Presentation on Z-Test

1. A Presentation on
Z–test
- By
Manisha Sharma
D Keerthana
Prerana Gilda
Akeefa Tareen
Rafia Talat

2. Z-test is a statistical technique used to test
the significance of a sample mean. It is
widely used in hypothesis testing, confidence
intervals, and sample size determination.
Understanding this method is essential for
data analysts and researchers.
Introductio
n

3.  Z-test is a statistical procedure used to test an
alternative hypothesis against a null hypothesis.
 Z-test is any statistical hypothesis used to
determine whether two samples’ means are
different when variance are known and is large (n >
30)
 It is comparison of the means of two independent
groups of samples, taken from one population with
known variance
What is Z-test ?

4. When do we use Z-Test ?
When samples are drawn at random.
When the samples are taken from population
are independent.
When standard deviation is known.
When number of observation is large (n > 30)

5. Procedure for testing the Hypothesis
Step-1: Formulation of hypothesis
Hypothesis testing is a fundamental
concept in Z-test. It involves setting up a
null hypothesis and an alternative
hypothesis,

6. 1. Null Hypothesis (H0):
A null hypothesis is a hypothesis which the researcher
tries to disprove, reject or nullify. The ‘null’ often refers
to the common vies of something.
2. Alternative Hypothesis (H1):
The alternative hypothesis is what the researcher really
thinks is the cause of a phenomenon.
Example: In case of determining the effectiveness of a
drug in curing asthma.
H0: The drug is not efficient to cure asthma.
Ha: The drug is efficient to cure asthma.

7. Step-2: Selecting the suitable level of significance
 Level of significance indicates that the chance of rejecting the null hypothesis
by considering it as false, when it is true.
 Generally 5% or 1% level of significance is used in hypothesis testing.
Accept the H0 if the sample
Statistic value lies in this area
95% of the area
5% 5%
Reject H0 if the sample statistic
value lies in these areas

8. Step-3: Selecting a suitable sample distribution:
The most commonly used probability distributions are
 Normal
 T and F
Step-4: Calculating Test Statistic:

9. Step-5: Draw conclusions:
 If the calculated test statistic is greater than the table value at given level
of significance, reject null hypothesis.
 If the calculated test statistic is less than or equal to table then accept the
null hypothesis

10. Thank You