5.8 An engineer suspects that the surface finish of a metal part is influenced by the feed rate andthe depth of cut. He selects three feed rates and four depths of cut. He then conducts a factorialexperiment and obtains the following data:Depth of Cut (in)Feed Rate (in/min)0.150.180.200.25747982990.20646888104607392969298991040.258610410811088889599991041081140.3098991101111029599107(a) Analyze the data and draw conclusions. Use a = 0.05.(c) Obtain point estimates of the mean surface finish at each feed rate.(d) Find the P-values for the tests in part (a).

Answered: Image /qna-images/answer/3abaf774-5955-48f4-baff-af9612afccca.jpg

Answered: 5.8 An engineer suspects that 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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Research reported the results of a study on the occurrence of oxygen and chloride in surface streams in central Washington state area. The following data are chloride concentration y (in milligrams per liter) and roadway area in the watershed x (in percentage) y 19.20 23.10 27.40 31.80 39.50 27.70 1.06 x 0.69 1.30 1.05 1.74 1.62 4.40 6.60 y 9.70 10.60 10.80 10.90 X 0.19 0.15 0.57 0.70 0.67 0.63 y 11.80 12.10 14.30 14.70 15.00 17.30 x 0.47 0.70 0.60 0.78 0.81 0.78 ✓ Fit the simple linear regression model using the method of least squares ✓ Find an estimate of 2 ✓ Estimate the mean chloride concentration for a watershed that has 1% roadway area ✓ Find the fitted value corresponding to x = 0.47 ✓ Find the associated residual ✓ Test the hypothesis, with a = 0.01 H₁; B₁ = 0 H₁: B₁0 ✓ Estimate the standard errors in ✓ Find a 99% prediction interval on chloride concentration when roadway area x = 1.0% A. 10.14 B. 13.81 C.ỹ = 0.470 + 20.567x D. (18.2066, 23.8694) E. 1.93591 F. 1.6629 G.y =…
A researcher studying koi fish collected data on three variables, A, B, and C. The following residual plots show the residual for a model for predicting each variable from the age of the fish. VARIABLE A 0.6T 0.4+ 0.2+ 0.0 -0.2 -0.4+ -0.6+ + + 4 2 6 Age (years) VARIABLE B 0.6T 0.4+ 0.2+ 0.0- -0.2+ -0.4+ -0.6- + 1 + 3 4 Age (years) VARIABLE C 0.6T 0.4 Residuals Residuals -LO
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.7 8.5 6.8 3.8 2.4 2.6 2.6 0.8 yy 13.7 11.1 9.9 7.6 5.8 5.9 5.9 4.8 xx = thousands of automatic weaponsyy = murders per 100,000 residentsThis data can be modeled by the equation y=0.84x+3.96.y=0.84x+3.96. Use this equation to answer the following;A) How many murders per 100,000 residents can be expected in a state with 2.9 thousand automatic weapons?Answer = Round to 3 decimal places.B) How many murders per 100,000 residents can be expected in a state with 3 thousand automatic weapons?Answer = Round to 3 decimal places.
The following table contains measurements (in millimeters) of the diameter for a component used in surgeries. Samples of three were taken at approximately one to two hour intervals. Construct the X-bar and Range charts’ control limits (LCL and UCL) for the diameter and answer 4 questions. Observation number Sample 1 2 3 1 7 8 9 2 8 6 8 3 7 8 8 4 8 8 8 1/4) What are the control limits for the X-bar chart? 2/4) What are the control limits for the Range chart? A new sample is obtained with the following measurements (in mm): 6 8 9 3/4) What does the X-bar chart indicate for the new sample? (Cant answer, the process is out of control, or the process is in control?) 4/4) What does the Range chart indicate for the new sample? (Cant answer, the process is out of control, or the process is in control?)
Data was collected for 300 fish from the North Atlantic. The length of the fish (in mm) is summarized in the frequency distribution table below. Lengths (mm) Frequency 180 194 1 195 209 16 210 - 224 71 225 - 239 108 240 - 254 83 255- 269 18 270 -284 3. (a) What is the class width? class width %3D (b) What is the class midpoint for the first class? class midpoint =
The following is a table of household consumption expenditures related to household income. The data obtained are as follows: 15 20 25 30 45 | 58 55 90 39 49 Income (X) consumption (Y) 12 24 28 37 65 79 In IDR 10,000 per month. a) Make a scatter diagram b) Determine the regression equation c) Estimate the amount of expenditure for consumption if the income is IDR 650.000 d) Correlation Coefficient (r) e) Coefficient of Determination (r?)
It is considered that the number of employees in the enterprise affects the number of production. Data are given below. What is the Regression Separation Sum of Squares (RAKT) in the validity of the regression model?
1 a 1 b 1 c
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.8 8.6 7.1 3.9 2.5 2.6 2.4 0.4 yy 14.3 11.5 9.8 7.6 6.2 6.5 6.4 4.1 xx = thousands of automatic weaponsyy = murders per 100,000 residentsThis data can be modeled by the equation y=0.86x+4.07.y=0.86x+4.07. Use this equation to answer the following; Special Note: I suggest you verify this equation by performing linear regression on your calculator.A) How many murders per 100,000 residents can be expected in a state with 3 thousand automatic weapons?Answer = Round to 3 decimal places.B) How many murders per 100,000 residents can be expected in a state with 4.1 thousand automatic weapons?Answer = Round to 3 decimal places.
9
For the past decade, rubber powder has been used in asphalt cement to improve performance. An article includes a regression of y = axial strength (MPa) on x = cube strength (MPa) based on the following sample data: X 112.3 97.0 92.7 86.0 102.0 99.2 95.8 103.5 89.0 86.7 y 74.5 71.1 58.2 48.8 74.2 73.3 68.4 59.5 58.0 48.4 USE SALT (a) Obtain the equation of the least squares line. (Round all numerical values to four decimal places.) y = -30.0452 +.9696 X Check the degree of your polynomial. Interpret the slope. A one MPa increase in cube strength is associated with an increase in the predicted axial strength equal to the slope. O A one MPa decrease in axial strength is associated with an increase in the predicted cube strength equal to the slope. O A one MPa increase in axial strength is associated with an increase in the predicted cube strength equal to the slope. A one MPa decrease in cube strength is associated with an increase in the predicted axial strength equal to the slope. (b)…
For the past decade, rubber powder has been used in asphalt cement to improve performance. An article includes a regression of y = axial strength (MPa) on x = cube strength (MPa) based on the following sample data: x 112.3 97.0 92.7 86.0 102.0 99.2 95.8 103.5 89.0 86.7 y 75.4 71.3 58.1 48.5 74.1 73.7 67.7 59.5 58.0 48.6 (a) Obtain the equation of the least squares line. (Round all numerical values to four decimal places.)y = Interpret the slope. A one MPa increase in axial strength is associated with an increase in the predicted cube strength equal to the slope.A one MPa decrease in cube strength is associated with an increase in the predicted axial strength equal to the slope. A one MPa increase in cube strength is associated with an increase in the predicted axial strength equal to the slope.A one MPa decrease in axial strength is associated with an increase in the predicted cube strength equal to the slope. (b) Calculate the coefficient of determination.…

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