1) A false positive rate is the rate of falsely rejecting the Ho i.e. null hypothesis for a particular problem.
2) The goal of a hypothesis testing is to provide an evidence over the insignificance of of the alternate hypothesis i.e. the possibilty of not rejecting the null hypothesis.
3) A Type I error is defined as the possibility of rejecting Ho
when Ho is true in nature i.e.
P(Type I error) = P(Rejecting Ho / Ho is true) <=
i.e. the alpha level is the maximum value of P(Type I error).
4) When the results of a hypothesis test are statistically significant, then we conclude to reject the null hypothesis i.e. we accept the claim given in the alternative hypothesis.
5) In a hypothesis testing, a p-value is the probability of obtaining any possible extremes along with the assumption of the null hypothesis being true in nature. A p-value is used in making a decision about the rejection/ acceptance of a null hypothesis i.e. when the p-value < , we reject the null hypothesis.
Hope this answers your query!
Name: Section Number To be graded assignments must be completed and submitted on the original book...
Name: Section Number: To be graded, all assignments must be completed and submitted on the original book page Introduction It is important that you be able to compute correctly. However, computation prowess is no substitute for a deeper understanding of what you are doing and why. This is especially true in the field of statistical science. At the undergraduate level, computations are pretty easy. At all levels, however, the underlying concepts are challenging. The following activity will demonstrate and elucidate...
1) Determine whether each of the following applies to the mull or the alternative hypothesis. A) Ho B) Ha or H C) The hypothesis that has equality (i.e. no difference). D) The hypothesis that has no equality (i.e. greater, less, or different). E) The hypothesis we assume is true until we have evidence to reject it. F) The research hypothesis. The goal in a hypothesis test is to test a claim. hypothesis. hypothesis. G) The statistical evidence can only support...
Select the correct definition of the p-value of a test from the answer choices below: The probability that the null hypothesis is true The probability that, assuming the null hypothesis is true, we obtained a test statistic as or more extreme than what we calculated The probability that, assuming the alternative hypothesis is true, we obtained a test statistic as or more extreme than what we calculated The probability that the alternative hypothesis is false, given that the null hypothesis...
α is the probability of a Type I error, which occurs when we accept the alternative H1 when the null hypothesis Ho is true. True False A Type II error occurs when when a false null hypothesis is rejected. True False If a null hypothesis is rejected at the 5% significance level but not at the 1% significance level, then the p-value of the test is less than 1%. True False The power of a test is the probability of...
These are all True & False Questions. Just write the number and T/F 6. If we reject the null hypothesis, we can conclude that the sample differs from the population mean. T/F 7. Type II error occurs when we set α to high. T/F 8. The alpha level determines the risk of Type I error. T/F 9. In a two-tailed test, you need more evidence to reject the null hypothesis. T/F 10. If the researcher hypothesizes that a treatment will...
True or False The model used for hypothesis testing of proportions is called a two-proportion z-test. True or False Beta (β) is the significance level which determines if the null hypothesis is rejected. True or False In business, the p-value is one of several factors in determining whether or not to reject a null hypothesis. True or False We could make a decision to reject a null hypothesis on a very low p-value or a very high z score.
Question 21 (4 points) For a hypothesis test about a population proportion or mean, if the level of significance is less than the p- value, the null hypothesis is rejected. (Ch10) True False Question 22 (4 points) Everything else being constant, increasing the sample size decreases the probability of committing a Type II error. (Ch10) True False The power of a statistical test is the probability of not rejecting the null hypothesis when it is true. (Ch10) True False Question...
An interval of numbers within which the parameter value is believed to fall. A number such that we reject Ho if the p-value is less than or equal to that number. The numerical value obtained from a statistical test. A statistical statement that says a difference between the parameter and a specific value exists or states that there is a difference between two parameters. The error that occurs if you reject the null hypothesis when it is true. 10. The...
you determine tiC meam and When designing statistical tests we need to consider a number of different factors. Please, explain shortly the following: 3 What is the test significance level and its correspondence to confidence interval? a) b) What are the Type I (false positive) and Type II (false negative) errors? Assume that the rejection region is R and the null hypothesis in Ho? error types? What is the connection between the respective c) What is the meaning of a...
The 2002 General Social Survey asked, "What do you think is the ideal number of children for a family to have?" The 484 females who responded had a mean of 2.97, and standard deviation of 1.77. The 95% confidence interval is (2.81, 3.13). (a) What is the sample statistic? (b) Find the standard error. (c) Using the confidence interval, what can you say about the true population mean? 1. We are confident that 95% of Americans think that the true...