The document provides an overview of hypothesis testing, including: - Definitions of hypothesis as an assumption that can be tested, and characteristics of a good hypothesis. - The process of hypothesis testing including formulating the null and alternative hypotheses, selecting a significance level, calculating a test statistic, and deciding whether to reject the null hypothesis. - Sources of hypotheses such as previous studies, observations, theories. - Types of hypotheses like universal/descriptive versus statistical, and errors that can occur in hypothesis testing like Type I and Type II errors. In summary, the document outlines the key concepts and steps involved in hypothesis testing.

1. 3/27/2016 4:58:58 AM
14MBA23 – RM Notes
Research Methods
Module 6 [A] – MBA – 2nd Semester
V T University Syllabus

2. 2
14MBA23 – Research Methods
Syllabus of Module 6 – Part A:
HYPOTHESIS TESTING:
Hypothesis: Meaning, Types, Characteristics,
Sources, Formulation of Hypothesis, Errors of
Hypothesis.

3. 14MBA23 – RM – M6
WHAT IS A HYPOTHESIS?
Hypothesis is the „Principal Instrument‟ in Research.
Hypothesis is the function to suggest ‘New Experiment or
Observation’.
Hypothesis is the method of making decisions using the data
from a scientific study.
Hypothesis is the formal procedure to ACCEPT or REJECT a
Research.
Hypothesis is „a formal question that intends to be resolved‟.
3

4. 14MBA23 – RM – M6
What is Hypothesis?
Hypothesis is a „Assumption, which may be true or false‟.
Hypothesis is an „Assumption about a population parameter‟.
Hypothesis is a „Question which need to be solved‟.
Examples for Hypothesis:
1. “Students who receive counseling will show a greater increase in creativity
than those students who have not been receiving counseling”.
2. “The Automobile A is performing as well as Automobile B”.
3. “Students perform better, when one subject test is given in a day, than two
subject test per day.
4

5. 14MBA23 – RM – M6
Define ‘HYPOTHESIS’:
“Hypothesis can be defined as a proposition or set of
proposition set forth as an explanation for the
occurrence of some specified group of phenomena
either asserted merely as a provisional conjecture to
guide some investigation or accepted as highly
probable in the light of establishing facts”
PS: (Research Methodology, - Methods and Techniques, 3rd Edn, By C R Kothari and Gaurav Garg – New Age International
Publishers, New Delhi)
5

6. 14MBA23 – RM – M6
Characteristics of a good hypothesis:
1. A Hypothesis must be clear and precise.,
2. A Hypothesis should be capable of being tested.,
3. A Hypothesis should be limited in scope and must be specific.,
4. A Hypothesis must be stated as simple as possible and easy to
understand.,
5. A Hypothesis should be consistent as with the most facts.,
6. A Hypothesis should be amendable to testing within a specific time.,
7. A Hypothesis must explain the facts that gave rise to the need for
explanation.
6

7. 14MBA23 – RM – M6
HYPOTHESIS TESTING: Hypothesis Testing is the
study of the „Power of Tests‟, which refers to the
„Probability of correctly rejecting the Null
Hypothesis, when a given state of nature exists.
Meaning of Hypothesis Testing: Hypothesis Testing
refers to the formal procedures used by statisticians
to ACCEPT or REJECT statistical hypothesis.
A Hypothesis Testing is an „Assumption‟ about the
population parameter. The Assumption may be True
or False.
7

8. 14MBA23 – RM – M6
HYPOTHESIS TESTING: In a nutshell, Hypothesis Testing is
the formal procedure followed by Scholars, Academicians,
Statisticians, Researchers etc, to accept or reject a Hypothesis.
Testing of Hypothesis leads to „Null Hypothesis and Alternative
Hypothesis‟ where the former is denoted as „H0‟ and the latter as „H1‟.
For testing Hypothesis or test of significance, we use both the
„Parametric Tests‟ and „Non-Parametric‟ tests.
Parametric Tests are assume within properties of the population, from
which we draw samples such assumptions may be about the population
parameters, sample size etc…tests where Parametric Tests
In Non Parametric Tests, there is no assumptions, and it is assume only
the „Nominal and Ordinal Data‟.

9. 14MBA23 – RM – M6
HYPOTHESIS TESTING: The procedure for testing a
Hypothesis is as follows: 1. Setting up of Hypothesis., 2. Selecting the
scientific level., 3. Test Statistics., 4. Critical Value., 5. Decision.,
(OR)
The steps in Hypothesis Testing will include: 1. Define the problem, 2.
Clearly state the Null and Alternative Hypothesis, 3. Choose a
relevant and appropriate probability distribution, 4. Choose a critical
value (Significant Level – One tail or Two Test Static), 5. Does the
static level fall on significant range? (If not do not reject the Null
Hypothesis and if Yes, reject the Null Hypothesis)
(THIS NEED TO BE IN A VERTICAL DIAGRAM)
9

10. 14MBA23 – RM – M6
HYPOTHESIS TESTING:
1. Setting-up of Hypothesis: A Hypothesis must be „Null or
Alternative Hypothesis‟.
When in comparison of two variables take it as 2 MBA 2nd Sem
students, if both are equal in academics as well as sports and there is
no differences between them then it shall be said as Null Hypothesis.
It will be denoted by H0.
While if there is some differences between one another of 2 MBA 2nd
Sem students then it will be taken as „Alternative Hypothesis‟. It
will be denoted by H1.
10

