hypothesis
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Hypothesis
HYPOTHESIS:
The word hypothesis is made up of two Greek roots ὑπόθεσις, its plural is
hypotheses which is a proposed explanation for an observable phenomenon. The
term derives from the Greek, ὑποτιθέναι – hypotithenai meaning "to put under"
or "to suppose." which mean that it is some sort of ‘sub-statements’, for it is the
presumptive statement of a proposition, which the investigation seeks to improve.
The scientists observe the man of special class of phenomena and broads over it
until by a flash of insight he perceives an order and intelligent harmony in it. This
is often referred to as an ‘explanation’ of the facts he has observed. He has a
‘theory’ about particular mass of fact.
This theory when stated testable proposition formally and clearly subjected to
empirical or experimental verification is known as hypothesis. The hypothesis
furnishes the germinal basis of the whole investigation and remains to the end of
its corner stone, for the whole research is directed to test it out by facts. At the
start of investigation the hypothesis is a stimulus to critical thoughts offers
insights into the confusion of phenomena. At the end it comes to prominence as
the proposition to be accepted or rejected in the light of the findings. The word
hypothesis consists of two words:
Hypo + Thesis = Hypothesis
‘Hypo’ means tentative or subject to the verification. “Thesis” means statement
about solution of a problem.
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Hypothesis
The word meaning of the term hypothesis is a tentative statement about the
solution of the problem. Hypothesis offers a solution of the problem that is to be
verified empirically and based on some rationale.
Another meaning of the word hypothesis which is composed of two
words:-‘Hypo’ means composition of two or more variables which is to be
verified. ‘Thesis’ means position of these variables in the specific frame of
reference.
This is the operational meaning of the term hypothesis. Hypothesis is the
composition of some variables i.e. to be verified empirically. It is a proposition
about the factual and conceptual elements. Hypothesis is called a leap into the
dark. It is a brilliant guess about the solution of the problem.
A tentative generalization or theory formulated about the character of phenomena
under observation are called hypothesis. It is a statement temporarily accepted as
true in the light of what is known at the time about the phenomena. It is the basis
for planning and action in the research for new truth.
The second most important consideration in the formulation of the research
problem is the construction of hypothesis. Hypotheses bring clarity specificity and
focus to a research problem but are not essential for a study. You can conduct a
valid investigation without constructing a single formal hypothesis. On the other
hand, within the context research study you can construct as many hypotheses as
you consider to be appropriate. Some believe that one must formulate a hypothesis
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Hypothesis
to undertake an investigation. Hypotheses primarily arise from a set of hunches
that are tested through a study and one can conduct a perfectly valid study without
having these hunches or speculation. However, in epidemiological studies to
narrow the field of investigation, it is important to formulae hypothesis.
The importance of hypothesis lies in their ability to bring direction, specificity and
focus to a research study. They tell a research what specific information to collect,
and thereby provide greater focus.
Let us imagine you are at the race sand you place a bet on the hunch that a
particular horse will win. You will only know if your hunch was right after the
race.
Hypotheses are based upon similar logics. As a researcher you do not know about
the phenomenon, a situation, the prevalence of a condition in a population or
about the outcome of a program, but you do have a hunch to form the basis of
certain assumptions or guesses. You test these by collecting information that will
enable you to conclude if your hunch was right. The verification process can have
one of the three outcomes. Your hunch may prove to be:
1) Right;
2) Partially right; or
3) Wrong
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Hypothesis
Without this process of verification, you cannot include anything about the
validity of your assumption.
Hence a hypothesis is a hunch, assumption, suspicion, assertion or an ides about a
phenomenon, relationship or situation, the realty or truth which you do not know.
A researcher calls these assumptions, assertions, statements or hunches
hypotheses and they become the basis of an inquiry.
