PYB110 Week Eight Revision Notes
Hypothesis Testing With Samples
We know that any one sample will not tell us the mean of the population from which it was
taken because it can change with every sample taken. We call this a sampling error.
Therefore we must also accept that different random samples will not all have the same
mean. This is called sampling variability.
Since we almost always use samples to represent populations, we want to minimise
sampling error and variability as much as possible.
The simplest way to minimise error is to collect as much data from the population as
This is really common sense – the larger the sample size, the less likely it will be
unrepresentative of the population from which it came.
Characteristics of the Distribution of Means
The mean of the distribution of means is the same as the population mean from which the
sam s taken.
Measuring Variability in Sample Means
The variance of the distribution of means can be calculated:
Where Ms the variance of the distribution of means :
o is the variance of the population
o N is the number of scores in each sample
Standard Error of the Mean
The standard deviation of the distribution of the means can also be calculated.
It is called the standard error of the mean.
Three Types of Distributions
3. Distribution of Means Hypothesis Testing A