Hypothesis testing is a method used to test claims about parameters in a population using sample data. It involves 5 steps: 1) stating the null and alternative hypotheses, 2) setting the significance level, 3) selecting the test statistic, 4) formulating the decision rule, and 5) making a decision to reject or not reject the null hypothesis. An example tests if a pizza delivery service meets its 12 minute goal using a sample average, standard deviation, and z-test at a 0.05 significance level. The null hypothesis of an average less than or equal to 12 minutes is rejected.

1. Group no – 5
Ashish Sharma

2. DEFINITION
Hypothesis testing is a method for testing a claim or
hypothesis about a parameter in a population,
using data measured in a sample.

3. Five stEPS:
Step 1 : State the hypotheses.
Step 2 : level of significance.
 Step 3 : select the test statistic.
 Step 4 : formulate the decision rule.
 Step 5 : make a decision.

4.  We begin by stating the value of a population
mean in a null hypothesis.
 The null hypothesis, stated as the null, is a
statement about a population parameter, such as
the population mean, that is assumed to be true.
Step 1 : State the hypotheses.

5.  To set the criteria for a decision, we state the level
of significance for a test.
 Level of significance, or significance level, refers to
a criterion of judgment upon which a decision is
made regarding the value stated in a null
hypothesis.
Step 2 : level of significance

6.  The test statistic is a mathematical formula that
allows researchers to determine the likelihood of
obtaining sample outcomes if the null hypothesis
were true.
Step 3 : select the test
statistic

7. Step 4 : formulate the decision rule
 A decision rule is a statement of the specific condition.
 critical value : the dividing point between the region
where the null hypothesis is rejected or not.

8. Step 5: Make a decision
The final step in hypothesis testing is
computing the test statistics, comparing it to the
critical value and making a decision to reject or
not to reject.

9. Example: Pizza House
A Pizza restaurant provides one of the fastest home
delivery services in the world with 20 mobile units. The
manager of home delivery services wants to formulate a
hypothesis test that could use a sample of response times
to determine whether or not the service goal of 12 minutes
or less is being achieved.
A sample of 40 home deliveries yields an average time of
13.25 minutes and standard deviation =3.2 minutes. Test
the hypothesis at 0.05 level of significance.

10. Example: Pizza House
Ho :   Ha: 
n = 40, x̅ = 13.25 minutes, s = 3.2 minutes
(The sample standard deviation s is used to estimate
.)
Since 2.47 > 1.645, we reject H0.
47.2
40/2.3
1225.13
n/
x
z 






11. Conclusion: We are 95% confident that Pizza
House is not meeting the response goal of 12
minutes; appropriate action should be taken to
improve service.