Hypothesis Testing for the Mean of a Poisson Distribution (Cambridge (CIE) A Level Maths): Revision Note
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Poisson Hypothesis Testing
How is a hypothesis test carried out for the mean of a Poisson distribution?
The population parameter being tested will be the mean, λ , in a Poisson distribution
As it is the population mean, sometimes μ will be used instead
A hypothesis test is used when the mean is questioned
The null hypothesis, H0 and alternative hypothesis, H1 will be given in terms of λ (or μ)
Make sure you clearly define λ before writing the hypotheses
The null hypothesis will always be H0 : λ = ...
The alternative hypothesis will depend on if it is a one-tailed or two-tailed test
A one-tailed test would test to see if the value of λ has either increased or decreased
The alternative hypothesis, will be H1 will be H1 : λ > ...or H1 : λ < ...
A two-tailed test would test to see if the value of λ has changed
The alternative hypothesis, H1 will be H1 : λ ≠ ...
To carry out a hypothesis test with the Poisson distribution, the random variable will be the mean number of occurrences of the event within the given time/space interval
Remember you may need to change the mean to fit the interval of time or space for your observed value
When defining the distribution, remember that the value of λ is being tested, so this should be written as λ in the original definition, followed by the null hypothesis stating the assumed value of λ
The Poisson distribution will be used to calculate the probability of the random variable taking the observed value or a more extreme value
The hypothesis test can be carried out by
either calculating the probability of the random variable taking the observed or a more extreme value and comparing this with the significance level
or by finding the critical region and seeing whether the observed value of the test statistic lies within it
Finding the critical region can be more useful for considering more than one observed value or for further testing
How is the critical value found in a hypothesis test with the Poisson distribution?
The critical value will be the first value to fall within the critical region
The Poisson distribution is a discrete distribution so the probability of the observed value being within the critical region, given a true null hypothesis may be less than the significance level
This is the actual significance level and is the probability of incorrectly rejecting the null hypothesis (a Type I error)
For a one-tailed test use the formula to find the first value for which the probability of that or a more extreme value is less than the given significance level
Check that the next value would cause this probability to be greater than the significance level
For H1 : λ < ... if
and
then c is the critical value
For H1 : λ > ... if
and
then c is the critical value
Using the formula for this can be time consuming so only use this method if you need to
otherwise compare the probability of the random variable being at least as extreme as the observed value with the significance level
For a two-tailed test you will need to find both critical values, one at each end of the distribution
Take extra care when finding the critical region in the upper tail, you will have to find the probabilities for less than and subtract from one
What steps should I follow when carrying out a hypothesis test with the Poisson distribution?
Step 1. Define the mean, λ
Step 2. Write the null and alternative hypotheses clearly using the form
H0 : λ = ...
H1 : λ = ...
Step 3. Define the distribution, usually where λ is the mean to be tested
Step 4. Calculate the probability of the random variable being at least as extreme as the observed value
Or if told to find the critical region
Step 5. Compare this probability with the significance level
Or compare the observed value with the critical region
Step 6. Decide whether there is enough evidence to reject H0 or whether it has to be accepted
Step 7. Write a conclusion in context
Worked Example
Mr Viajo believes that his travel blog receives an average of 8 likes per day (24 hour period). He tries a new advertising campaign and carries out a hypothesis test at the 5% level of significance to see if there is an increase in the number of likes he gets. Over a 6-hour period chosen at random Mr Viajo’s travel blog receives 5 likes.
(i) State null and alternative hypotheses for Mr Viajo’s test.
(ii) Find the rejection region for the test.
(iii) Find the probability of a Type I error.
(iv) Carry out the hypothesis test, writing your conclusion clearly.
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Examiner Tips and Tricks
Take extra careful when working in the upper tail in Poisson distribution questions, this is where its easy to make mistakes.
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