This preview has intentionally blurred sections. Sign up to view the full version.
View Full Document
Unformatted text preview: Econ 103 UCLA, Fall 2010 Problem Set 1 Due: Thursday, October 7 in hardcopy at the beginning of class Note: Please attach the “Homework Cover Page” from Classweb to the front of your home work. Part 1: True or False and explain briefly why. 1. The expected value of a discrete random variable is the outcome that is most likely to occur. 2. If two random variables X and Y are independently distributed, then E ( Y ) = E ( Y  X ) . 3. A probability density function tells the probability that a random variable is less than or equal to a certain value. 4. V ar ( X + Y ) = V ar ( X ) + V ar ( Y ) + 2 Cov ( X,Y ) 5. V ar ( X Y ) = V ar ( X ) V ar ( Y ) 2 Cov ( X,Y ) 6. If ρ XY = 0 , then X and Y are independent. 7. Let Y be a random variable. Then the standard deviation of Y equals E ( Y μ Y ) . 8. Assume that X , Y , and Z follow the distribution N ( μ,σ 2 ) . Then W = X + Y Z is normally distributed. 9. Assume that Y ∼ F 1 , ∞ . Then Y ∼ χ 2 1 . 10. Observations in a random sample are independent of each other. 11. If ˆ μ is an unbiased estimator of μ , then ˆ μ = μ . 12. If the pvalue equals . 96 , then we cannot reject the null hypothesis. 13. The standard error of ¯ Y equals the standard deviation of Y . That is, SE ( ¯ Y ) = σ Y . 14. Assume that H : μ Y = μ Y, and H 1 : μ Y > μ Y, , and Y is normally distributed. To compute the critical value for this 1sided test, we divide by two the positive critical value of the 2sided test. 15. Everything else equal, the length of the confidence interval decreases with the sample size n ....
View
Full Document
 Spring '09
 CASANOVA
 Normal Distribution, Standard Deviation, Variance, Probability theory

Click to edit the document details