Hypothesis Testing One major function of inferential statistics is the testing of the hypotheses. When researchers “test a hypothesis” they are testing the null hypothesis and the assumption that...

The Hypothesis Testing
In hypothesis testing, a sample data is taken and results are retrieved from that sample data to reject/not reject the null hypothesis value which is assumed to be true for population parameter. During hypothesis testing, null hypothesis and alternative hypothesis are assumed, both of which are exclusive (Hung et al, 1997). During hypothesis testing there might occurs two types of error:
(I) Type-I error (Rejecting a null hypothesis when it’s actually true): This type of error occurs due to low power of sample size, using higher level of significance and improper research techniques e.g. no use of random sample etc.
(II) Type-II error (Not rejecting a null hypothesis when it’s actually false): This type of errors occurs due to low power of sample size, using very low level of significance etc.
It’s not possible to minimise probability of committing Type-I and Type-II...