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Unit 12 vocab

QuestionAnswer
bias concerns the center of the sampling distribution for a statistic which is not close to where the the true value of a population parameter is
central limit theorem for all large n the sampling distribution of x is approximately normal for any population with finite standard deviation
mean (of the sampling distribution) is equal to the population proportion p
normal approximation (of the sampling distribution) is closer to a normal distribution when the sample size n is large
parameter a number that describes the population. (the value of a parameter is not known)
population proportion a parameter p
sample mean used to estimate the unknown parameter μ
sample proportion a statistic that is used to gain information about the parameter p
sampling distribution (of a statistic) is the distribution of values taken by statistic in all possible samples of the same size from the same population
sampling variability the value of a statistic varies in repeated random sampling
statistic a number that can be computed from the sample data without making use of an unknown parameter (it is often used to estimate an unknown parameter)
unbiased the mean of its sampling distribution is equal to the true value of the parameter being estimated
Created by: user-2016449
 

 



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