Chapter 7,8,9 Statistics

Type I error

incorrectly convicting the defendant when he is innocent

The smaller the margin of error the larger the sampling required. The higher the level of confidence the larger the sample size required.

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a 100% confidence interval is not possible unless either the entire population is sampled or an absurdly wide interval of estimates is provided

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increasing there sample size by a factor of 4, decreases the standard error by a factor of 2. Changing the standard error doubles the magnitude of the standardized z-value

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level of significance

size of rejection region

sampling distribtution of proportion

follows the binomial distribution when sampling with replacement

when sample standard deviation

always assume normal distribution

hypothesis

claim about a population parameter

sampling distribution

distribution of all of the possible values of a sample statistic for a given sample size selected from a population

sampling distribution of the mean

distribution of all possible sample means if you select all possible samples of a given size

central limit theorem

even if population is not normal, sample mean from population will be applicable normal as long as the sample size is large enough. Large enough=30

if standard deviation is known

have a normal distribution is given or sample size is large.

Type II error

incorrectly failing to convict the defendant when he is guilty

unbiased

meaning the mean of all possible sample means is equal to the pop. mean

degrees of freedom

n-1

confidence interval estimate

range of numbers called an interval constructed around the point estimate

point estimate

value of a single sample statistic, such as a sample mean

standard error of mean

value of the standard deviation of all possible sample means, which expresses how the sample means varies from sample to sample

sampling error

variation that occurs due to selecting a single sample from the population