Statement of Hypothesis
The two hypothesis i ,e, null hypothesis (H_{0}) and Alternative Hypothesis (H_{1}) are so constructed that if one is correct the other is wrong. Generally the Null Hypothesis for testing the mean will take any one of the followings forms:
H0 : µ ≤ µ_{0} H_{0 }: µ µ_{0 }H_{0} : µ = µ_{0}
Where= population mean and µ_{0} hypothesis value .
Step 2. Specification of Significant level
The validity of H0 against H1 is then ascertained at a certain level of significance. The significance level stands for the confidence with which the experimenter rejects or retains the null hypothesis. Significance level is usually expressed as percentage or by the value of α i ,e, 5% or α= =0.05.
Step3. Formulation of the Rejection and Acceptance Regions
The followings table give the typical cases of setting up the regions of rejection acceptance for the various cases of H0 with the hypothesized value of the population mean.
Making the Inference
On the basis of the sample mean calculated from the sample data a decision is made from the rule given in step4. If the samples mean lies in the region of rejection, null hypothesis H0 is rejected while alternative HypothesisH1 is accepted. If the samples mean lies in the region of acceptance the alternative step has been done. From the figure above one can observe that the area in the tails equal the level of significance. For one tailed test appear in one tail and for two tailed test α/ 2 appears in each tail of the curve.