In this week I will dig deeper
into the concept of hypothesis testing. This blog aims to orient on various
statistical concepts in an example oriented and simplified manner. With this
aim I am now going deeper into the concept of hypothesis testing. Testing of
hypothesis is confirmatory in nature. Here either a null hypothesis is rejected
and an alternative hypothesis is accepted or a null hypothesis is accepted and
an alternative hypothesis is rejected. These conclusions are based on results
obtained from a sample, through the computation of a test statistic. This test
statistic is based on sampling distribution of sample statistic. The value of
the test statistic is compared with the tabulated value and either the null
hypothesis is accepted or the null hypothesis is rejected. These are inferences
about the population based on results obtained from the sample.
Null hypothesis is interested in
maintaining the “Status Quo”. Alternative hypothesis is the opposite of null
hypothesis.
For example: A person is
looking for greener pastures and so is in look out for a new job.
Null Hypothesis: Current job is
good (maintaining the status quo)
Alternative Hypothesis: The new
job is good (opposite of null hypothesis)
(to be continued tomorrow)
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