__SAMPLE POINT-__each individual outcome of an experiment

__SAMPLE SPACE__-

*the collection of all possible sample points in an experiment*

__EVENT-__

*a collection of sample points*

__PRIOR PROBABILITY__-

*initial estimate of the probability of an event*

__RANDOM VARIABLE__-

*a numerical description of the outcome of an experiment*

__EXPECTED VALUE OF A RANDOM VARIABLE__-

*a measure of the average value of a random variable*

__VARIANCE OF A RANDOM VARIABLE__-

*a measure of the dispersion of a random variable*

__PARAMETER__-

*a numerical measure from a population*

__STATISTIC__-

*a numerical measure from a sample*

__SAMPLING DISTRIBUTION__-

*a probability distribution for all possible values of a statistic*

__PROPERTIES OF ESTIMATORS:__

__Unbiased:__

*Property of a statistic where the expected value of a statistic/estimator = the parameter being estimated*

__Consistency:__

*as n increases the probability that the value of a statistic/estimator gets closer to the parameter being estimated increases*

__CENTRAL LIMIT THEOREM__

*-the sampling distribution of the sample mean can be approximated by a normal probability distribution as the sample size becomes large. This holds even if the population from which the sample mean comes from is not normal, or unknown.*

__ASYMPTOTIC DISTRIBUTION__

*- an estimator’s sampling distribution in large samples*

__ASYMPTOTIC PROPERTIES OF AN ESTIMATOR__-

*properties of an estimator in large samples*