1. A (n) _________________ hypothesis is a hypothesis that stands in opposition
ID: 3179768 • Letter: 1
Question
1. A (n) _________________ hypothesis is a hypothesis that stands in opposition to the null hypothesis.
2. An alternative or research hypothesis that specifies the nature or direction of a hypothesized difference is considered a ___________________.
3. A ________________ tailed test scenario is appropriate when the alternative or research hypothesis is non-directional in nature.
4. A_________________ tailed test scenario is appropriate when the alternative or research hypothesis is directional in nature.
5. A Type I error involves ____________ a null hypothesis when it is ____________.
6. A Type II error involves ____________ a null hypothesis when it is ____________.
Explanation / Answer
1. A (n) _________________ hypothesis is a hypothesis that stands in opposition to the null hypothesis.
3. A ________________ tailed test scenario is appropriate when the alternative or research hypothesis is non-directional in nature.
4. A_________________ tailed test scenario is appropriate when the alternative or research hypothesis is directional in nature.
5. A Type I error involves ____________ a null hypothesis when it is ____________.
6. A Type II error involves ____________ a null hypothesis when it is ____________.
[ANSWERS]
1. Alternative
3.TWO
4.ONE
5.REJECT HO, TRUE
6.ACCEPT HO,FALSE
REASONS:
1.
Null hypothesis (H0)
The null hypothesis states that a population parameter is equal to a value
The alternative hypothesis states that the population parameter is different than the value of the population parameter in the null hypothesis. The alternative hypothesis is what you might believe to be true or hope to prove true
3.
A two-tailed test allows you to determine if two means are different from one another. A direction does not have to be specified prior to testing.
A one-tailed test allows you to determine if one mean is greater or less than another mean, but not both. A direction must be chosen prior to testing.
5.
Type I and Type II errors
• Type I error, also known as a “false positive”: the error of rejecting a null
hypothesis when it is actually true.
• Type II error, also known as a "false negative": the error of not rejecting a null
hypothesis when the alternative hypothesis is the true state of nature.
type II error in a test with rejection region R is 1 ( | is true) - P R Ha
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