The document discusses research hypotheses. It defines a hypothesis as an educated guess, tentative view, or untested proposition that provides a preliminary explanation. A hypothesis presents an expected relationship between variables and provides a tentative explanation for a phenomenon being investigated. Examples of testable hypotheses are provided. The key differences between hypotheses and theories are explained, with theories arising from repeated testing of hypotheses. Characteristics of good testable hypotheses and different ways of categorizing hypotheses, such as by formulation, direction, and derivation, are outlined. The steps for testing hypotheses, including defining the null and alternative hypotheses and determining whether to reject or fail to reject the null hypothesis, are described. Common errors in hypothesis testing, such as Type I and Type II errors,

1. Research Hypotheses
Dr. Amitabh Mishra

2. Hypothesis Defined
• An educated guess
• A tentative point of view
• A proposition not yet tested
• A preliminary explanation
• A preliminary Postulate
Dr. Amitabh Mishra

3. “Hypothesis is a formal statement that presents the
expected relationship between an independent and
dependent variable.”
(Creswell, 1994)
“A hypothesis is a logical supposition, a reasonable
guess, an educated conjecture. It provides a tentative
explanation for a phenomenon under investigation."
(Leedy and Ormrod, 2001)
Dr. Amitabh Mishra

4. HYPOTHESIS: Example
–The mileage of Maruti Wagon R is as good as
Hyundai Santro.
–The customer loyalty of Parle is better than
Britannia.
•These hypotheses are capable of
objectively verified and tested

5. Hypothesis vs. Theory
• A theory is a well-established principle that has
been developed to explain some aspect of the
natural world.
• A theory arises from repeated observation and
testing and incorporates facts, laws, predictions,
and tested hypotheses that are widely accepted.
Dr. Amitabh Mishra

6. Hypothesis vs. Theory
•A hypothesis is a specific, testable prediction about
what you expect to happen in your study.
–For example: a study designed to look at the relationship between
study habits and test anxiety might have a hypothesis that states,
“This study is designed to assess the hypothesis that students with
better study habits will suffer less test anxiety.” Unless your study is
exploratory in nature, your hypothesis should always explain what
you expect to happen during the course of your experiment or
research.
Dr. Amitabh Mishra

7. Hypothesis Theory Fact
• A specific, testable
prediction about what is
expected to happen in a
study
•makes a specific
prediction about a
specified set of
circumstances
•a speculative guess that
has yet to be tested
•is new and relatively
untested
•the probability of error
and correction are high
• Well-established
principle which predicts
events in general terms
• Arises from repeated
observation and testing
•Incorporates facts,
laws, predictions, and
tested hypotheses that
are widely accepted
•extensively tested and
is generally accepted
•is something which is
assumed to be true
•once a theory has
been confirmed and
reconfirmed over and
over again, we get to
the point that it will be
treated as a "fact"
•doesn't mean 'absolute
certainty
Dr. Amitabh Mishra

8. Why it is needed?
• To bring direction, specificity & focus to a research
study.
• To have something to test.
• The hypothesis can be proved to be:
– right,
– partly right,
– wrong (false).
Dr. Amitabh Mishra

9. Functions of a hypothesis
• Providing focus
• What data to collect and what data not to collect
• Enhancing objectivity
• Making conclusions easier
Dr. Amitabh Mishra

10. 1. A Hypothesis must be conceptually clear
– Concepts should be clearly defined
– The definitions should be commonly accepted
– The definitions should be easily communicable
2. The hypothesis should have empirical reference
– Variables in the hypothesis should be empirical realities
– If they are not, it would not be possible to make the observation
and ultimately the test
Characteristics of a Testable Hypothesis
Dr. Amitabh Mishra

11. 3. The Hypothesis must be specific
– Place, situation and operation
4. A hypothesis should be related to available
techniques of research
– Either the techniques are already available, or
– The researcher should be in a position to develop suitable
techniques
Characteristics of a Testable Hypothesis
Dr. Amitabh Mishra

