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AP Statistics: Confidence Intervals Flashcards

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8726981200Point Estimatea sample statistic that an unbiased estimate for a single number approximating the population parameter0
8726981201Unbiased EstimateA statistic that is no more likely to overestimate than to underestimate the population parameter1
8726981202Margin of Error (general definition)The maximum expected difference between a population parameter and a point estimate of a statistic obtained from a random sample2
8726981203Confidence Interval (CI)A range of estimated values for a population parameter; the point estimate plus/minus the margin of error3
8726981204Margin of Error for Population MeanThe critical value (t*) times the standard error of the sampling distribution of the sample mean4
8726981205Margin of Error for Population ProportionThe critical value (z*) times the standard error of the sampling distribution of the sample proportion5
8726981206Critical Value (Z* or T*)The value of the test statistic that cuts off the most extreme values of a distribution; denoted with a *6
8726981207Confidence LevelThe percentage of all possible samples of a given size that will generate a confidence interval that contains the true population parameter7
8726981208Increasing the sample sizeIf all other factors remain constant, the width of a confidence interval can be decreased by...8
8726981209Increase the confidence levelIf all other factors remain constant, the width of a confidence interval must increase to...9
8726981210Standard errorAn estimate of the standard deviation of a sampling distribution often used with confidence intervals since the population parameters are rarely known10
8726981211Standard error of the sample meanUsed when sigma is unknown and must be estimated by the sample standard deviation; requires the use of a t-distribution11
8726981212Standard error of the sample proportionUsed when the population proportion is unknown and must be estimated by the sample proportion; a z distribution is still used12
8726981215t-distributionA family of unimodal, symmetric distributions with more variability (therefore higher tail probabilities) than a normal distribution; graphically a z-distribution with fat tails13
8726981216degrees of freedomA statistic that describes the amount of variability in a distribution; larger values indicate smaller tail probabilities14
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