Question

In chi-squared analysis, by convention, when the p-value for the difference between the observed experimental outcomes and the expected outcome is less than 5 percent (p < 0.05)?
a. The experimental results are considered to be statistically significantly different from the expected outcome. b. The experimental results are NOT considered to be statistically significantly different from the expected outcome. c. The difference between the experimental results (data) and the expected results are so large (statistically) that we should rule out the hypothesis that generated those expectations. d. The difference between the experimental results (data) and the expected results are NOT that great (in a statistical sense). Thus, we should NOT rule out the hypothesis that generated those expectations.

Answer 1

The experimental results are considered to be statistically significantly different from the expected outcome.

In order for a result to be considered statistically significant, an analyst must conclude that it cannot be solely attributed to chance. The analyst reaches this conclusion via statistical hypothesis testing. It is employed to offer support for the null hypothesis, which contends that the data are merely the product of random chance, to show that the null hypothesis is plausible.

With the assumption that the results are actually of pure chance, this test yields a p-value, which is the likelihood of seeing outcomes as extreme as those in the data. It is frequently accepted that a p-value of 5% or less indicates statistical significance. The p-value for the discrepancy between the observed experimental results and the expected result in the particular scenario is less than 5% (p 0.05). It is therefore statistically significant.

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