The width of a confidence interval is determined, in part, by the variability pr
ID: 3182437 • Letter: T
Question
The width of a confidence interval is determined, in part, by the variability present in the population. A. True B. False The rejection of a true null hypothesis is known as a ________. A. good decision B. Type I Error C. Type II error D. sampling error If the null hypothesis is rejected, we have proven that the alternative is true. A. True B. False Values of the test statistic that separate the acceptance region from the rejection region are called ______ values. A. calculated B. critical C. sample D. population The statement of what the investigator is trying to conclude is placed in the _______ hypothesis. A. null B. alternative C. accepted D. rejected Which of the following is not true when applied to the t distribution? A. it approaches the standardized normal distribution as n approaches infinity B. it is symmetric about its median C. it has a mean of 0 and a variance of 1 D. there is a different t distribution for each degree of freedom value When the value of the level of significance is increased the probability for committing a Type II error _______. A. increases B. decreases C. stays the sameExplanation / Answer
Solution:
6. The Type I error is the error if we reject the null hypothesis even if it is true
Hence The rejection of a true null hypothesis is known as a B. Type I error
7. On the basis of test statistics calculated from random samples and critical value if we reject the null hypothesis we assume that alternative hypothesis is true
hence if the null hypothesis is rejected we have proven that the alternative is true
8. Value of the test statistics that separate the acceptance region from the rejection region are called B. critical values
9. The null hypothesis is probably contain equality of population quantity and hence the statement of what the investigator is trying to conclude is placed in the B. alternative hypothesis
10. Type I error and Type II error has the inverse relationship hence we can say the
When the value of the level of significance (type I error) is increased the probability for committing a Type II error B.decreases
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