11. 14MBA23 – RM – M6
HYPOTHESIS TESTING:
2. Selecting a significant level: Hypothesis need to be
tested on the pre-determined level of significance:
(a) The magnitude of differences of samples „Means‟.,
(b) The Size of the samples.,
(c) The Variability of measurements within the samples.,
(d) The Hypothesis is Directional or Non-Directional., ( A
directional hypothesis will state 2 extremes specifically Ex: Good or Bad, while
Non-Directional will not be specific, like stating Somewhat Good or Somewhat
Bad)
In brief the level of significance must be adequate to, in the
context of the purpose and nature of enquiry.
11

12. 14MBA23 – RM – M6
HYPOTHESIS TESTING:
3. Test Statistics:
In this phase, the researcher uses the hypothetical
parametric value stated under the Null Hypothesis.
12

13. 14MBA23 – RM – M6
HYPOTHESIS TESTING:
4. Critical Value & 5. Decision :
Here using the value of test static and critical value,
the researcher make a Decision about Rejecting or
Not Rejecting the Null Hypothesis.
13

14. 14MBA23 – RM – M6
HYPOTHESIS TESTING: When shall a Null
Hypothesis is accepted or rejected?
A null hypothesis shall be rejected when,
(a) Value of test static < Lower critical value or value of test
static > Upper critical value in case of two tailed test.,
(b) Value of test static > Critical Value, in case of right tailed
test.,
(c) Value of test static < Critical Value , in case of left tailed
test.
(To confirm the test, various statistical tools are used to measure the same)
15

15. 14MBA23 – RM – M6
SOURCES OF HYPOTHESIS:
1. Previous Study, (Secondary Sources).,
2. Personal Experiences, (Higher the experience can lead to higher
degree of formation).,
3. Imagination and Thinking, (Creative Thinking and Imagination of the
researcher).,
4. Observation, (Collection of existing and previous facts related to the
problem and formulation of a good hypothesis)
5. Scientific Theory, (Scientific Theory is a fertile source of hypothesis
formulation).,
6. Culture (Culture helps to understand the tradition, family system,
Values, Norms, Region and Educational System of that area) 15

16. 14MBA23 – RM – M6
HYPOTHESIS: Hypothesis shall be basically in 2
phases – Universal/ General, or Descriptive
Hypothesis and Statistical Hypothesis.
(a)Universal or General or Descriptive Hypothesis
can be UNIVERSAL HYPOTHESIS or
EXISTENCE HYPOTHESIS.,
(b) Statistical Hypothesis can be NULL,
ALTERNATIVE or RESEARCH HYPOTHESIS.,
16

17. 14MBA23 – RM – M6
HYPOTHESIS:
(a)Universal or General or Descriptive Hypothesis
i. Universal Hypothesis: All time valid issues are
Universal Hypothesis, Ex: Students who are
meritorious grab jobs in „Campus Interview‟ itself.
ii. Existence Hypothesis: „Valid for now‟ concept is
the existence hypothesis. Ex: The college chairman
recognized the meritorious students of
17

18. 14MBA23 – RM – M6
HYPOTHESIS:
(a) Statistical Hypothesis:
i. Null Hypothesis: Denoted by H0, where there exists no
relationship to study on achieving objectives.
ii. Alternative Hypothesis: Denoted by H1, where variables
have relationship effects and is helpful for study.
iii. Research Hypothesis: Study by Primary Sources
(Observation, Interview) or Secondary Sources (Building
the existing theory) or Logical means.
18

19. Hypothesis
1. Null Vs Alternative Hypothesis., (H0 & H1)
2. Universal Vs Existence Hypothesis., (Always valid Vs Presently
valid)
3. Directional Vs Non-Directional Hypothesis.,(Good/ Bad Vs
Somewhat Good/ Bad)
4. Statistical Vs Descriptive Hypothesis., Metric – (Null, Alternative and
Research) and Non Metric (Universal and Existence)
5. Associated Vs Causal Hypothesis., (No Cause and Effect Vs Cause
and Effect)
6. Inductive Vs Deductive Hypothesis., (Observation Based and Theory
Based)
19

20. Errors in Hypothesis
Errors in Hypothesis: There are 2 types of errors:
(a) Type I Error:
(b) Type II Error:
20

21. Errors in Hypothesis
Errors in Hypothesis: There are 2 types of errors:
(a) Type I Error:
In Type I Error occurs when the researcher rejects a Null Hypothesis
when it is True.
The Type I error is called as „Significant Level‟.
This error is also called as Alpha, and is denoted by á
21

22. Errors in Hypothesis
Errors in Hypothesis: There are 2 types of errors:
(b) Type II Error:
In Type II error, occurs when the researcher fails to reject the Null
Hypothesis when it is false.
The Type II error is called as „Power of Test‟.
This error is called as Beta, and is denoted by â.
22

23. 23
14MBA23 – Research Methods
End of Module 6 A
Sanjeev Kumar Singh.,
MBA DEPARTMENT - V T UNIVERSITY, Belagavi, Karnataka State
Mob: +91 91640 76660
Email: harsubhmys@yahoo.co.in