True/False portion: 1) The sample mean x is a point estimate for the population mean µ. In tests of significance, it is possible to reject the null hypothesis and yet still have a significant result. 2) If one rejects the null hypothesis at the 5% level, then there is a 5% chance 3) that you made the wrong decision.

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
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Chapter1: Starting With Matlab
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True/False portion:
1)
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)
that you made the wrong decision.
If one rejects the null hypothesis at the 5% level, then there is a 5% chance
4)
In the p-value approach, if p-value>a (the level of significance) we reject
the null hypothesis.
If you fail to reject the null hypothesis at the 5% level, then the probability
5)
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..
The level of significance is the probability of rejecting the null hypothesis
9)
when the null hypothesis is true.
10)
even with the same level of significance, hypotheses and data?
Classical hypothesis testing can give different decisions than the P-value approach
Transcribed Image Text:True/False portion: 1) 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) that you made the wrong decision. If one rejects the null hypothesis at the 5% level, then there is a 5% chance 4) In the p-value approach, if p-value>a (the level of significance) we reject the null hypothesis. If you fail to reject the null hypothesis at the 5% level, then the probability 5) 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.. The level of significance is the probability of rejecting the null hypothesis 9) when the null hypothesis is true. 10) even with the same level of significance, hypotheses and data? Classical hypothesis testing can give different decisions than the P-value approach
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