The sample mean x is a point estimate for the population mean u. In tests of significance, it is possible to reject the null hypothesis and still have a significant result. yet 3) If one rejects the null hypothesis at the 5% level, then there is a 5% chance that you made the wrong decision.

Calculus For The Life Sciences
2nd Edition
ISBN:9780321964038
Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Chapter12: Probability
Section12.4: Discrete Random Variables; Applications To Decision Making
Problem 10E
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False portion:
The sample mean x is a point estimate for the population mean µ.
2)
In tests of significance, it is possible to reject the null hypothesis and yet
still have a significant result.
3)
If one rejects the null hypothesis at the 5% level, then there is a 5% chance
that you made the wrong decision.
In the p-value approach, if p-value>a (the level of significance) we reject
the null hypothesis.
5)
If you fail to reject the null hypothesis at the 5% level, then the probability
that you are wrong is always 5%.
A wider confidence interval gives a greater level of confidence than a
6)
narrower one (when working with the same data).
If the sample mean of a data set is 3.2 then the population mean must also
7)
be 3.2
8)
As the sample size (n) increases, the standard deviation of x from that
sample decreases, this assumes the standard deviation is positive..
9)
The level of significance is the probability of rejecting the null hypothesis
when the null hypothesis is true.
10)
Classical hypothesis testing can give different decisions than the P-value approach
even with the same level of significance, hypotheses and data?
Transcribed Image Text:4 100% False portion: The sample mean x is a point estimate for the population mean µ. 2) In tests of significance, it is possible to reject the null hypothesis and yet still have a significant result. 3) If one rejects the null hypothesis at the 5% level, then there is a 5% chance that you made the wrong decision. In the p-value approach, if p-value>a (the level of significance) we reject the null hypothesis. 5) If you fail to reject the null hypothesis at the 5% level, then the probability that you are wrong is always 5%. A wider confidence interval gives a greater level of confidence than a 6) narrower one (when working with the same data). If the sample mean of a data set is 3.2 then the population mean must also 7) be 3.2 8) As the sample size (n) increases, the standard deviation of x from that sample decreases, this assumes the standard deviation is positive.. 9) The level of significance is the probability of rejecting the null hypothesis when the null hypothesis is true. 10) Classical hypothesis testing can give different decisions than the P-value approach even with the same level of significance, hypotheses and data?
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