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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A lower risk of Type II error and lower power
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A lower risk of Type II error and higher power
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A higher risk of Type II error and lower power
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No change in risk of Type II error or power
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Detailed explanation-1: -Increase the significance level The higher significance level implies a higher probability of rejecting the null hypothesis when it is true. The larger probability of rejecting the null hypothesis decreases the probability of committing a type II error while the probability of committing a type I error increases.
Detailed explanation-2: -The probability of making a type I error is , which is the level of significance you set for your hypothesis test. An of 0.05 indicates that you are willing to accept a 5% chance that you are wrong when you reject the null hypothesis. To lower this risk, you must use a lower value for .
Detailed explanation-3: -The significance level is usually set at 0.05 or 5%. This means that your results only have a 5% chance of occurring, or less, if the null hypothesis is actually true. To reduce the Type I error probability, you can set a lower significance level.