Based on a small sample, a significance test may not yield a statisticallysignificant outcome even if the true value is considerably different fromthe null value. This outcome is also known as? *O significance levelO type l errortype Il errorO power of the test

Ans: A significance test may not yield a statistically significant outcome even if the true…

Answered: Based on a small sample, a significance…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The average retirement age in America is 66 years old. Do small business owners retire at an older average age? The data below shows the results of a survey of small business owners who have recently retired. Assume that the distribution of the population is normal. 63, 74, 59, 64, 74, 60, 71, 67, 65, 70, 63 What can be concluded at the the � = 0.05 level of significance level of significance? For this study, we should use The null and alternative hypotheses would be: �0: �1: The test statistic = (please show your answer to 3 decimal places.) The p-value = (Please show your answer to 4 decimal places.) The p-value is � Based on this, we should the null hypothesis. Thus, the final conclusion is that ... The data suggest the populaton mean is significantly older than 66 at � = 0.05, so there is sufficient evidence to conclude that the population mean retirement age for small business owners is older than 66. The data suggest…
please answer part b Also is there significant evidence that brand 1 and 3 different in mean ratings? is there significant evidence that brand 1 and 4 different in mean ratings? is there significant evidence that brand 2 and 3 different in mean ratings? is there significant evidence that brand 2 and 4 different in mean ratings? is there significant evidence that brand 3 and 4 different in mean ratings?
What is the null hypothesis? Why do we want to reject our null hypothesis? The first step is the find the mean of our sample and compare it to the "hypothesized" mean of our null hypothesis—why do we do that? We use the results of our first step to calculate a test-statistic. Why is this important and how does it relate to the concept of z-score, which we learned a few weeks ago? What is a p-value? What role does it play in the rejection of the null hypothesis? What does it mean to reject the null hypothesis? Does that guarantee that the null hypothesis is false?
Part 1: Hypothesis Test for the Mean- Manual Tasks• Define your concern of interest drawing upon your variables in your dataset.• Conceptualize your null and alternate hypotheses based on your testing concept.a. Apply 1 one-sided test (upper-tail or lower-tail) and 1 two-sided test concepts for the mean with unknown population standard deviation (�) at 1%, 5%, or 10% levels of significance (choose one of them for each test) by stating the appropriate decision rule. b. Calculate p-value for each of your tests and perform testing for your same hypotheses with p-value solution. Comment on how p-value changes for 1%, 5%, and 10% significance levels (for all three).**Here in order to apply normal distribution approximation, it would be better if you choose your sample size greater than 100 (n>100).c. Make a confidence interval estimation for the population mean with unknown variancebased on 90%, 95% and 99% confidence levels and make interpretations for all three. Data is: Name…
The Woodcock-Johnson Cognitive Ability test indicates that the average score is 95. The same group of 12th grade students (n = 72) in Columbus are tested and the sample mean is 110.1 and the sample standard deviation is 15.2. Do the scores provide good evidence that the mean IQ of this population is greater than 95? What is the p-value for this data what is your decision about the null hypothesis? reject or fail to reject?
The summary statistics are n=85, x=3.93, s=0.63. Use a 0.01 significance level to test the claim that the population of student course evaluations has a mean equal to 4.00. identify null/ alt hypothesis, test statistic, P- value, and state final conclusion that addresses the original claim
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Suppose an education administrator wants to know whether the test scores of a new standardized graduation exam are different for males and females. To test this hypothesis, the administrator decides to perform a ?‑test for two independent means. She takes a random sample of test scores from both male and female populations. Some of the summary data are shown in the table. Population PopulationDescription Samplesize Samplemean (pts) Sample standard deviation (pts) 1 Female ?1=21 ?⎯⎯⎯1=34.3 ?1=3.09 2 Male ?2=22 ?⎯⎯⎯2=34.7 ?2=3.82 The administrator assumes that the population variances are equal, so she computes a pooled ?‑test statistic. Determine the number of degrees of freedom, df, for the pooled ?‑statistic.
Please no written by hand solution and no img 4c. (Quantitative variable) Set up a T-distribution hypothesis test (StatCrunch T- stats -> One Sample). Copy and paste your results from StatCrunch into the write up. Explain the results (reject ?0 or fail to reject ?0) at the ?=0.05 significance level and at the ?=0.01 significance level. It is ok if this is the same question you used to construct the T-distribution confidence interval, if you don’t have enough quantitative questions in your survey to use a different question. Example hypothesis tests are in Chapter 7. Is the average mean of age for women higher than 0.05 and 0.01?
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Based on a small sample, a significance test may not yield a statistically significant outcome even if the true value is considerably different from the null value. This outcome is also known as? * O significance level O type I error O type II error power of the test