Download Probability and Statistics Diagnostic Exam: Economics 422 and more Exams Introduction to Econometrics in PDF only on Docsity! Economics 422 Diagnostic Exam September 11, 1991 _gives the probability thatI- A(n) ___ the random variable will assume each of its possible values a. biased estimator b. unbiased estimator c. probability density function d. cumulative distribution function 2. The expected value of a nonlinear func- tion E(h(x)) is generally ______ to h(E(x)). a. unequal b. equal 3. The expected value of a constant c is a. undefined b. greater than or equal to 0 but no larger than 1 c. equal to c d. a/ways less than the standard deviation 4. if y = a. is a random variable for "reasonable" func- tions b. can not be a random variable for "reason- able" functions 5. A(n) estimator is a. a function or formula used to obtain an es- timate of a parameter b. a good predictor of the outcome of an ex- periment c. a random variable d. both a and b e. both a and c 6. A random variable is a. a constant that appears in a formula or a probability model. b. a variable whose variance is determined by the outcome of an experiment in which the outcome is subject to chance. c. a variable whose value is determined by the outcome of an experiment in which the outcome is subject to chance. d. a variable whose mean is determined by the outcome of an experiment in which the outcome is subject to chance. e. both a and d 7. The random variable X\ is _______the random variables Xz,...,Xn if the prob- ability that X\ will take on any value is completely unaffected by it he particular values assumed by X?,..., Xn a. consistent with b. dependent on c. independent of d. unbiased by 8. A random sample consists of random vari- ables -which are _____ and have __ a. dependent; have the same probability dis- tribution b. independent; have the same probability dis- tribution c. independent; have a finite variance. d. dependent; have the same variance. 9. A constant that appears in a formula or a probability model. a. A covariance b. A mean c. An estimator d. A parameter In the following assume that f\x,y) represents the joint probability density function of x and y, that fi(x), and /a(y) represent the (marginal)probability density functions for x and y respectively.
