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Quantitative Analysis


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P-Value


The smallest level of significance at which the null hypothesis can be rejected. It indicates the probability that a calculated test statistic as large or larger is the product of chance alone. P-values range from 0 to 1. A zero p-value would mean that the probability of sampling a population and obtaining a test statistic (t-statistic) with as large or larger a value is nil. The smaller the p-value, the stronger the evidence against the null hypothesis and in favor of the alternative hypothesis. Typically, p-values smaller than 0.05 are deemed statistically significant for the null hypothesis to be rejected.

If the p-value is less than an assumed level of significance, the null hypothesis will be rejected. For example, assume that the p-value of a given test statistic is 0.003, and that the required level of significance is 0.05. Because the p-value is smaller than the level of significance, we reject the null hypothesis.

For a practical example, see: p-value in application.


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