1. An engineer who is studying the tensile strength of a steel alloy intended for use ingolf club shafts knows that tensile strength is approximately normally distributed with thesigma=60 psi. A random sample of 12 specimens has a mean tensile strength of 3450 psi.a=0.01.Ho: μ = 3500, H₁: µ ‡ 3500(a) Calculate the type II error if the true mean diameter is 3470 psi.(b) What sample size would be required to detect a true mean diameter as low as 3470 psiif you wanted the power of the test to be at least 0.9?

σ = 60 pai Random sample of 12 specimens Mean = 3450 psi α = 0.01 Ho:µ = 3500 H1:µ ≠ 3500

Answered: 1. An engineer who is studying 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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1.8 A Canadian manufacturer identified a critical diameter on a crank bore that needed to be maintained within a close tolerance for the product to be successful. Sam- ples of size 4 were taken every hour. The values of the differences (measurement - specification), in ten- thousandths of an inch, are given in Table 1.4. (a) Calculate the central line for an X-bar chart for the 24 hourly sample means. The centerline is x = — . . . (4.25 -3.00 -1.50 +3.25)/24. = (b) Is the average of all the numbers in the table, 4 for each hour, the same as the average of the 24 hourly averages? Should it be? (c) A computer calculation gives the control limits LCL = -4.48 UCL 7.88 = Construct the X-bar chart. Identify hours where the process was out of control.
1. Model 1: OLS, using observations 1-706 Dependent variable: RST Coefficient Std. Error t-ratio p-value const 3586.38 38.9124 92.17 <0.0001 *** TOTWRK −0.150746 0.0167403 −9.005 <0.0001 *** Mean dependent var 3266.356 S.D. dependent var 444.4134 Sum squared resid 1.25e+08 S.E. of regression 421.1357 R-squared 0.103287 Adjusted R-squared 0.102014 F(1, 704) 81.08987 P-value(F) 1.99e-1810538.19 Log-likelihood −5267.096 Akaike criterion 10538.19 Schwarz criterion 10547.31 Hannan-Quinn 10541.71 RSTi =3586.38−0.150746 x TOTWRKi , R2=0.103287,SER=421.1357 (38.9124) (0.0167403) Question? could you please help with this question below. 3) By observing the GRETL output in Part (1) above, provide a detailed explanation of the coefficient of determination. Based on your analysis, is this a good model? Why or why not?
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You are studying the velocities of projectiles. Prior experience tells you that standard deviation of velocities is around 9.7 ft/sec. How many independent samples of projectile velocity do you have to measure to estimate the mean velocity within ±±0.98 ft/sec with 92% confidence?
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Which of the following is the correct formula for the margin of error of a population mean where the population standard deviation is not known? A. EBP =z⋅√p'⋅q'n=z⋅p′⋅q′n B. t=¯x−μs√nt=x¯-μsn C. EBM =t⋅s√n=t⋅sn D. EBM =z⋅σ√n
A random sample of 17 adult male wolves from the Canadian Northwest Territories gave an average weight x1 = 98.6 pounds with estimated sample standard deviation s1 = 5.6 pounds. Another sample of 26 adult male wolves from Alaska gave an average weight x2 = 88.2 pounds with estimated sample standard deviation s2 = 6.0 pounds. (a) Categorize the problem below according to parameter being estimated, proportion p, mean μ, difference of means μ1 – μ2, or difference of proportions p1 – p2. Then solve the problem. μp μ1 – μ2p1 – p2 (b) Let μ1 represent the population mean weight of adult male wolves from the Northwest Territories, and let μ2 represent the population mean weight of adult male wolves from Alaska. Find a 99% confidence interval for μ1 – μ2. (Use 1 decimal place.) lower limit upper limit (c) Examine the confidence interval and explain what it means in the context of this problem. Does the interval consist of numbers that are all positive? all negative? of…

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