Standard deviation of multiple sample means - SD/ square root of n
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Central limit theorem
large sample size- likely to be normal
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Confidence intervals
estimate of standard error to create acceptable boundaries- work out mean of each sample and construct confidence intervals so that 95% of samples have means in the confidence intervals
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Upper bound
Mean+ (1.96 x SE)
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Lower bound
Mean- (1.96 x SE)
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Further the boundaries are apart
lower the representativeness of the sample
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higher the confidence interval
further from the mean but more samples should contain population mean between boundaries
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Z- score
How many SDs you are from the mean
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Can use to
Find probability of how many scores you might expect to find, use probability distribution and percentage of z-scores to identify statistical significance/ use standardised scores to compare to different data sets
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