National open university of nigeria introduction to econometrics I eco 355

3.4. The Choice between Confidence-Interval and Test-of-Significance Approaches 
to Hypothesis Testing 
In most applied economic analyses, the null hypothesis is set up as a straw man and the 
objective of the empirical work is to knock it down, that is, reject the null hypothesis. 
Thus, in our consumption–income example, the null hypothesis that the MPC 
is 
patently absurd, but we often use it to dramatize the empirical results. Apparently editors 
of reputed journals do not find it exciting to publish an empirical piece that does not 
reject the null hypothesis. Somehow the finding that the MPC is statistically different 
from zero is more newsworthy than the finding that it is equal to, say, 0.7.
Thus, J. Bradford De Long and Kevin Lang argue that it is better for economists. 

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4.0 
CONCLUSION 
In this unit we conclude that in the study of statistics, a statistically significant result (or 
one with statistical significance) in a hypothesis test is achieved when the p-value is less 
than the defined significance level. The p-value is the probability of obtaining a test 
statistic or sample result as extreme as or more extreme than the one observed in the 
study whereas the significance level or alpha tells a researcher how extreme results must 
be in order to reject the null hypothesis. 
 
5.0 
SUMMARY 
The unit has discussed extensively the analysis of level of significance and the exact p 
value, in addition to how to interpret the level of significance in hypothesis testing. I 
belief at this junction that you must have learn through this unit of level of significance 
and it‘s rudimentary.
6.0 
TUTOR MARKED ASSESSMENT EXERCISE 
 
Write short note on ―Level of Significance‖