STATISTICAL TECHNIQUES AND TOOLS
TESTS OF SIGNIFICANCE
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Always the same as the p value
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The pre-set threshold for significance
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The sample size
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The power
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Detailed explanation-1: -The significance level or alpha level is the probability of making the wrong decision when the null hypothesis is true. Alpha levels (sometimes just called “significance levels”) are used in hypothesis tests. Usually, these tests are run with an alpha level of . 05 (5%), but other levels commonly used are .
Detailed explanation-2: -The most common threshold is p < 0.05, which means that the data is likely to occur less than 5% of the time under the null hypothesis. When the p-value falls below the chosen alpha value, then we say the result of the test is statistically significant.
Detailed explanation-3: -With an alpha level of 0.01, there will be only a 1% chance of rejecting a true Ho. The change in alpha will also effect the Type II error, in the opposite direction. Decreasing alpha from 0.05 to 0.01 increases the chance of a Type II error (makes it harder to reject the null hypothesis).