Q8/Linearized the model below and use the data to find(a4, B4):0.1 0.20406 0.9 1.3 15 1.7 1.80.751.25 145 1.25 0.85 0.55 0.35 0.28 0.18

In the case where the independent variables and dependent variables are not linearly related to each…

Answered: Linearized the model below and use the…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Consider the regression equation In Y = 4.37 +0.2X₁ +0.3X2- a. Predict the value of Y when X₁ = 8.5 and X₂ = 4.8. b. Interpret the meaning of the regression coefficients 100 b₁, and 100 b₂. a. The predicted value of Y is. (Type an integer or decimal rounded to two decimal places as needed.) b. Choose the correct answer below. OA. Holding constant the other variables, for every one percent increase in X, or X₂, the value of Y increases by b₁ or b2 units, respectively. OB. Holding constant the other variables, for every one unit increase in X, or X₂, the value of Y increases by b, or b2 percent, respectively. OC. For every decrease of one unit of In Y, holding bo constant, the estimated change in X, or X₂ is 100.b, or 100 b₂ units, respectively. OD. Holding constant the other variables, for every one unit increase in X, or X₂, the value of Y increases by 100 b₁ or 100 b2 percent, respectively. O E. Holding constant the other variables, for every one percent increase in X, or X₂, the…
An unknown metal has been found and the following experimental results have been tabulated in the table below. The table contains the grams of the unknown metal and the volume in milliliters of water displacement. Find a linear model that expresses volume as a function of the mass. grams Volume in ml 20 222.3 21.5 246.2 23 258.2 24.5 277.8 26 291.9 27.5 318.1 29 322.3 A) Write the linear regression equation for the data in the chart.Volume = �+ where x is the grams of the unknown metal. Round your answers to 3 decimal places B) If the mass of an unknown metal is 18, using your un-rounded regression equation find its predicted volume. Round your answer to 1 decimal place.
Consider the regression equation In Y₁ = 3.89 +0.5X₁ +0.3X₂i a. Predict the value of Y when X₁ = 7.1 and X₂ = 4.9. b. Interpret the meaning of the regression coefficients 100.b₁, and 100.b₂.
Use the computer output to estimate the intercept B 0 and the slope B 1.The regression equation is Y=24.6+3.05X. Predictor Coef SE Coef T P Constant 24.636 5.321 4.63 0.000 X 3.052 0.4596 6.64 0.000 Intercept B : Slope B 1 :
In a regression analysis involving 30 observations, the following estimated regression equation was obtained. ŷ = 18.6 + 3.7x, - 2.2x2 + 7.9x3 + 2.6x4 (a) Interpret b, in this estimated regression equation. = 3.7 is an estimate of the change in y corresponding to a 1 unit change in x, when x,, x3, and x, are held constant. = -2.2 is an estimate of the change in y corresponding to a 1 unit change in x, when x2, x3, and x are held constant. O b1 = 7.9 is an estimate of the change in y corresponding to a1 unit change in x, when x,, x2, and x, are held constant. O b, O b, = 3.7 is an estimate of the change in y corresponding to a 1 unit change in x, = 2.6 is an estimate of the change in y corresponding to a 1 unit change in x, when x,, x2, and x3 are held constant. when and x4 are held constant. Interpret b, in this estimated regression equation. O b2 = 2.6 is an estimate of the change in y corresponding to a 1 unit change in x, when x,, x2, and x, are held constant. = 7.9 is an estimate…
Consider the regression équation In =3.94+0.4X₁₁ +0.7X₂- a. Predict the value of Y when X₁ =7.4 and X₂ = 5.2. b. Interpret the meaning of the regression coefficients 100 b,, and 100-b₂. a. The predicted value of Y is (Type an integer or decimal rounded to two decimal places as needed.) b. Choose the correct answer below. OA. Holding constant the other variables, for every one unit increase in X, or X₂, the value of Y increases by b, or by percent, respectively. B. Holding constant the other variables, for every one percent increase in X, or X₂, the value of Y increases by b, or b₂ percent, respectively. C. Holding constant the other variables, for every one unit increase in X, or X₂, the value of Y increases by 100 b, or 100-b₂ percent, respectively. OD. Holding constant the other variables, for every one percent increase in X, or X₂, the value of Y increases by b, or b₂ units, respectively. OE. For every decrease of one unit of In Y, holding bo constant, the estimated change in X, or…
Given are 3 observations for two variables, x and y. 1 3 6. 9. 10 What is the estimated regression equation? Select one: a. ÿ = -2 + 6.5x O b. ý 10.89 – 0.87x с. у -0.87+ 10.89x d. ŷ 6.5 – 2x %3D
Round to two decimal places as needed.
Given the data as shown in the table below X 56 44 68 76 94 a) Using Y = -0.0034 +1.0598 as the equation of the "Best-Fit" line. Calculate the residuals, Y - Y, of this data: X₁ = 56, Y₁ - Y₁ . Round your answer to 4 dec places. Y 0.84 0.91 0.83 0.85 0.71 X₂ = 44, Y₂ - Y₂ = to 4 decimal places. X3 = 68, Y3 - 3 = to 4 decimal places. X4 = 76, Y₁ - Y₁ = www to 4 decimal places. X5 = 94, Y5 - 5 = to 4 decimal places. Se = b) Using the formula Se == e²+ e²+...+² N-2 Round your answer Round your answer Round your answer Round your answer calculate the standard deviation, se, of all residuals. Round your answer to 4 decimal CO
Fit a straight line to the data given in Table , first assuming that there is no error in w (weight) values, and then assuming that there is no error in (height) values. Compare the results from both equations.
Run a regression analysis on the following data set, where y is the final grade in a math class and is the average number of hours the student spent working on math each week. hours/week X 4 5 8 9 11 11 14 15 15 20 Grade y 43.6 63 65.2 70.6 65.4 74.4 81.6 82 97 100 State the regression equation y=mx+b, with constants accurate to two decimal places. What is the predicted value for the final grade when a student spends an average of 13 hours each week on math? Grade = Round to 1 decimal place.
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Linearized the model below and use the data to find(u4, B4): 0.1 0.2 04 06 0.9 1.3 1.5 1.7 1.8 yl0.75 1.25 1.45 1.25 0.85 0.55 0.35 0.28 0.18