Best (1986), states the research or scientific hypothesis is a formal affirmative
statement predicting a single research outcome, a tentative explanation of the
relationship between two or more variable. For the hypothesis to be testable, the
variables must be operationally defined. That is, the researcher specifies what
operations were concluded, or tests used, to measure each variable. Thus
hypothesis focuses the investigation on a definite target and determines what
observations, or measures, are to be used.
A better understanding of the hypothesis could be had by taking note of the
following definition: a hypothesis is a suggested solution to a problem. A
hypothesis consists of elements expressed in an orderly system of relationships
which seek to explain a condition that has not yet been verified by facts. In a
hypothesis, some of the elements or relationship between the element are known
facts. But other elements or relationships are conceptual. That is, they arte product
of the research worker’s imagination. They leap beyond known facts to intelligent
guesses about unknown conditions in an effort to extend or enlarge our
knowledge. The conceptual and factual elements and relationships must be
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Hypothesis
formulated in such a precise and objective manner that the research worker can
test the implications of the hypothesis.
Definitions of hypothesis:
The term hypothesis has been defined in several ways. Some important definitions
are given below
“It is a tentative supposition or provisional guess which seems to explain
the situation under observation.”
-James E. Greighton
“A hypothesis is a tentative generalization the validity of which remains
to be tested. In its most elementary stage the hypothesis may be a hunch,
guess, imaginative idea which becomes the basis for further
investigation.”
Lungerg
“It is a shrewd guess or inference that is formulated and provisionally
adopted to explain observed facts or conditions and to guide in further
investigation.”
John W. Best
“A hypothesis then could be defined as an expectation about events based
on generalization of assumed relationships between the variables.”
Bruce W.Tuckman
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Hypothesis
“A hypothesis is a statement temporarily accepted as true in the light of
what is, at the time, known about a phenomenon, and it is employed as a
basis for action in the search for the truth, when the hypothesis is
completely established, it may take the form of facts, principles, theories.”
Barr and Scates
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Hypothesis
Sources of Hypothesis:
Hypotheses are oriented originally forms the same background that serves to
reveal the problem. The sources are basically theoretical background, knowledge,
insight and imagination that come from industrial programme and wide reading
experiences, familiarity with existing practices. The major sources of hypothesis
are given below:
1) Specialization of an educational field.
2) Programme of reading: published studies, abstracts research journals.
Handbooks, seminars on the issue, current research on the current issue.
3) Instructional programme persuaded.
4) Analysis of the area studied.
5) Considering existing practices and needs.
6) Extension of the investigation. And
7) Offshoots of the research in the field
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Hypothesis
The functions of a hypothesis:
While some researchers believe that to conduct a study requires a hypothesis, having
a hypothesis is not essential as already mentioned. However a hypothesis is important
in terms of bringing clarity to the research problem.
The formulation of hypotheses provides a study with focus. It tells you what specific
aspects of a research problem to investigate.
A hypothesis tells you what data to collect and what not to collect, thereby providing
focus to the study. As it provides a focus, construction of hypotheses enhances
objectivity in a study. A hypothesis may enable you to add to the formulation of
theory. It enables you to specifically conclude what is true or what is false.
The following are the main functions of hypothesis in the research process suggested
by H.H Mc. Ahsan:
1) It is the temporary solution of the problem concerning with some truth which
enables an investigator to start his research works.
Phase 1
Formulate your hunch or assumption
Phase 2
Collect the required data
Phase 3
Analyse data to draw conclusions about the hunch true or false
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Hypothesis
2) It offers a basis in establishing the specifics what to study for and many
provide possible solutions to the problem.
3) Each hypothesis may lead to formulate another hypothesis.
4) A preliminary hypothesis may take the form off final hypothesis.
5) Each hypothesis provides the investigator with definite statement which may
be objectivity tested and accepted or rejected and deals for interrupting results
and drawings conclusion that is related to original purpose.
The functions of hypothesis may be condensed into three. The following are the
threefold functions of a hypothesis:
1) To delimit the field of the investigation.
