Key concepts you need to know

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Florida International University *

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3613

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Industrial Engineering

Date

May 22, 2024

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docx

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Uploaded by BarristerGoatMaster1023

All answers should be original in your own words. If two answers or two examples read similar or coming directly from a textbook or online source, they will only get partial points. Detailed and clear answers get more points. 1. What is central limit theorem? Why is it useful engineering data evaluation? Illustrate its use with one example. 2. When is t test used for hypothesis testing with small samples? Why does Z test become inaccurate for small samples? Illustrate through the PDF figure. 3. Show the application of t test for comparing two small samples with a practical and realistic engineering example. 4. Describe the hypothesis testing for comparing two proportions. What distribution does proportions follow? Why is Z test relevant for this type of sample set? How do you estimate the standard error in this case. 5. Describe Type II error and its importance using a real practical engineering example. What are the parameters that affect the probability of making a Type II error in Hypothesis Testing in that example. Are false-positives same as Type II error? 6. Give two examples of data that follows lognormal distribution? Explain why that data could possibly be following that distribution.

7. How are the regression coefficients estimated in linear regression. Show the confidence intervals of the regression coefficient and regression estimate through equations and a graph. 8. How do you know if a data follows normal distribution. Show the steps involved in the process. 9. A commercial cab was involved in a hit-and-run accident. About 90% of the cabs in the city are yellow cabs and 10% of the cabs are orange. A witness identified the color of the accident-causing cab as orange. But in such incidents, the judge knows that the witness is correct only 85% of the times. What is the probability that the car is orange? Why is the probability for orange car low even when the witness is correct 85% of the times. 10. Using your own practical engineering example, define and explain the terms sensitivity, specificity, precision and accuracy.

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