What p-Value Tells The Business Statistician, Especially in Terms of The Normal Curve?

Grand Canyon –  Sym 506 Weekly Discussion

What does the p-value tell the business statistician, especially in terms of the normal curve? If the p-value is smaller than the level of significance, what does that mean in terms of the null hypothesis? Why?

Calculated probability or P value is the chance of establishing observed or extreme outcomes when the study null hypothesis of a question of study is true. P value is normally employed to establish the statistical importance of a hypothesis test.  In this case, the p value tells the business statistician the importance of the hypothetical test to the business. Thus it plays a great role in evaluating the current or future situation of a business based on the hypothetical question or test in question. The statistical hypothesis tests are employed to test the population claim validity. In case the null hypothesis is not true then the alternative hypothesis is taken in. P value measures the effectiveness of a data by establishing the variation of the actual data from the normal curve. The hypothesis is used to create a normal curve and the collected data is used to create the actual curve. The divergence of the actual curve from the normal curve determines how much data defies the anticipated normal and thus cautioning a business statistician on how much the business may need to be adjusted to attain the designed value. Thus p value can be used especially when demonstrated using a curve to establish how far the business data defies what would be considered as normal business outcome. If p value is below the level of significance it simply implies that the null hypothesis is not true. In this case the null hypothesis is rejected while the alternative hypothesis is taken in. The p-value focuses on evaluating the significance of the statistics using the null hypothesis. Thus the data is only considered significance if it satisfies the null hypothesis. Thus if it appears anywhere below the


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