The p-value is one of the business statisticians best tools and friends. Evaluating the p-value provides insight and outcomes about null hypothesis and indicates strength of possible conclusions to outcomes according to Lind, Marchal & Wathen (2015). The p-value lets the statistician know whether or not they should accept or reject outcomes. Even if this decision is not final, it gives insight and direction into possible happenings.
When it comes to normal curves, the p-value tells the statistician where the data lies, inside or outside the designated critical region. Where this lies and the level of significance is paramount when it comes to deciphering the puzzle because it shows the confidence of weather or not to accept or reject the null. If the p-value is smaller than the level of significance, this means the null should be rejected because the significance is a sign of small probability where the null can be excepted. Also, if the p-value is less than the confidence level this means the data lies in the designated critical region and should be rejected. The smaller the p-value the more the test should reject the null and gives significant proof of why. This p-value can basically give insight to the business statisticians of how to make decisions.
Lind, D.A., Marchal, W.G., & Wathen, S.A. (2015). Statistical Techniques in Business & Economics. McGraw -Hill Education: New York.
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