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Types of Hypothesis

The presentation discusses the types of hypotheses in research, primarily focusing on the null hypothesis (H0) and alternative hypothesis (H1). It outlines the procedure for testing hypotheses, including steps for formulating hypotheses, selecting significance levels, and calculating probabilities. Additionally, it addresses potential errors in hypothesis testing, specifically Type I and Type II errors.

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0% found this document useful (0 votes)
13 views16 pages

Types of Hypothesis

The presentation discusses the types of hypotheses in research, primarily focusing on the null hypothesis (H0) and alternative hypothesis (H1). It outlines the procedure for testing hypotheses, including steps for formulating hypotheses, selecting significance levels, and calculating probabilities. Additionally, it addresses potential errors in hypothesis testing, specifically Type I and Type II errors.

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rahulroy74275
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TYPES OF HYPOTHESIS

POWERPOINT
PRESENTATION BY,
TAPASH CH RAY,
DOCTORAL STUDENT,
UNIVERSITY OF GAUHATI
Theoretically, there should be only one hypothesis, that is the research hypothesis---
The basis of your investigation.
Nonetheless, because of the conventions in scientific enquiry and because of the wording used
in the construction of a hypothesis, hypotheses can be classified into several types.
Broadly, there are two categories of hypothesis:

Research Hypotheses; and


Alternative Hypotheses.
NULL HYPOTHESIS AND ALTERNATIVE HYPOTHESIS
➢ A null hypothesis exists when a researcher believes there is no relationship between the
variables or there is a lack of information to state a scientific hypothesis. This is something
to attempt to disprove or discredit. The null hypothesis is usually written as H0.
➢ This is where the alternative hypothesis enters into the picture/scene. The alternative
hypothesis is usually denoted as H1.
➢ Its main function is to explicitly specify the relationship that will be considered as true in
case the research hypothesis proves to be wrong.
➢The alternative hypothesis is a set of two hypotheses (research and null) that states the
opposite of the null hypothesis. In attempt to disprove a null hypothesis, researcher will
seek to discover an alternative hypothesis.
NULL HYPOTHESIS (H0)

The null hypothesis is a statement that there is no relationship between variables.

It is a negative statement.
ALTERNATIVE HYPOTHESIS (H1)

The statement which suggests that there is a relationship between variables.


EX. HOW PRICE CHANGES EFFECT PRODUCT DEMAND

Null Hypothesis (H0): Price changes have no effect on the demand for the product.

Alternative Hypothesis (H1): Price changes significantly affect the demand for the
product.
PROCEDURE OF TESTING HYPOTHESIS
Step 1. Making a formal statement: The first step consists of making a formal statement of
the null hypothesis and also the alternative hypothesis

Step 2. Selecting a significant level: The hypotheses are tested on pre-determined level of
significance.
a) The magnitude of the difference between sample means.
b) The size of the samples
c) The variability of measurement with samples.
d) Whether the hypothesis is directional or non-directional.

Step 3. Deciding the distribution to use: After deciding the level of significance, the next
step is to determine the appropriate sampling distribution.
Cont…
Step 4. Selecting a random sample and computing an appropriate value: Another step is
to select a random sample(s) and compute an appropriate value from the sample data
concerning the test statistics utilizing the relevant distribution.

Step 5. Calculating of the probability: One has to calculate the probability that the sample
result would diverse as widely as it has from expectations, if the null hypothesis were in fact
true.

Step 6. Comparing the probability: Comparing the probability is calculated with the
specified value for significance level.
TESTING OF HYPOTHESIS

Testing of hypothesis can be classified as:


A) Parametric tests of standard tests of hypothesis; and
B) Non-parametric tests or distributions- free test of hypothesis.
ERRORS IN TESTING A HYPOTHESIS

A hypothesis is an assumption that may prove to be either correct or incorrect. It is possible


to arrive at an incorrect conclusion about a hypothesis for a variety of reasons. Incorrect
conclusions about the validity of a hypothesis may be drawn if:

❖the study design selected is faulty;


❖the sampling procedure adopted is faulty;
❖the method of data collection is inaccurate;
❖the analysis is wrong;
❖The statistical procedures applied are inappropriate; or/and
❖the conclusions drawn are incorrect.
TYPE I AND TYPE II ERRORS WHILE TESTING A
HYPOTHESIS

Type I error means rejection of the hypothesis, which should have been accepted.

Type II error means accepting the hypothesis that should have been rejected.
When a null hypothesis is actually:
When your decision is to:

True False

Accept Correct decision


Type II error
Reject Correct decision
Type I error

Source: Kumar, 2014, Fig. 6.4, pp.105


REFERENCES

1. Kothari, C.R. (1990). Research Methodology: Methods and Techniques (2nd Edition). New
Age International Publication.
2. Kumar, R. (2014). Research Methodology: A Step-by-Step Guide for Beginners (4th
Edition). Sage Publication.
THANK YOU.

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