of dollars, X₁, and the family size, x2. The total sum of squares and regression sum of squares were found to be, SST = 162.1 and SSE(R) = 90.6. The least squares estimates of the regression parameters are bo = -0.022, b₁ = 0.051, and b₂ = 1.19. A third independent variable number of preschool children in the household-was added to the regression model. The sum of squared errors when this augmented model was estimated by least squares was found to be 83.1. Test the null hypothesis that, all other things being equal, the number of preschool children in the household does not affect milk consumption. Use α = 0.01. Click here to view page 1 of a table of critical values of F. Click here to view page 2 of a table of critical values of F. Choose the correct null and alternative hypotheses below. A. Ho: B3 = 0 |…
During oil drilling operations, components of the drilling assembly may suffer from sulfide stress cracking. An article reported on a study in which the composition of a standard grade of steel was analyzed. The following data on y = threshold stress (% SMYS) and x = yield strength (MPa) was read from a graph in the article (which also included the equation of the least squares line). X 634 643 712 709 y S = 100 92 87 83 835 78 (b) Compute the estimated standard deviation s 820 810 75 74 870 63 856 923 878 937 57 55 ΣΥ, = 10,575, ΣΥ, = 892, Σχιζ = 8,739,877, = 8,739,877, Σy? L x = 65,852, ExY, = 701,865 (a) What proportion of observed variation in stress can be attributed to the approximate linear relationship between the two variables? (Round your answer to four decimal places.) (Round your answer to four decimal places.) SB₁ 47 Does it appear that this true average change has been precisely estimated? O This is a fairly wide interval, so has been precisely estimated. 0 O This is a…
Find the least-squares line y=Bo+B₂x that best fits the given data. Given: The data points (-2,2). (-1,5), (0.5), (1,4), (2,2). Suppose the errors in measuring the y-values of the last two data points are greater than for the other points. Weight these data points twice as much as the rest of the data. 1-2 1 -1 x= 1 1 1 2 PP 2 Next question y 5 CIT OA. y 7.1-0.73x OB. y 3.6-0.37x OC. y 3.3-0.53x OD. y 3.4-0.47x

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Q5:A- Show that the boundary-value problem has a unique solution: ý=ýcosx + 2xy, 0≤x≤, y(0) = -0.3, y()= -0.1. B- Find the least squares line approximating the data in the following table: x 2 4 6 y 7 9.4 12.3