MA 237 - Probability and Statistics for Engineering and Sciences

Objectives

1. Define statistics and explain its application in engineering and sciences.
2. Explain the role of the scientists and engineers in quality improvement.
3. Define data and measurements.
4. Group the data according to different types of frequency distributions.
5. Graph frequency distributions.
6. Use descriptive measures to calculate arithmetic mean, median, variance, standard deviation, and coefficient of variation.
7. Calculate quartiles and other percentiles.
8. Define probability, sample spaces, and events.
9. Know permutations and combinations.
10. Know the axioms and theorems of probabilities.
11. Understand mathematical expectation and decision making.
12. Define random variables.
13. Calculate binomial distribution.
14. Calculate hyper geometric distribution.
15. Calculate the mean and the variance of a probability distribution.
16. Know Chebyshev's Theorem
17. Use Poisson approximation to the binomial distribution.
18. Calculate probability density functions.
19. Calculate Kth moment about the origin and mean.
20. Find standard normal distribution.
21. Perform the normal approximation to the binomial distribution.
22. Use Gamma function to calculate mean and the variance of Gamma distributions.
23. Find the joint distribution functions.
24. Calculate conditional density.
25. Transform observations to near normality.
26. Perform simulation techniques using computers.
27. Define populations and samples.
28. Find the value of random variable having the chi-square distribution.
29. Define and use inferences concerning means, variances, and proportions.
30. Define unbiased estimate.
31. Calculate maximum error of estimate.
32. Find confidence interval.
33. Test a hypothesis about a parameter.
34. Select null hypothesis.
35. Know the relation between tests and confidence intervals.
36. Use the method of least squares to fit curves.
37. Calculate confidence limits and limits of prediction.
38. Know curvilinear and multiple regression.
39. Analyze variance.
40. Reform factorial experimentation.
41. Analyze the statistical content of quality-improvement programs.
42. Apply statistics to reliability and testing.
43. Use computer software (if available) to solve statistical problems.

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Syllabus

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Outline

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Text

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Examples of Objectives