It is tentative answer to research question
It is tentative because its genuineness can be
evaluated only after it has been used empirically
Hypothesis are useful and they guide research
process in proper direction in mere fact finding
In all analytical and experimental studies
hypothesis should be set up in order to give a
proper direction to them.
Number of steps are involved in testing hypothesis
Set up suitable significance level
e.g. 5% or1%
Choose test criterion
e.g. t-test, Z-test, f-test & Chi Square test
Compute the statistic
e.g. whether to accept or reject Null/ Alternative
Research: Analytical study of FDI and its impact on
economy in last decade.(2002-2012)
There is positive relationship between FDI & GDP
We develop Null Hypothesis Ho for testing the
This null hypothesis is specifically formulate for
testing for possible rejection or nullification
The null hypothesis is always a statement of no
change or no difference or no relationship
e.g. There is no positive relationship between FDI
H0 is accompanied by an alternative Hypothesis
H0 -There is no positive relationship between FDI
Ha -There is positive relationship between FDI &
Both the H0 & Ha are expressed in terms
population parameter not in terms of sample
There are two types of errors that can be committed in
making decisions regarding accepting and rejecting the
If null hypothesis which is actually true is rejected, the
decision based on the sample evidence is wrong. Such
an error is called type I error.
If the null hypothesis is false but is not rejected, then
the error is called type II error.
LEVEL OF SIGNIFICANCE
It signifies the probability of committing type I error α and
generally taken as equal to 5% (α = 0.05)
This means that even after testing the hypothesis when
decision is made, we may still committing an error in
rejecting null hypothesis
Sometimes the value of α is taken as 0.01 but it is the
discretion of the investigator, depending upon the sensitivity
of the study.
If the calculated test value is larger than the
corresponding critical value (table value), we
reject the null hypothesis & conclude that the
research hypothesis is supported
If the table value is larger than the calculated
value, the research hypothesis is not supported.
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