These slides describe detail topic on hypothesis testing. I hope students get more benefits about it.

1. Program: Pharm-D 4th
Semester: II (2019-20)
Course: Bio-Statistics
Course code: PHAR-03428
Class Teacher: DR. LIAQUAT AHMAD
email: liaquatahmad@uvas.edu.pk
Lecture # 35-37

2. Hypothesis Testing
Hypotheses
A common aim in many studies is to check
whether the data agree with certain predictions.
These predictions are hypotheses about variables
measured in the study.
A hypothesis is a statement about some char-
acteristic of a variable or a collection of
variables.

3. When a hypothesis relates to characteristics of a
population, such as population parameters, one
can use statistical methods with sample data to
test its validity.

4. Significance Test
A significance test is a way of statistically testing a
hypothesis by comparing the data to values predicted
by the hypothesis. Data that fall far from the
predicted values provide evidence against the
hypothesis.
Assumptions:
All significance tests require certain assumptions for
the tests to be valid. These assumptions refer, e.g., to
the type of data, the form of the population
distribution, method of sampling, and sample size.

5. Steps of Hypothesis Testing
• Step-1
Two hypotheses about the value of a population
parameter:
• the null hypothesis H0 and
• the alternative Hypothesis H1
• The null hypothesis H0 is the hypothesis that is directly
tested. This is usually a statement that the parameter has
value corresponding to, in some sense, no effect. The
alternative hypothesis Ha is a hypothesis that contradicts
the null hypothesis. This hypothesis states that the
parameter falls in some alternative set of values to what
null hypothesis specifies.

6. • Step-2
• Level of Significance:
Commonly used level of significance are 10%,
5% and 1%
• Step-3
Test Statistic:
The test statistics is a statistic calculated from the
sample data to test the null hypothesis. This
statistic typically involves a point estimate of the
parameter to which the hypotheses refer.

7. • Step-4
Calculations
• Step-5
Decision Rule: Reject H0 if calculated value of test
statistic is greater than the table value (1.645, 1.96, 2.567)
• Step-6
Conclusion: Since the calculated value of test statistic
falls in the rejection region, so we reject H0 and accept Ha
OR
Since the calculated value of test statistic falls in the
acceptance region, so we accept H0

8. Significance test for a population
mean μ
1. Significance test for μ when Population sd known
• Hypotheses:
The null hypothesis is considered to have form
H0 : μ = μ0
where μ0 is some particular number
The alternative hypothesis refers to alternative parameter
values from the one in the null hypothesis. The most common
form of alternative hypothesis is
Ha : μ ≠ μ0
This alternative hypothesis is called two-sided, since it
includes values falling both below and above the value μ0
listed in H0

9. • Level of Significance : 5%
• Test Statistic:

10. Examples: