Author Question: Which of the following is true about Type I errors? a. Considered only when results are not ... (Read 37 times)

torybrooks · **on:** Jul 8, 2018

Which of the following is true about Type I errors?

a. Considered only when results are not statistically significant in a study
b. Extremely likely to happen when p is less than 0.001
c. More likely to happen when p is less than 0.01 rather than p is less than 0.05
d. Occur when the researcher says there is a significance, but findings are actually not statistically significant

Question 2

Which of the following is true about the level of significance? The level of significance:

a. ensures that findings will be correct 95 of the time if an alpha value of less than 0.05 is used.
b. refers to a statistic calculated during computer analysis of data.
c. represents the probability of getting a calculated statistic as high as the one found in the study if the null hypothesis is really true.
d. represents the risk the researcher is willing to take in making a Type I error and is established before data are analyzed.

ms_sulzle · **Reply #1 on:** Jul 8, 2018

Answer to Question 1

ANS: D
With a Type I error, study results indicate there is a significant difference, when in reality there is not.
Researchers should always be concerned with both Type I and Type II errors. With a Type I error, study results indicate there is a significant difference, when in reality there is not.
A Type I error is less likely to happen with smaller and smaller levels of significance. With a Type I error, study results indicate there is a significant difference, when in reality there is not. C. With a Type I error, study results indicate there is a significant difference, when in reality there is not.

Answer to Question 2

ANS: D
A Type I error occurs when the null hypothesis is rejected, though it is actually true. The level of significance is the cutoff point selected by the researcher before data collection that indicates the probability of a true significant difference between groups.
It is the likelihood of correct findings, but cannot ensure that they actually are correct.
A p value is calculated by the computer, but this is compared to the level of significance determined acceptable by the researcher.
It actually has to do with making a Type I error. A Type I error occurs when the null hypothesis is rejected, though it is actually true.