2) To sensitize the researcher so that he should work selectively, and have very
realistic approach to the problem.
3) To offer the simple means for collecting evidences to the verification.
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Hypothesis
Nature of Hypothesis:
The following are the main features of hypothesis:
1) It is conceptual in nature. Some kind of conceptual elements in the framework
are involved in the hypothesis.
2) It is a verbal statement in declarative form. It is a verbal expression of ideas
and concepts, it is not merely idea but in the verbal form, the idea is ready
enough for verification.
3) It has the empirical referent. A hypothesis contains some empirical referent. It
indicates the tentative relationship between two or more variables.
4) It has a forward or future reference. A hypothesis is future oriented. It relates
to the future verification not the past facts and information.
5) It is the pivot of scientific research. All the research activities are designed for
its verification.
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Hypothesis
Characteristics of Good Hypothesis:
A good hypothesis must have the following main hypothesis:
1) A good hypothesis is in agreement with the observed facts.
2) A good hypothesis does not conflict with any law of nature which is
known to be true.
3) A good hypothesis is started in a simplest possible term.
4) A good hypothesis permits of the application of deductive reasoning.
5) A good hypothesis shows very clear verbalization. It is different from what
we generally called hunch.
6) A good hypothesis ensures that the methods of verification are under the
control of investigator.
7) A good hypothesis guarantees that available tools and techniques will be
effectively used for the purpose of verification.
8) A good hypothesis takes into account the different types controls which
are to be exercised for the purpose of verification.
9) A good hypothesis ensures that the sample is easily approachable.
10) A good hypothesis shows clearly the role of each variable used in the
study.
11) A good hypothesis maintains a very apparent distinction with what is
called theory law, facts, assumptions and postulates.
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Hypothesis
If-then statement:
As already stated a hypothesis is a testable statement of the relationship among
variables. A hypothesis can also test whether there are differences between two
groups. To examine whether or not the conjectured relationships or differences
exist, these hypothesis can be set either as propositions or in the form of IF-THEN
statements.
TYPES OF HYPOTHESIS:
Following are the main types of hypothesis
Null Hypothesis.
Alternate Hypothesis.
Directional Hypothesis.
Non directional Hypothesis.
Null Hypothesis:
The null hypothesis is a proposition that states a definite, exact relationship between
two variables. That is, it states the population correlation between two variables is
equal to zero or that the difference in the means of two groups in the population is
equal to zero. In general, the null statement is expressed as no significant relationship
between two variables or no significant difference between two groups.
The null hypothesis is the hypothesis that states that there is no relation between the
phenomena whose relation is under investigation, or at least not of the form given by
the alternative hypothesis.
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Hypothesis
To explain it further, in setting up null hypothesis, we are stating that there is no
difference between what we might find in a population characteristics and the sample
we are studying. Since we do not know the true state of affairs in the population, all
we can do is draw inferences based on what we find in our samples. What we imply
through the null hypothesis is that any differences found between two sample groups
or any relationship found between two variables based on our sample is simply due to
random sampling fluctuations and not due to any true difference between the two
population groups, or relationship between two variables. The null hypothesis is thus
formulated so that it can be tested for possible rejection. If we reject the null
hypothesis, then all permissible alternative hypotheses relating to the particular
relationship tested could be supported. It is the theory that allows us to have faith in
the alternative hypothesis that is generated in the particular research investigation.
This is one more reason why theoretical framework should be grounded on sound,
defendable logic to start with. Otherwise other researchers are likely to refuse and
postulate other defensible explanations through different alternative hypothesis.
Example:
One may wish to compare the test scores of two random samples of men and women,
and ask whether the mean score of one population-group differs from the other. A
null hypothesis would be that the mean score of the male population was the same as
the mean score of the female population:
H0:μ1 = μ2
Where:
H0 = the null hypothesis
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Hypothesis
μ1 = the mean of population 1, and
μ2 = the mean of population 2.
