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HYPOTHESES
 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
investigation
 In all analytical and experimental studies
hypothesis should be set up in order to give a
proper direction to them.
HYPOTHESIS TESTING
Number of steps are involved in testing hypothesis
 Formulate 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
 Make decision
e.g. whether to accept or reject Null/ Alternative
hypothesis
Formulate Hypothesis:
Research: Analytical study of FDI and its impact on
economy in last decade.(2002-2012)
Hypothesis:
There is positive relationship between FDI & GDP
 We develop Null Hypothesis Ho for testing the
hypothesis.
 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
& GDP
 H0 is accompanied by an alternative Hypothesis
Ha
e.g.
H0 -There is no positive relationship between FDI
& GDP
Ha -There is positive relationship between FDI &
GDP
Both the H0 & Ha are expressed in terms
population parameter not in terms of sample
statistics
 There are two types of errors that can be committed in
making decisions regarding accepting and rejecting the
null hypothesis.
 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.
DECISION
 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.
Hypotheses

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Hypotheses

  • 2.  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 investigation  In all analytical and experimental studies hypothesis should be set up in order to give a proper direction to them.
  • 3. HYPOTHESIS TESTING Number of steps are involved in testing hypothesis  Formulate 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  Make decision e.g. whether to accept or reject Null/ Alternative hypothesis
  • 4. Formulate Hypothesis: Research: Analytical study of FDI and its impact on economy in last decade.(2002-2012) Hypothesis: There is positive relationship between FDI & GDP
  • 5.  We develop Null Hypothesis Ho for testing the hypothesis.  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 & GDP
  • 6.  H0 is accompanied by an alternative Hypothesis Ha e.g. H0 -There is no positive relationship between FDI & GDP Ha -There is positive relationship between FDI & GDP Both the H0 & Ha are expressed in terms population parameter not in terms of sample statistics
  • 7.  There are two types of errors that can be committed in making decisions regarding accepting and rejecting the null hypothesis.  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.
  • 8. 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.
  • 9. DECISION  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.