# Sample Paper on Difference between P-Value of One-tailed and Two-tailed Test

When conducting a statistical significance test, p-values are generally provided in the output of the population selected. Therefore, ANOVA, regression, and correlation majorly apply the formula during hypothesis testing to assist in understanding the data transmitted. A one-tailed test is one-sided on the critical distribution area, and it is greater than or less than a particular figure, but not both (Hick 316). However, the two-tailed tests is a technique where the critical region is two-sided and confirms if the samples are within the range of values identified in a null hypothesis.

First, alpha levels assist in providing relatively accurate results. Hence, it is the probability of arriving an incorrect decision when the null hypothesis is correct. Therefore, one-tailed uses the aggregate value, and it can only appear on either the left or right side. However, a two-tailed splits the alpha into half.  The distinction between and two-tailed P-value is more straightforward in context. In the interpretation of a one-tail P value, it is possible to interpret the group that will have extensive data (Mourougan Sendi and Sethurama 37). Besides, a two-tailed selection involves a random range of benefits from the sample in case the null hypothesis is correct.

In differentiating the two tests, power must also be considered because it provides a relevant distinction. One-tailed tests subject the researcher into focusing on one side of the distribution table. Moreover, there is more power to one-tiled tests because people are always sure of the decisions made. The two-tailed test considers the probable outcomes making it difficult to rely on one provision. Therefore, it is easier to make conclusions of the sample with the one-tail null hypothesis being correct.

Work Cited

Hick, W. E. “A note on one-tailed and two-tailed tests.” (1952): 316.

Mourougan, Sendil, and K. Sethuraman. “Hypothesis Development and Testing.” J. Bus. Manag 19 (2017): 34-40.