Alternatively, the null hypothesis may postulate (suggest) that the two samples are
drawn from the same population, thus the variance and shape of the distributions
would be equal, likewise the mean values.
Formulation of the null hypothesis is a vital step in testing statistical significance. One
can then establish the probability of observing the obtained data (or data more
different from the prediction of the null hypothesis) if the null hypothesis is true. That
probability is commonly named the "significance level" of the results.
That is, in scientific experimental design, one may predict that a particular factor will
produce an effect on our dependent variable — this is the alternative hypothesis. We
then consider how often we would expect to observe our experimental results or
results even more extreme, if we were to take many samples from a population in
which there was no effect (i.e. we test against our null hypothesis). If we find that this
happens rarely (up to, say, 5% of the time), we can conclude that our results support
our experimental prediction — we reject our null hypothesis.
Alternate Hypothesis:
The alternative hypothesis, as the name suggests, is the alternative to the null
hypothesis: it states that there is some kind of relation. The alternative hypothesis
may take several forms, depending on the nature of the hypothesized relation; in
particular, it can be two-sided (for example: there is some effect, in a yet unknown
direction) or one-sided (the direction of the hypothesized relation, positive or
negative, is fixed in advance).
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Hypothesis
Alternative hypothesis is the "hypothesis that the restriction or set of restrictions
to be tested does NOT hold." Often denoted H1.
In statistical hypothesis testing, the alternative hypothesis (or maintained
hypothesis or research hypothesis) and the null hypothesis are the two rival
hypotheses which are compared by a statistical hypothesis test. An example might
be where water quality in a stream has been observed over many years and a test
is made of the null hypothesis that there is no change in quality between the first
and second halves of the data against the alternative hypothesis that the quality is
poorer in the second half of the record.
Modern statistical hypothesis testing accommodates this type of test since the
alternative hypothesis can be just the negation of the null hypothesis.
Example:
The alternative hypothesis, H1, is a statement of what a statistical hypothesis test
is set up to establish. For example, in a clinical trial of a new drug, the alternative
hypothesis might be that the new drug has a different effect, on average, compared
to that of the current drug. We would write
H1: the two drugs have different effects, on average.
The alternative hypothesis might also be that the new drug is better, on average,
than the current drug. In this case we would write
H1: the new drug is better than the current drug, on average.
The final conclusion once the test has been carried out is always given in terms of
the null hypothesis. We either "Reject H0 in favour of H1" or "Do not reject H0".
We never conclude "Reject H1", or even "Accept H1".
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Hypothesis
If we conclude "Do not reject H0", this does not necessarily mean that the null
hypothesis is true, it only suggests that there is not sufficient evidence against H0
in favour of H1. Rejecting the null hypothesis then, suggests that the alternative
hypothesis may be true.
Directional Hypothesis:
Those hypothesis who, in stating the relationship between two variables or
comparing two groups, terms such as positive, negative, more than, less than, and
the like are used then these hypothesis are directional because the direction of the
relationship between the variables (positive/negative) is indicated or the nature of
the difference between two groups on a variable (more than/less than) is
postulated.
A directional hypothesis is also called a one tailed hypothesis.
Example:
1. The greater the stress experienced in the job, the lower the job satisfaction
of employees.
2. Women are motivated than men.
Non Directional Hypothesis:
Those hypothesis that do postulate a relationship or difference, but offer no
indication of the direction of these relationships and differences are called non
directional hypothesis.
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Hypothesis
In other words, though it may be conjectured that there would be a significant
relationship between two variables , we may not be able to say whether the would
be positive or negative. Likewise, even if we can conjecture that there will be
differences between two groups on a particular variable, we will not be able to say
which group will be more and which less on that variable.
