In a test of statistical hypotheses, the P-value tells usO the probability of observing a sample mean as we did or something more unusual ifthe null hypothesis is true.if the null hypothesis is true.if the alternative hypothesis is true.the largest level of significance at which the null hypothesis can be rejected.

In a test of Statistical hypothesis The p value tells us a..The probability of observing a sample…

Answered: In a test of statistical hypotheses,…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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Suppose a hypothesis test was performed with a level of significance of 0.05. Then if the null hypothesis is actually true, then there is a 5% chance that the researcher will end up rejecting the null hypothesis in error. True False
What does it mean when sample results are statistically significant?
☐True ☐False As a general rule, as the sample size increases the probability of rejecting the null hypothesis decreases.
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If the p-value is very large (say close to 1), then it is likely that we will reject the null hypothesis. True False
Statistics is not about getting accurate results. It is about Finding sufficient evidence to prove that your null hypothesis (Ho) is correct Gathering data about the population Finding sufficient evidence to prove that your null hypothesis statement is wrong
If the null hypothesis is false, you cannot make which kind of error? Type I Type II
Charlie will perform a hypothesis test at the a = 0.05 level. Felice will perform the same test at the a = 0.01 level.
Evaluate the significance of the p-value. You can think of the p-value as the probability that the null hypothesis is true. A value greater than 0.05 indicates that in more than 1 in 20 (or more than 5%) repetitions of an experiment of the same size, the observed deviation from predicted valuescould have been obtained by chance, even if the null hypothesis is actually true; the data are therefore not significant for rejecting the null hypothesis. Statisticians have arbitrarily selected the 0.05 p-value as the boundarybetween rejecting or not rejecting the null hypothesis. A p-value of less than 0.05 means that you can consider the deviation to be significant, and you can reject the null hypothesis.
A university has decided to introduce the use of plus and minus grading as long as there is evidence that 60% of the faculty is in support of this change. Write an appropriate null hypothesis and alternate hypothesis to test if the proportion is greater than 60%.
A fellow student tells you the P-value is the probability that the null hypothesis is true, so when the P-value is small, you reject the null hypothesis. Explain why the student is not correct. What would you tell the student about the P-value to help them out? What exactly is the relationship between the P-value and the hypotheses?
In hypothesis testing, O if the P-value is 0.01, we should conclude there is a 1% chance the null hypothesis is false. O neither the test statistic nor the P-value can ever be negative. O we always begin the hypothesis test by assuming the null hypothesis is true. O if the P-value is 0.99, we should conclude that the null hypothesis is true. O results that are statistically significant will always be practically important (or practically significant).

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