-Find the least square line y=a + bx and y(5) for the data
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- Explain the differences between Gaussian elimination and Gauss-Jordan elimination.Use the method of least squares to fit the model to the data. Y hat= _+_xSelect the equation of the least squares line for the data: (51.00, 1.0), (48.75, 2.5), (52.50, .5), (46.50, 5.0), (45.00, 4.5), (41.25, 6.5), (43.50, 5.0). a) ŷ = -28.956 − 0.54067x b) ŷ = 28.956 − 0.59474x c) ŷ = 0.54067x − 28.956 d) ŷ = 31.852 − 0.59474x e) ŷ = 28.956 − 0.54067x f) None of the above
- In a study of the causes of bearing wear, a machine was run 24 times, with various loads (denoted x1), oil viscosities (x2), and ambient temperatures (x3). The wear, denoted y, was modeled as y = β0 + β1x1 + β2x2 + β3x3 + ε. When this model was fit to the data, the sum of squares for error was SSE = 9.37. Then the reduced model y = β0 + β1x1 + β2x2 + β3x3 was fit, and the sum of squares for error was SSE = 27.49. Is it reasonable to use the reduced model, rather than the model containing all the interactions, to predict wear? Explain.EXER 5.1: Given the observations (1,1), (2,3), (4,5), find the least squares estimates for m and b for the best fit line y=mx+b.The least squares technique minimizes the sum of the squares of the vertical distances between the actual y values and the predicted values of y True or false
- 1. Find the value of SSE that is minimized by the least squares method.Set up the system for the linear least squares approximation for the data (-2,0), (2,3) and (3,1)Various doses of a poisonous substance were givento groups of 25 mice and the following results wereobserved: Dose (mg) Number of deathsx y4 16 38 610 812 1414 1616 20 (a) Find the equation of the least squares line fit tothese data.(b) Estimate the number of deaths in a group of 25 micethat receive a 7-milligram dose of this poison.