Hypothesis Testing for the Population Mean of a Normal Distribution (Edexcel A Level Maths): Revision Note
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Normal Hypothesis Testing
How is a hypothesis test carried out with the normal distribution?
The population parameter being tested will be the population mean, in a normally distributed random variable
The population mean is tested by looking at the mean of a sample taken from the population
The sample mean is denoted
For a random variable
the distribution of the sample mean would be
A hypothesis test is used when the value of the assumed population mean is questioned
The null hypothesis, H0 and alternative hypothesis, H1 will always be given in terms of µ
Make sure you clearly define µ before writing the hypotheses, if it has not been defined in the question
The null hypothesis will always be H0 : µ = ...
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 µ has either increased or decreased
The alternative hypothesis, H1 will be H1 : µ > ... or H1 : µ < ...
A two-tailed test would test to see if the value of µ has changed
The alternative hypothesis, H1 will be H1 : µ ≠ ..
To carry out a hypothesis test with the normal distribution, the test statistic will be the sample mean,
Remember that the variance of the sample mean distribution will be the variance of the population distribution divided by n
the mean of the sample mean distribution will be the same as the mean of the population distribution
The normal distribution will be used to calculate the probability of the observed value of the test statistic taking the observed value or a more extreme value
The hypothesis test can be carried out by
either calculating the probability of the test statistic taking the observed or a more extreme value (p – 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 for the mean of a normal distribution?
The critical value(s) will be the boundary of the critical region
The probability of the observed value being within the critical region, given a true null hypothesis will be the same as the significance level
For an
% significance level:
In a one-tailed test the critical region will consist of
% in the tail that is being tested for
In a two-tailed test the critical region will consist of
in each tail
To find the critical value(s) find the distribution of the sample means, assuming H0 is true, and use the inverse normal function on your calculator
For a two-tailed test you will need to find both critical values, one at each end of the distribution
Can I use the standard normal distribution, Z , to perform a hypothesis test?
You could use the standard normal distribution:
Find the z-value for your sample mean using
Find the critical value(s) for the Z distribution using the percentage points table
If the z-value is further away from 0 than the critical value then reject H0
You could use the standard normal distribution as an alternative method for finding the critical value(s) is to use the standard normal distribution:
Step 1. Find the distribution of the sample means, assuming H0 is true
Step 2. Use the coding
to standardise to Z
Step 3. Use percentage points table to find the z - value for which the probability of Z being equal to or more extreme than the value is equal to the significance level
Step 4. Equate this value to your expression found in step 2
Step 5. Solve to find the corresponding value of
If using this method for a two-tailed test be aware of the following:
The symmetry of the normal distribution means that the z - values will have the same absolute value
You can solve the equation for both the positive and negative z – value to find the two critical values
Check that the two critical values are the same distance from the mean
What steps should I follow when carrying out a hypothesis test for the mean of a normal distribution?
Following these steps will help when carrying out a hypothesis test for the mean of a normal distribution:
Step 1. Define the distribution of the population mean usually
Step 2. Write the null and alternative hypotheses clearly using the form
H0 : μ = ...
H1 : μ ... ...
Step 3. Assuming the null hypothesis to be true, define the test statistic, usually
Step 4. Calculate either the critical value(s) or the p – value (probability of the observed value) for the test
Step 5. Compare the observed value of the test statistic with the critical value(s) or the p - value with the significance level
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
Alternatively, if you have used the standard normal distribution method then in steps 4 and 5 you could compare the z – value corresponding to the observed value with the z – value corresponding to the critical value
Worked Example
The time, minutes, that it takes Amelea to complete a 1000-piece puzzle can be modelled using
. Amelea gets prescribed a new pair of glasses and claims that the time it takes her to complete a 1000-piece puzzle has decreased. Wearing her new glasses, Amelea completes 12 separate 1000-piece puzzle and calculates her mean time on these puzzles to be 201 minutes. Use these 12 puzzles as a sample to test, at the 5% level of significance, whether there is evidence to support Amelea’s claim. You may assume the variance is unchanged.
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Examiner Tips and Tricks
Use a diagram to help, especially if looking for the critical value and comparing this with an observed value of a test statistic
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