11Components that are critical for the operation of electrical systems are replaced immediately upon failure. Suppose that the life time of a certainsuch component can be modeled by a lognormal distribution with mean u = 500 hours and standard deviation a= 100 hours. Currently, 10components are in storage. What is the approximately probability that the system will be in continuous operation for at least the next 5600hours?Hint: Find the correct answer to question 10.Type your answer.

11. Let ∑x be the all components are in storage which follows normal distribution because the life…

Answered: 11 Components that are critical for 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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.A new, miracle diabetes drug that diminishes major symptoms of diabetes has been approved by the FDA. Health care professionals and researchers believe that the new drug will prolong lifespan of diabetes patients. If the population is in steady state and the incidence is constant, what will the effect of this new drug be on the prevalence of diabetes in the population? Explain.
In this example, what is the probability of a person who lives in a single home with a single family with multiple generations getting infected with Covid? Enter the answer to three digits after the decimal place.
A survey was conducted and asked: "Do you consider your health to be poor?" This was coded as 1 for "yes" and 0 for "no." The effect of age (in years) and sex (1 male, 0 = female) on the outcome was examined using logistic regression. The fitted logistic model is: = logit(ô) = −0.544 + ß * sex + 0.0331 * age (a) What are the odds of responding "yes" for a female subject who is 60 years old? (b) What is the estimated odds ratio corresponding to the age variable? Interpret this estimate. (c) Suppose that, based on the data from the survey, the odds of responding "yes" for males are 3.79% greater than the odds for females, adjusting for age. What is the value of Â? (d) If we only wanted to assess the association between survey response (yes/no) and sex, what other method(s) (that we have learned in this class) could we have used (name at least one)? In your own words, explain why we cannot use the same method(s) if we want to consider the effects of both sex and age on survey response.
The Striket Riche Company has begun drilling for oil. It anticipates 130 hour of drilling time before reaching the oil. Experience has shown that the drill bits it uses in this type of rock formation have a lifetime that is lognormal with tmed = 2 hr and s=0.91. The company currently has 35 drill bits available. What is the probability of striking oil before it runs out of bits?
Consider a two component parallel system in which both components have times to failure and times to 0.0024 f/hr and µ1 = = 0.001 f /hr, 12 repair that are exponentially distributed. The data is 1, 0.003 r/hr and µ2 = 0.005 r/hr. Evaluate the reliability or probability of success for a mission of 1000 hr. (hint: form a history for each component using the data for failure rate and repair rate)
One tree in the study had a weight that exceeded its expected weight (according to the best fit curve) by more than that of any other tree. By how many tons did the trees actual weight exceed the expected weight for its height?
Can gender, educational level, and age predict the odds that someone votes for a particular candidate in the election? Over 1500 voters were selected, and data were col-lected on the highest year of school completed, their age, and their gender. We wish to t a logistic regression model: log(1 p p ) = 0 + 1Age + 2Education + 3Gender, where p is the binomial probability that a person voted for candidate Johnson, and gender is coded as the indicator for female. The R output is given below. parameter df estimate s.e z p-value (Intercept) 1 .1119 .3481 .321 .748 Age 1 .0020 .0032 .613 .54 Education 1 -.0100 .0184 .547 .585 Gender 1 .4282 .1040 4.117 .000 Null deviance: 255.95 on 1499 degrees of freedom Residual deviance: 220.80 on 1496 degrees of freedom Write down the tted logistic regression and give a short summary about the data analysis . Calculate the probability of voting for Johnson for a…
Suppose X has a lognormal distribution with parameters mu = 1.5 and sigma = 0.2 . Find the 33rd percentile?
4. As fallen trees lie on the forest floor they slowly decay. Will the amount of light present have an impact on the rate of decay? In the following table x is a random variable representing the remaining percentage of total mass of a log after it was exposed to the elements for three weeks while y represents the numbers of hours of direct sunlight the log received each day. X 0.60 .70 .65 .82 .87 y 1.0 2.3 3.0 4.0 4.5 (a) Plot a scatter diagram of the data. Remember to label your axes appropriately and choose a consistent scale. (b) Based on a scatter diagram, would you estimate the correlation coefficient to be positive, close to zero, or negative? Please circle one of the following choices: A. Positive B. Close to zero C. Negative (c) Interpret your results from parts (a) and (b). 16 tv
Q1. 807 people were randomly selected and data was collected on whether or not they smoked cigarettes in the past 12 months (smoked = 1 if they did, smoked = 0 otherwise), their years of schooling (educ), the natural log of their annual income in dollars (In[income]), age in years (age), and race (white = 1 if white, white = 0 otherwise). The following logit models were estimated and the results are summarized in the table below. The numbers in parentheses are the standard errors. (1) logit (2) logit (3) sample average constant 1.43 0.02 (0.40) (1.06) educ -0.10 -0.11 12 (0.03) (0.03) In[income] 0.16 10.8 (0.11) age -0.02 -0.02 41 (0.0004) | (0.0004) white 0.02 0.7 (0.23) log-likelihood -525 -524 In column (2), the regression equation for smokeď* is: smoked* = x'3 + e = B1 + B2educ + B3 In[income] + B4age + B5white + e In column (3), the sample averages of the regressors are listed. For example, 12 is the sample average of educ, 10.8 is the average of In[income], etc. (a) Using the…
The Striket Riche Company has begun drilling for oil. It anticipates 130 hour of drilling time before reaching the oil. Experience has shown that the drill bits it uses in this type of rock formation have a lifetime that is lognormal with tmed = 2 hr and s=0.91. The company currently has 35 drill bits available. What is the probability of striking oil before it runs out of bits?

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