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Question 1 95% confident that the population mean is between 3 and 6. If the hypothesized population mean (i.e., test value) is 2, what conclusion

Question 1

95% confident that the population mean is between 3 and 6. If the hypothesized population

mean (i.e., test value) is 2, what conclusion can you make?

A There is not enough information to retain or reject the null hypothesis.

B Reject the null hypothesis.

C Retain the null hypothesis.

D Both retain and reject the null hypothesis.

Question 2

If the calculated t is not in the rejection region, the p-value is:

A There is not enough information to make this determination

B Greater than .05

C Both less than .05 and greater than .05; it depends

D Less than .05

Question 3

P is greater than 5%, what should your conclusion be in the context of a one sample t-test:

A Retain the null hypothesis; the population mean is not significantly different than the test value

B Reject the null hypothesis; the population mean is not significantly different than the test value

C Reject the null hypothesis; the population mean is significantly different than the test value

D Retain the null hypothesis; the population mean is significantly different than the test value.

Question 4

The population mean is not equal to the test value signifies the following:

A Retain the null hypothesis.

B The population correlation may be 0 - retain as one among many hypotheses that the data support.

C The sample correlation may be 0 - retain as one among many hypotheses that the data support.

D Reject the null hypothesis.

Question 5

T-obtained is -2.56 and t-critical is -1.45. What is the correct conclusion?

A P> .05; Reject the null hypothesis

B P>.05: Retain the null hypothesis

C P< .05; Reject the null hypothesis

D P< .05; Retain the null hypothesis

Question 6

T-obtained is 6.56 and t-critical is 7.45. What is the correct conclusion?

A P<.05; Reject the null hypothesis

B. P> .05; Reject the null hypothesis

C. P< .05: Retain the null hypothesis

D. P> .05; Retain the null hypothesis

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