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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A public opinion poll surveyed a simple random sample of voters. Respondents were classified by gender (female or male) and by voting preference (Republican, Democrat, or Independent). The results are presented here: Republican 250 200 Female Male You want to determine if gender and voting preference are independent. Use a level of significance of a = 0.05. Are the requirements met for this hypothesis test? Explain. O Yes. A random sample was used, and all expected counts are greater than or equal to 5. O Yes. A random sample was used, and all observed counts are greater than or equal to 5. O No. A random sample was used, but at least one of the expected counts is less than 5. O No. A random sample was not used. Democrat 300 150 Independent 50 50
Type I error is "rejecting the null hypothesis when it is true." If a hypothesis, whether null or alternative, specifies just a single value for the population parameter, the hypothesis is said to be composite. III. The smallest significance level at which a null hypothesis can be rejected is called the probability value. Which of the above statements is/are true? 5. I.
Significance testing is similar to hypothesis testing, except rather than comparing a p-value to a level of significance to reach a conclusion, the p-value is used as a measure for how strong the information from the sample is as evidence against the null hypothesis. A small p-value indicates that the sample provides strong evidence against the null hypothesis and is statistically significant. A larger p-value indicates that the sample provides weaker evidence against the null hypothesis and is not statistically significant. Suppose that two rival scientists want to conduct the following hypothesis test for a certain population: Ho: ≤ 60 Hy: μ > 60 Assume that the mean of the population is known to be 8.4. Scientist 1 took a sample of 36 from the population and got a sample mean of 63.164000. What is the approximate p-value for Scientist 1's data? Scientist 2 took a sample of 8 from the population and got a sample mean of 64.276582. What is the approximate p-value for Scientist 2's…
If the decision in a hypothesis test said to reject Ho, then we can always make a conclusion that the sample data supports the claim. True False
true or false If the p-value is 0.13 and the level of significance , αα , is 0.05 in a hypothesis test for a mean, then we accept the null hypothesis.
Is this what significance means? Statistical significance is very often mentioned in research reports. When asked what it means, a student replies that "results that are statistically significant tell us that they cannot easily be explained by chance variation alone if the hypothesis testing was true. Do you think this statement is essentially correct? Explain your answer.
Failing to reject an invalid null hypothesis (continuing to incorrectly assume a null is valid) is called: the beta-risk. the level of confidence. the level of significance. the power of the test. the alpha-risk.
True/False portion: 1) The sample mean x is a point estimate for the population mean u. 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.
What does the p-value represent in a test of hypothesis? The p-value represents the significance level of the hypothesis test. The p-value is the probability that the sample data occurred given that the null hypothesis is true. The p-value is the probability that the sample data occurred given that the alternative hypothesis is true. The p-value is the probability that the null hypothesis is true.
Suppose you conduct 17 independent hypothesis tests each at the 8% significance level. Assume that every null hypothesis is true. The probability of making a type 1 error on a given test is 8%. What is the probability of making at least one error on 17 tests? Enter your answer as a probability, not a percent (so 0.456 rather than 45.6%). Round your answer to three decimal places.
Which of the following is the name for the statistical hypothesis that describes no change, or nothing expected? Type I error Null hypothesis Type II error Alternative hypothesis
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

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