How to Solve Hypothesis Testing Problems
One common type of problem you will find in Basic Statistics homework is the type of problem that involves using sample data to test a hypothesis .
A hypothesis is a statement about a population parameter. This is, it is a claim that we make about a certain population parameter, such as the population mean, or the population standard deviation.
For example, an engineer from a car manufacturer may claim that the population mean gas mileage of a new car model is 25 mpg. That would be an hypothesis. Or for example, a political polls researcher may claim that the voting share of certain candidate is 53%. That would be another hypothesis, about the true proportion of voters who support that certain candidate.
Consider the following example : A psychologist claims that the mean IQ scores of statistics instructors is greater than 100. She collects sample data from 15 statistics instructors and she finds that and s = 11. The sample data appear to come from a normally distributed population with unknown and .
Let us solve this problem:
Notice that we want to test the following null and alternative hypotheses
Considering that the population standard deviation is not provided, we have to use a t-test with the following formula:
This corresponds to a right-tailed t-test. The t-statistics is given by the following formula:
The critical value for and for degrees of freedom for this right-tailed test is . The rejection region is given by
Since , then we reject the null hypothesis H 0 .
Alternatively, we can use the p-value approach. The right-tailed p-value for this test is calculated as
Considering that the p-value is such that , we reject the null hypothesis H 0 .
Hence, we have enough evidence to support the claim that the mean IQ scores of statistics instructors is greater than 100.