In the semi-conductor manufacturing plant example, compute for the predicted value(ŷ) of observation# 1 using the regression model: ŷ = 2.26 +2.74x₁ +0.0125x2TABLE 1-2 Wire Bond Pull Strength DataObservation Number12345Pull Strength y9.9524.4531.7535.0025.02Wire Length x₁2811108Die Height X₂50110120550295

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Answered: In the semi-conductor manufacturing…

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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The estimated regression equation for a model involvingtwo independent variables and 55 observations is: y-hat = 55.17 + 1.1X1 - 0.153X2 Other statistics produced for analysis include: SSR = 12370.8 SST = 35963.0 Sb1 = 0.33 Sb2 = 0.20 a) Interpret b1 and b2 in this estimated regression equation b. Predict y when X1 = 55 and X2 = 70. b) Compute R-square and Adjusted R-Square. e. Compute MSR and MSE. f. Compute F and use it to test whether the overall model is significant using a p-value (α = 0.05). g. Perform a t test using the critical value approach for thesignificance of β1. Use a level of significance of 0.05. h. Perform a t test using the critical value approach for thesignificance of β2. Use a level of significance of 0.05.
Wh ich of the following regressions represents the weakest linear relationship between x and y? Regression 1y=ax+by=ax+ba=11.9a=11.9b=0.1b=0.1r=0.7944r=0.7944 Regression 2y=ax+by=ax+ba=12.9a=12.9b=19.8b=19.8r=0.0346r=0.0346 Regression 3y=ax+by=ax+ba=9.8a=9.8b=15.6b=15.6r=0.2439r=0.2439 Regression 4y=ax+by=ax+ba=-9.4a=−9.4b=11b=11r=-0.5893r=−0.5893 Regression }1Regression 1 t{Regression }2Regression 2 {Regression }3Regression 3 {Regression }4Regression 4
Consider a linear spline with 16 knots. How many regression coefficients do you estimate when running a linear regression model with that spline?
We collected teacher ratings for 25 courses taught by an instructor over a six-vear period. The students' ratings of the instructor are on a scale of 1 to 9. We found that The linear regression equation is: Average Rating = 7,88 -0.068 Numher of Students 1. Interpret the slope of this model including units: The average rating decreases per each additional student 0.068 ed teacher rating for a class size of 15 students using the given 7.88 prediction equation is Next page CS Scanned with CamScanner
Solids (grams) obtained from a material as y, with respect to drying time (Hours) as x. Ten experiments were carried out to obtain the following observations: Table on the picture (a) Create a scatter diagram for the data. (b) Estimated regression model according to the data conditions. (c) Calculate Model Accuracy (R²) and Relationship Between Variables (r²)
Compare the linear regression data for two students walking in front of a motion sensor: Bob’s walk d = 0.75t + 2 r = 0.70 Tracey’s walk d = 0.75t + 2 r = 0.95 a) How are the movements of these walkers similar? different? b) Sketch possible distance versus time graphs for Bob and Tracey.
Refer to the following computer output from estimating the parameters of the nonlinear model Y = aRbScTd The computer output from the regression analysis is: DEPENDENT VARIABLE: LNY R-SQUARE F-RATIO P-VALUE ON F OBSERVATIONS: 32 0.7766 32.44 0.0001 VARIABLE PARAMETER ESTIMATE STANDARD ERROR T-RATIO P-VALUE INTERCEPT -0.6931 0.32 -2.17 0.0390 LNR 4.66 1.36 3.43 0.0019 LNS -0.44 0.24 -1.83 0.0774 LNT 8.28 4.60 1.80 0.0826 Based on the information in the table, which of the parameter estimates are statistically significant at the 90% level of confidence?
Ms. Patsy Knowlet, a water quality engineer, noted that there seemed to be a close connection between an important streamflow water quality parameter, Y, and the flow, X m/s. She found that 9 pairs of observations yielded the following data: E*= 152 E* = 576 Ey= Ey* = 5183 y = 1726 45.6 Find the 95% confidence limits of the slope of the regression.
Thirty data points on Y and X are employed to estimate the parameters in the linear relation Y = a + bx. The computer output from the regression analysis is DEPENDENT VARIABLE: R-SQUARE F-RATIO P-VALUE ON F OBSERVATIONS: 30 0.5300 13.79 0.0009 VARIABLE PARAMETER STANDARD T-RATIO P-VALUE ESTIMATE ERROR INTERCEPT 93.54 46.210 2.02 0.0526 |-3.25 0.875 |-3.71 0.0009 At the 1% level of significance, the critical t-value for the test is (Write the numbers as they are, do not round them)
The table contains data on vehicle speed (h) and fuel consumption (lt / 100km) of 5 randomly selected vehicles. Estimate the average fuel consumption of a vehicle traveling at 45 km / h using the simple linear regression equation between vehicle speed and fuel consumption. Speed 55 60 65 70 75 Consumption 13 12 11 10 9 a. 15 b. 8 c. 7 d. 20
The following data on x maternal age in years of the young birth mothers and y = weight of baby born in grams summarizes the result of a study. Assume that a simple linear regression model y = Bo + B1x + e is an appropriate model for the study. x-bar = 17 (avg of x's) y-bar = 3004.1 (avg of y's) SSx = 20 SSxy %3D 4903 SSw 1539182.9 n 10 Calculate the value of s-(standard error of regression) and enter the answer to the nearest tenth (1 decimal place).
The estimated regression equation for a model involving two independent variables and 10 observations follows. ý = 22.1370 + 0.5303Xq + 0.4920X2 (a) Interpret b₁ in this estimated regression equation. O b₁ = 0.5303 is an estimate of the change in y corresponding to a 1 unit change in x₂ when x₁ is held constant. O b₁ = 0.5303 is an estimate of the change in y corresponding to a 1 unit change in x₁ when X₂ is held constant. O b₁ = 22.1370 is an estimate of the change in y corresponding to a 1 unit change in x₁ when x₂ is held constant. O b₁ = 0.4920 is an estimate of the change in y corresponding to a 1 unit change in x₂ when x₁ is held constant. O b₂ = 0.4920 is an estimate of the change in y corresponding to a 1 unit change in x₁ when x₂ is held constant. Interpret b₂ in this estimated regression equation. O b₂ = 0.4920 is an estimate of the change in y corresponding to a 1 unit change in x₂ when x₁ is held constant. O b₂ = 22.1370 is an estimate of the change in y corresponding to a…

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