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Math 3339: Statistical Methods for Engineers – University of Houston – Final Exam Practice Questions with Answers (2024)

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This document contains 45 comprehensive final exam practice questions with detailed solutions for Math 3339: Statistical Methods for Engineers at the University of Houston. It covers core topics such as probability distributions, confidence intervals, hypothesis testing, ANOVA, regression, and the Central Limit Theorem. Ideal for reviewing key concepts and formulas before the exam

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Math 3339: Statistical Methods for
Engineers - Final Exam
University of Houston
Duration: 3 Hours
Instructions: Answer all questions. Show all your work for full credit.


1. 1. Define the term 'population' in the context of statistics.

Answer: A population is the complete set of items that data can be
collected from, about which information is desired.


2. 2. The probability that a part produced by a machine is defective is 0.05. If 20 parts are
selected, what is the expected number of defective parts?

Answer: Expected value = n * p = 20 * 0.05 = 1.


3. 3. A normal distribution has a mean of 100 and a standard deviation of 15. What is the
probability that a randomly selected value is greater than 130?

Answer: Z = (130 - 100)/15 = 2. P(Z > 2) = 0.0228.


4. 4. What does the Central Limit Theorem state?

Answer: The Central Limit Theorem states that the sampling
distribution of the sample mean approaches a normal distribution
as the sample size increases, regardless of the population's
distribution, provided the sample size is sufficiently large.


5. 5. Construct a 95% confidence interval for a sample mean of 50 with a standard
deviation of 10 and a sample size of 36.

Answer: CI = 50 ± Z*(σ/√n) = 50 ± 1.96*(10/6) = 50 ± 3.27 = (46.73,
53.27)


6. 6. What is the difference between a parameter and a statistic?

Answer: A parameter describes a characteristic of a population; a
statistic describes a characteristic of a sample.


7. 7. Compute the sample variance for the data: 4, 8, 6, 5, 3.

, Answer: Mean = 5.2; Variance = [(4-5.2)^2 + (8-5.2)^2 + (6-5.2)^2 +
(5-5.2)^2 + (3-5.2)^2]/(5-1) = 3.7


8. 8. If two events A and B are independent, what is P(A ∩ B)?

Answer: P(A ∩ B) = P(A) * P(B)


9. 9. A die is rolled twice. What is the probability that the sum is 7?

Answer: There are 6 outcomes that sum to 7: (1,6), (2,5), (3,4), (4,3),
(5,2), (6,1); Total outcomes = 36; Probability = 6/36 = 1/6


10. 10. What is the expected value of a binomial distribution with n = 10 and p = 0.4?

Answer: E(X) = np = 10 * 0.4 = 4


11. 11. Find the standard deviation of a binomial distribution with n = 12 and p = 0.25.

Answer: SD = sqrt(np(1-p)) = sqrt(12*0.25*0.75) ≈ 1.5


12. 12. What is the probability density function of the standard normal distribution?

Answer: f(x) = (1/√(2π)) * e^(-x²/2)


13. 13. What is the standard error of the mean for a population with σ = 20 and sample size
n = 64?

Answer: SE = σ/√n = 20/8 = 2.5


14. 14. Construct a 99% confidence interval for a mean of 70 with σ = 12 and n = 25.

Answer: Z = 2.576; CI = 70 ± 2.576 * (12/5) = 70 ± 6.182 = (63.818,
76.182)


15. 15. State the null and alternative hypotheses for testing whether a mean is different
from 100.

Answer: H0: μ = 100; H1: μ ≠ 100


16. 16. In hypothesis testing, what is a Type I error?

Answer: Rejecting a true null hypothesis.


17. 17. A test yields a p-value of 0.03. What conclusion can you draw at α = 0.05?

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