SOFTWARE PROJECT MANAGEMENT
QUALITY MANAGEMENT
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Type I Errors
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Type III Errors
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Type II Errors
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None of the above
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Detailed explanation-1: -A type I error is often called a false positive. This occurs when the null hypothesis is rejected even though it’s correct. The rejection takes place because of the assumption that there is no relationship between the data sets and the stimuli. As such, the outcome is assumed to be incorrect.
Detailed explanation-2: -The type I error rate is the probability of rejecting the null hypothesis given that it is true. The test is designed to keep the type I error rate below a prespecified bound called the significance level, usually denoted by the Greek letter (alpha) and is also called the alpha level.
Detailed explanation-3: -What Causes Type II Errors? A type II error is commonly caused if the statistical power of a test is too low. The highest the statistical power, the greater the chance of avoiding an error. It’s often recommended that the statistical power should be set to at least 80% prior to conducting any testing.