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Explaining 6 Basic Statistics Questions on Hypothesis Testing

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I am just wanting someone to see if answered these word questions correctly. My book isn't exactly to the direct point. I understand if your unable to.

Which of the following accurately describes the critical region?
* outcomes with a high probability if the null hypothesis is true
* outcomes with very low probability if the null hypothesis is true (this is the one i selected?)
* outcomes with a high probability whether or not the null hypothesis is true
* outcomes with a very low probability whether or not the null hypothesis is true

with o= .05, how are the boundaries for the critical region determined?
* boundaries are drawn so there is 5% (0.5) in the center of the distribution
* boundaries are drawn so there is 5 % (.05) in each tail (this is what i chose, but i am torn between it and the 2.5% because of each tail?)
* boundaries are drawn so there is 2.5% (.025) in each tail
* boundaries are drawn so there is 10% (.10) in each tail of the distribution

If a hypothesis test produces a z score in the critical region, what decision should me made?
*fail to reject the null hypothesis
* fail to reject the alternative hypothesis
* reject the alternative hypothesis
* reject the null hypothesis (this is the one i had chosen?)

A sample of n= 25 individuals is selected from a population with u=80 and a treatment is administered to the sample. what is expected if the treatment has no effect?
* the sample mean should be very different from 80 and should lead you to fail to reject the null hypothesis
* the sample mean should be close to 80 and should lead you to fail to reject the null hypothesis
* the sample mean should be very different from 80 and should lead you to reject the null hypothesis
* the sample mean should be close to 80 and should lead you to reject the null hypothesis. ( this is the one that i had chosen?)

which of the following is an accurate definition of a type 1 error?
* rejecting a false null hypothesis
* rejecting a true null hypothesis (this is the one i had chosen?)
* failing to reject a false null hypothesis
* failing to reject a true null hypothesis

which of the following is an accurate definition of a type II error?
* rejecting a true null hypothesis
* rejecting a false null hypothesis
* failing to reject a true null hypothesis
* failing to reject a false null hypothesis ( this is the one i had chosen?)

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Which of the following accurately describes the critical region?
outcomes with very low probability if the null hypothesis is true

with o= .05, how are the boundaries for the critical region ...

Solution Summary

The solution gives detailed steps on explaining 6 basic statistics questions including hypothesis testing, type 1 error, type 2 error and critical region.

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Six basic statistics questions regrading hypothesis testing

A two tailed hypothesis test is being uses to evaluate a treatment effect with o= .05. if the sample data produce a z- score of z= -2.24 what is the correct decision?

* reject the null hypothesis and conclude that the treatment has an effect
* fail to reject the null hypothesis and conclude that the treatment has no effect
* fail to reject the null hypothesis and conclude that the treatment has an effect
* reject the null hypothesis and conclude that the treatment has no effect

the critical boundaries for a hypothesis test are z= +1.96 and -1.96. if the z score for the sample data is z= -1.90, what is the correct statistical decision?

* reject H1
* reject Ho
* fail to reject Ho
* fail to reject H1

A researcher administers a treatment to a sample of participants selected from a population with u= 80. If a hypothesis test is used to evaluate the effect of the treatment which combination of factors is most likely to result in rejecting the hypothesis?

* a sample mean much different than 80 with o= .01
* a sample mean near 80 with o=.01
* a sample mean much different than 80 with o= .05
* a sample mean near 80 with o= .05

under what circumstances can a very small treatment effect still be significant
* if the standard error of M (oM) is very large
* if the sample size of (n) is very large
* if the sample standard deviation (o) is very large
* all of these factors are likely to produce significant results.

A sample of n=9 individuals is selected from a population with u= 60 and o=6, and a treatment is administered to the sample. after the treatment, the sample mean M= 63. What is the Cohen's d for this sample?

* 1.00
* 0.33
* 2.00
* 0.50

Which of the following is an accurate definition for the power of a statistical test?
* the probability of supporting a false null hypothesis
* the probability of rejecting true null hypothesis
* the probability of rejecting a false null hypothesis
* the probability of supporting true null hypothesis

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