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Chapter 7: The Distribution of Sample Means, Standard error of M - 1.…
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Standard error of M - 1. describes the distribution of sample means. It provides a measure of how much difference is expected from one sample to another. When standard error is small, sample means are closer together & have similar values; large error, sample means are scattered over a wide range and there are big differences.
- Standard error measures how well an individual sample mean represents the entire distribution. Standard error also provides a measure of how much distance is between the sample mean and population mean.
Determined by 2 factors - the size of the sample and the standard deviation of the population from which the sample is selected.
As the sample size increases, the error between the sample mean and the population should decrease - LAW OF LARGE NUMBERS
Population Standard Deviation - when n=1 the standard error = standard error of M is the identical to the standard deviation = σ
Standard error measures how well an individual sample means represents the entire distribution. Provides a measure of how much distance b/w a sample mean and population mean.
A z-Score for Sample Means - the sign tells whether the loaction is above (=) or below (-) the mean. The # tells the distance b/w the mean in terms of the number of standard deviations.
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3 Distributions
- Original population scores - has its own shape, mean, & standard deviation. 2. Sample selected from the population - consists of a small set of scores for a few people who have been selected to represent the entire population. 3. Distribution of sample means - theoretical distribution consisting of the sample means obtained from all the possible ransom samples of a specific size.
