The level of significance refers to the probability of making a Type I error. □ True □ False a) For a given sample size, revising a decision rule so that the probability of a Type I error is decreased will also decrease the probability of making a Type II error. □ True □ False b) The first step in hypothesis testing is to determine the critical value(s) of the test statistic. □ True □ False c) Compared to using a = 0.10, the selection of a = 0.001 will tend to make it less likely that a true null hypothesis will be rejected. □ True □ False

The level of significance refers to the probability of making a Type I error. □ True □ False a) For a given sample size, revising a decision rule so that the probability of a Type I error is decreased will also decrease the probability of making a Type II error. □ True □ False b) The first step in hypothesis testing is to determine the critical value(s) of the test statistic. □ True □ False c) Compared to using a = 0.10, the selection of a = 0.001 will tend to make it less likely that a true null hypothesis will be rejected. □ True □ False

College Algebra (MindTap Course List)

12th Edition

ISBN:9781305652231

Author:R. David Gustafson, Jeff Hughes

Publisher:R. David Gustafson, Jeff Hughes

Chapter8: Sequences, Series, And Probability

Section8.7: Probability

Problem 58E: What is meant by the sample space of an experiment?

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Determine whether the following situation is true. When performing a hypothesis test for one population proportion with significance level of 5%, using critical value approach or the p-value approach might result in different conclusions. a) True b) False
Suppose the results indicate that the null hypothesis should not be rejected; thus, it is possible that a type II error has been committed. Given the type of error made in this situation, what could researchers do to reduce the risk of this error? Choose a 0.01 significance level, instead of a 0.05 significance level. Increase the sample size.
Suppose the results indicate that the null hypothesis should be rejected; thus, it is possible that a type I error has been committed. Given the type of error made in this situation, what could researchers do to reduce the risk of this error? Choose a 0.01 significance level, instead of a 0.05 significance level. Increase the sample size.
What is the relationship between the t-test and the sample size? (i.e., when will a t-test be more likely to be significant/you would reject the null)?
The sample size is 41, P-value is 0.041, and the significance level is 0.05. Consequently, we reject the null hypothesis.
A hypothesis test is conducted with a level of significance of 10% and the resulting p value is .08 . This means that the test is statistically significant at the relevant level of significance, and the null hypothesis should be rejected. True False
Will conducting a hypothesis test and a confidence interval always result in the same statistical conclusion in analyses involving one and two population, assuming a constant type I error? Explain why.
The ___________ is a value used in making a decision about the null hypothesis and is found by converting the sample statistic to a score with the assumption that the null hypothesis is true.
To decide whether the variation among sample mean ranks is large enough to warrant rejection of the null hypothesis of equal population means, we use the ratio of_________to________. This ratio is called the -statistic.
A researcher looks at the mean salaries of male and female electricians and decides based on the evidence that there is no difference between the two groups. Given that there was a failure to reject the null hypothesis, it is possible that a type II error was made. Given the type of error made in this situation, what could researchers do to reduce the risk of this error? Choose a .01 significance level, instead of a .05 significance level. Increase the sample size.
2. if both XA and XB data come from a sample that is given two different treatments,then display the data in the form of paired data and perform a two-average difference test fordependent sample at 95% confidence level
The drug Ritalin is designed to stimulate the central nervous system. In a random sample of 252 boys aged ten – twelve years old, it was found that 44 of the boys were taking Ritalin. It is known that the proportion of all boys aged 13 – 15 who take Ritalin is 24%. A researcher claims that the population proportions of boys who take Ritalin aged 10 – 12 is different than boys aged 13 – 15. Can you support this claim at the 5% significance level? a. Conduct a hypothesis test to test the claim at the 5% significance level. Be sure to state you Ho and Ha, your test statistic and p-value, whether or not you reject Ho and whether you support the claim. b. Show that you can use the large sample methodology. c. Write a complete sentence describing what a Type I error is in context.