12. 5. The hypothesis should be related to a
body of theory
– Hypothesis has to be supported by theoretical argumentation
– It should depend on the existing body of knowledge
– In this way the study could benefit from the existing knowledge and later
on through testing the hypothesis could contribute to the reservoir of
knowledge
Characteristics of a Testable Hypothesis
Dr. Amitabh Mishra

13. Types of Hypotheses
13Dr. Amitabh Mishra

14. Categorizing Hypotheses
Can be categorized in different ways
1. Based on their formulation
– Null Hypotheses and Alternate Hypotheses
2. Based on direction
– Directional and Non-directional Hypothesis
3. Based on their derivation
– Inductive and Deductive Hypotheses
14Dr. Amitabh Mishra

15. Categorizing Hypotheses
1. Null Hypotheses and Alternate Hypotheses
• Null hypothesis always predicts that
– No differences between the groups being studied (e.g.,
experimental vs. control group) or
– No relationship between the variables being studied
• By contrast, the alternate hypothesis always predicts
that there will be a difference between the groups
being studied (or a relationship between the variables
being studied)
15Dr. Amitabh Mishra

16. Categorizing Hypotheses
• Alternate Hypothesis can further be
classified as
2. Directional Hypothesis and Non-
directional Hypothesis
Simply based on the wording of the hypotheses
we can tell the difference between directional
and non-directional
16Dr. Amitabh Mishra

17. Categorizing Hypotheses
2. Directional Hypothesis and Non-directional Hypothesis
• If the hypothesis simply predicts that there will be a difference
between the two groups, then it is a non-directional hypothesis. It is
non-directional because it predicts that there will be a difference but
does not specify how the groups will differ.
• If, however, the hypothesis uses so-called comparison terms, such as
“greater,”“less,”“better,” or “worse,” then it is a directional
hypothesis. It is directional because it predicts that there will be a
difference between the two groups and it specifies how the two
groups will differ.
17Dr. Amitabh Mishra

18. Categorizing Hypotheses
3. Inductive and Deductive Hypotheses
(classified in terms of how they were derived):
• Inductive hypothesis - a generalization based on
observation
• Deductive hypothesis - derived from theory
Theory Hypothesis Observation Confirmation
Observation Pattern Hypothesis Theory
18Dr. Amitabh Mishra

19. Hypotheses Testing
19Dr. Amitabh Mishra

20. Hypothesis Testing
• All hypothesis tests are conducted the same
way.
• The researcher
1. states a hypothesis to be tested,
2. formulates an analysis plan,
3. analyzes sample data according to the plan,
and
4. accepts or rejects the null hypothesis, based on
results of the analysis.
20Dr. Amitabh Mishra

21. Problem Definition
Clearly state the null and
alternate hypotheses.
Choose the relevant test
and the appropriate
probability distribution
Choose the critical value
Compare test statistic and
critical value
Reject null
Does the test statistic fall
in the critical region?
Determine the
significance level
Compute relevant
test statistic
Determine the
degrees of
freedom
Decide if one-or
two-tailed test
Do not reject null
No
Yes
Steps in HypothesisTesting
21Dr. Amitabh Mishra

22. Errors in
Hypotheses Testing
22Dr. Amitabh Mishra

23. Errors in Hypothesis Testing
DATA ANALYSIS OUTCOME
In Population Accept Null
Hypothesis
Reject Null
Hypothesis
Null Hypothesis
True
Correct Decision Type I Error
Null Hypothesis
False
Type II Error Correct
Decision
23Dr. Amitabh Mishra

24. Type I Error
• Type I error occurs when the sample results lead to the rejection of
the null hypothesis when it is in fact true.
• The probability of type I error (α) is also called the level of
significance.
Type II Error
• Type II error occurs when, based on the sample results, the null
hypothesis is not rejected when it is in fact false.
• The probability of type II error is denoted by β.
• Unlike α, which is specified by the researcher, the magnitude of β
depends on the actual value of the population parameter
(proportion).
Dr. Amitabh Mishra