TEST 1

# TEST 1 - Acceptance region The set of values of a test...

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Acceptance region: The set of values of a test statistic for which the null hypothesis is accepted (is not rejected). Asymptotic distribution: The approximate sampling distribution of a random variable computed using a large sample. For example, the asymptotic distribution of the sample average is normal. Asymptotic normal distribution: A normal distribution that approximates the sampling distribution of a statistic computed using a large sample. Bernoulli random variable: A random variable that takes on two values, 0 and 1. Bernoulli distribution: The probability distribution of a Bernoulli random variable. Bivariate normal distribution: A generalization of the normal distribution to describe the joint distribution of two random variables. Best linear unbiased estimator: An estimator that has the smallest variance of any estimator that is a linear function of the sample values Y and is unbiased. Under the Gauss-Markov conditions, the OLS estimator is the best linear unbiased estimator of the regression coefficients conditional on the values of the regressors Causal effect: The expected effect of a given intervention or treatment as measured in an ideal randomized controlled experiment Chi-squared distribution: The distribution of the sum of m squared independent standard normal random variables.The parameter m is called the degrees of the freedom of the chi- squared distribution Conditional distribution: The probability distribution of one random variable given that another random variable takes on a particular value Confidence level: The prespecified probability that a confidence interval (or set) contains the true value of the parameter Confidence interval (or confidence set): An interval (or set) that contains the true value of a population parameter with a prespecified probability when computed over repeated samples Coverage probability: the probability, computed over all possible random samples, that it contains the true population mean Conditional expectation: The expected value of one random value given that another random variable takes on a particular value Conditional mean: The mean of a conditional distribution; see conditional expectation. Causal effect: The expected effect of a given intervention or treatment as measured in an ideal randomized controlled experiment. Cross-sectional data: Data collected for different entities in a single time period Control group: The group that does not receive the treatment or intervention in an experiment. Covariance: A measure of the extent to which two random variables move together.The covariance between X and Y is the expected value E[(X 2 mX)(Y 2 mY)], and is denoted by cov(X,Y) or by sXY Convergence in probability: When a sequence of random variables converges to a specific value; for example, when the sample average becomes close to the population mean as the sample size increases. Critical value: The value of a test statistic for which the test just rejects the null hypothesis at the given significance level. Consistency:

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## This note was uploaded on 02/17/2011 for the course ECO 4421 taught by Professor Mason during the Fall '10 term at FSU.

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TEST 1 - Acceptance region The set of values of a test...

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