SEM and Confidence Intervals

Question 1

Sampling Error

Answer 1

The difference between a population parameter and a sample statistic.
The larger the sample size, the smaller the sampling error.
Reduced through repeated sampling from the same population, or creating a sampling distribution.

Question 2

Sampling Distribution

Answer 2

A distribution of different samples taken from the same population.
The mean of sampling distributions should resemble that of the population mean.

Question 3

Standard Error of the Mean (SEM)

Answer 3

The standard deviation of the sampling distribution.
A measure of the uncertainty of the mean of a specific sample.
The score range over which 68% of sample means are expected to fall.
As N increases, SEM decreases and vice versa.
Used to approximate the range by which the population mean should fall.
Less variable the sampling distribution, the smaller the SEM, and the more reliable the sample mean.
More variable the sampling distribution, the larger the SEM and the less reliable the sample mean.
Provides measure of certainty and an estimate of the magnitude of sampling error in order to make accurate estimates of population parameters.

Question 4

Confidence Intervals

Answer 4

The score range over which most of the means fall (either 95% or 99%).
Only use z scores in these calculations if there is a very large N (greater than 30). If N is less than 30, use a t score for the degrees of freedom of distribution.
Provides measure of certainty and an estimate of the magnitude of sampling error in order to make accurate estimates of population parameters.