The document provides a detailed exploration of hypothesis formulation and testing in research methodology, including definitions, types, and functions of hypotheses. It outlines the key steps involved in hypothesis testing, such as formulating hypotheses, setting criteria for decision-making, and analyzing data. Additionally, it explains the implications of p-values in determining the validity of hypotheses, along with the concepts of type I and type II errors.

1. ADVANCE RESEARCH METHODOLOGY

2. 
 The word hypothesis is derived form the Greek
words“hypotithenai” means to put under or
suppose Plural is Hypothesis
 A researcher calls these assumptions, assertions, or
statements they become the basis of an inquiry.
 In most cases, the hypothesis will be based upon
either previous studies or the researcher’s own or
someone else’s observations
Defining the word

3. 
 A tentative statement about something, the validity of
which is usually unknown (Black, James A & Dean J
Champion, Method and Issues in Social Research, New
York: John Wiley & Sons, Inc, 1976
 Hypothesis is proposition that is stated in a testable form
and that predicts a particular relationship between two or
more variable (Baily, Kenneth D, Methods of Social
Research, 3rd edition, New York: The Free Press, 1978)
 A hypothesis is written in such a way that it can be
proven or disproven by valid and reliable data (Grinnell,
Richard, Jr. Social Work Research and Evaluation, 3rd
edition, Itasca, Illinois, F.E. Peacock Publishers, 988)
Definition of Hypothesis

4. 
A problem is formulated in the form of a
question;
A hypothesis is a suggested solution to a
problem.
A problem (question) cannot be directly tested,
whereas a hypothesis can be tested and verified.
The Difference between
Hypothesis & Problem

5. 
 Unknown validity
 Specifies relation between two or more variables
 Simple, specific, and contextually clear
 Capable of verification
 Related to the existing body of knowledge
 Operation able
Characteristics of hypothesis

6. 
 Provides a study with focus
 Signifies what specific aspects of a research problem is to
investigate
 What data to be collected and what not to be collected
 Enhancement of objectivity of the study
 Formulate the theory
 Enable to conclude with what is true or what is false
Functions of hypothesis

7. 
 Step 1: State the hypotheses.
(Formulation of hypothesis)
 Step 2: Set the criteria for a decision.
(Set the level of significance)
 Step 3: Compute the test statistic.
(Data analysis )
 Step 4: Make a decision
(on basis of P . Value)
4 Steps to Hypothesis Testing

8. 
 Working hypothesis
Null hypothesis
 Research hypothesis
Type of hypothesis

9. 
 The working or trail hypothesis is provisionally
adopted to explain the relationship between some
observed facts for guiding line
 Examples:
 Population influence the numbers of bank branch
 Education effect the social norm
 Science university influence the invention of the
country
Working hypothesis

10. 
 A null hypothesis is formulated against the working
hypothesis; opposes the statement of the working
hypothesis
 Examples:
 Population have no influence on the numbers of bank
branches
 Education does not affect social norm
 Science university have no influence / impact on
invention of the country.
Null hypothesis

11. 
 An alternate hypothesis is formulated when a
researcher totally rejects null hypothesis
 Examples
 population has significant effect on the number of
bank branches
 education has significant effect social norm
 science universities have significant influence / impact
on invention of the country
Alternate hypothesis

12. 
 Interval estimation
 t-state
chi-square
Hypothesis Testing
Types of Tests

13. 
 If the Ho value lies in the range of interval we have
to accept Ho Ho = 0.3
 If the Ho value lies outside form range of interval we
have to reject Ho H1 # 0.3
Hypothesis Testing
Interval Method
Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Intercept 24.45454545 6.413817299 3.812791091 0.005142172 9.664256253 39.24483466
X Variable 1 0.509090909 0.035742806 14.24317115 5.75275E-07 0.42666785 0.591513968

14. 
 If the calculated value is more than table value
rejects Ho
 If the calculated value is less than table value accept
Ho : Table value 2.62
Hypothesis Testing
t - state Method
Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Intercept 24.45454545 6.413817299 3.812791091 0.005142172 9.664256253 39.24483466
X Variable 1 0.509090909 0.035742806 14.24317115 5.75275E-07 0.42666785 0.591513968

15. 
 Type 1 error
 Rejecting the null hypothesis when it is in fact true is
called a Type I error.
 Type 11 error
 Not rejecting the null hypothesis when in fact it is false
Hypothesis Testing
Types of Errors

16. 
 If the calculated value lies in the range of table
values we have to accept Ho HO = 0
 If the calculated value lies in the range of table
values we have to accept Ho HO # 0
 2.18 and 17.53 not lies in the range so reject Ho
Hypothesis Testing
Chi-Square Method

17. 
 The smaller the p-value, the more statistical evidence
exists to support the alternative hypothesis.
 If the p-value is less than 1%, there is overwhelming
evidence that supports the alternative hypothesis.
 If the p-value is between 1% and 5%, there is a strong
evidence that supports the alternative hypothesis.
 If the p-value is between 5% and 10% there is a weak
evidence that supports the alternative hypothesis.
 If the p-value exceeds 10%, there is no evidence that
supports the alternative hypothesis.
Interpreting the p-value