Non directional hypothesis are formulated either because the relationships or
differences have never been previously explored and hence there is no basis for
indicating the direction or because there have been conflicting findings in
previous research studies on the variables. In some studies a positive relationship
might have been found, while in others a negative relationship might have been
traced. Hence the current researcher might only be able to hypothesize that there
would be a significant relationship, but the direction may not be clear. In such
case, the hypothesis could be stated non directionally.
A non directional hypothesis is also called a two tailed hypothesis.
Examples:
1. There is a relationship between age and job satisfaction.
2. There is a difference between the work ethic values of American and Asian
employees.
Before concluding the discussion on hypothesis, it has to be reiterated that hypothesis
generation and testing can be done both through deduction and induction.
In deduction, the theoretical model is first developed, testable
hypothesis are then formulated, and data collected and then the
hypothesis are tested.
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Hypothesis
In the inductive process, new hypothesis are formulated based on
what is known from the data already collected, which are then tested.
In sum, new hypothesis not originally thought of or which have been previously
untested might be developed after data are collected. Creative insights might compel
researchers to test a new hypothesis from existing data, which, if substantiated, would
add new knowledge and help theory building. Through the enlargement of our
understanding of the dynamics operating in different situations using the deductive
and the inductive processes, we add to the total body of the knowledge in the area.
Steps in Hypothesis Testing:
The steps to be followed in hypothesis testing are:
1. State the null and alternative hypothesis.
2. Choose the appropriate statistical test depending on whether the data collected
are parametric or non parametric.
3. Determine the level of significance required.,
4. See if the output results from computer analysis indicate that the significance
level is met. This critical value demarcates the region of rejection from that of
acceptance of the null hypothesis.
5. When the resultant value is larger than the critical value, the null hypothesis is
rejected and the alternate accepted. If the calculated value is less than the
critical value, the null is accepted and the alternate rejected.
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Hypothesis
HYPOTHESIS TESTING WITH QUALITATIVE RESEARCH:
NEGATIVE CASE ANALYSIS
Hypothesis can also be tested with qualitative data. For example, let us say that a
researcher has developed the theoretical framework after extensive interviews that
unethical practices by employees are a function of their inability to discriminate
between right and wrong, or due to a dire need for more money or the organizations
indifferences to such practices. To test the hypothesis that these three factors are the
primary ones that influence unethical practices, the researcher would look for data
that could refute the hypothesis. When even a single case does not support the
hypothesis, the theory could be revised. Let us say that researcher has find a case
where an individual is deliberately engaged in the unethical practice of accepting
kickbacks (despite the fact that he was knowledgeable enough to discriminate
between right and wrong, was not in the need of money, and knew that the
organization would not be indifferent to his behavior) simply he wanted to get back at
the system, which would not listen to his advice. This new discovery through
disconfirmation of the original hypothesis, known as negative case method, enables
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the researcher to revise the theory and the hypothesis until such time as the theory
becomes robust.
Summary:
Hypotheses, though important, are not essential for a study. A perfectly valid study
can be conducted without constructing single hypotheses.
Hypotheses are important for bringing clarity, specificity and focus to a research
study.
A hypothesis is a speculative statement that is subjected to verification through a
research study. In formulating a hypothesis it is essential to make sure that it is
simple, specific and conceptually clear; is able to be verified; is rooted in an existed
body of knowledge; and able to be operationalized.
The testing of the hypothesis becomes meaningless if anyone of the aspect of your
study, design, sampling procedures, method of data collection, analysis of data,
statistical procedures applied or conclusive drawn is faulty or inappropriate this can
result in erroneous verification of hypothesis.
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Hypothesis
REFRENCES:
Yogesh Kumar & Ruchika Nath. Research Methodology
Uma Sekaran. Research Methods for Business A Skill Building Approach Fourth
Edition
Retrived 2 April 2, 2010 from http://www.wikipedia.org/
Dr. Tariq H. Malik. Meliorism of research Methodology
http://www.stats.gla.ac.uk/steps/glossary/hypothesis_testing.html#h1
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