Data on pull-off force (pounds) for connectors used in an automobile engine application are as follows:79.8 75.1 78.2 74.1 73.9 75.0 77.6 77.3 73.8 74.6 75.5 74.0 74.775.9 72.7 73.8 74.2 78.1 75.4 76.3 75.3 76.2 74.9 78.0 75.1 76.8If necessary, round all intermediate calculations to four decimal places (e.g. 12.3456).(a) Calculate a point estimate of the mean pull-off force of all connectors in the population (Round the answer to four decimal places(e.g. 90.2353).)(b) Calculate a point estimate of the pull-off force value that separates the weakest 50% of the connectors in the population from thestrongest 50% (Express the answer to two decimal place (e.g. 90.15).)(c) Calculate the point estimate of the population variance (Round the answer to three decimal places (e.g. 3.567).)(d) Calculate the point estimate of the population standard deviation (Round the answer to two decimal places (e.g. 1.23).)(e) Calculate the standard error of the point estimate found in part (a) (Round the answer to two decimal places (e.g. 1.23).)(f) Calculate a point estimate of the proportion of all connectors in the population whose pull-off force is less than 73 pounds (Roundthe answer to three decimal places (e.g. 0.123).)

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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 accompanying data on flexural strength (MPa) for concrete beams of a certain type. 5.5 7.2 7.3 6.3 8.1 6.8 7.0 7.1 6.8 6.5 7.0 6.3 7.9 9.0 8.9 8.7 7.8 9.7 7.4 7.7 9.7 7.9 7.7 11.6 11.3 11.8 10.7 The data below give accompanying strength observations for cylinders. 6.5 5.8 7.8 7.1 7.2 9.2 6.6 8.3 7.0 8.4 7.1 8.1 7.4 8.5 8.9 9.8 9.7 14.1 12.6 11.5 Prior to obtaining data, denote the beam strengths by X,, . Xm and the cylinder strengths by Y,, . Y. Suppose that the X,'s constitute a random sample from a distribution with mean u, and standard deviation o, and that the Y's form a random sample (independent of the X's) from another distribution with mean H2 and standard deviation (a) Use rules of expected value to show that X – Y is an unbiased estimator of µ, - µ. E(X – Y) E(X) – E(Y) = H1 - H2 nm E(X - Y) (E) – E(Y)* = l1 - 42 E(X - Y) = nm( E(X) – E(Yn) = H1 - H2 E(X – Y) E(X - Y) = V E(X) – E(Y) = µ1 – H2 E(X) – E(Y) = µ1 - 42 Calculate the estimate for the given data.…
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