Chapter 7: Probability and Samples Flashcards
Sampling error
the natural discrepancy between the sample statistic and its corresponding population parameter
distribution of sample means
The set of means from all the possible random samples of a specific size (n) selected from a specific population.
The sample mean will be closer to the population mean if the sample is ___
is larger
central limit theorem states that
The Expected Value of M is always equal to the population mean μ & the shape of the distribution of sample means tends to be normal.
the expected value of m
The mean of the distribution of the sample of means is equal to the mean of the population of scores (μ)
the shape of the distribution of sample means is guaranteed to be normal if
- the population from which the samples are obtained is normal, or
- the sample size is n = 30 or more.
sampling distribution
A distribution of statistics (ex. distribution of sample means)
standard error
Provides a measure of the average distance between M (sample mean) and μ (population mean)
population variance & sample mean
the smaller the population variance is, the more probable it is that the sample mean will be closer to the population mean
the standard error goes __ as the sample size goes ___
down, up
up, down
Standard Deviation vs. Standard Error
SD: Variability of a distribution of scores
SE: Variability of a distribution of sample means
the standard deviation of sample means formula
σM = σ/√n OR √σ²/n
if you sample again and again, the mean of all those means will be equal to _____
the true mean
if you sample again and again the standard deviation of that distribution will equal ____
the sampling error for that sample
difference between finding z-scores for individual scores vs. samples
you use the standard error instead of the standard deviation
