The p-value in hypothesis testing represents: O the probability that the sample data are statistically significant, given that the null hypothesis is true none of these O the probability of failing to reject the null hypothesis, given the sample data the probability under the null hypothesis of obtaining data at least as extreme as the acquired data O the probability that the null hypothesis is true

Business Non response questionnaires were mailed to 300 randomly selected businesses in each of three categorical sizes. The following data shows the number of responses. Size of Company Response No Response Small 175 125 Medium 145 155 Large 120 180 Test the claim that the size of the company is independent of the company`s response State the null and alternative  hypothesis    Give the p-value   Give a conclusion for the hypothesis test

The null hypothesis in the test for goodness of fit is that   a.  the data fit the expected frequencies.   b.  the data do not fit the expected frequencies.   c.  the variables are independent.   d.  the variables are dependent.

In hypothesis testing the statistical conclusion is either to reject or not to reject the null hypothesis based on the sample data. Which of the following statements is true? The conclusion will always reject a false null hypothesis. The conclusion is always subject to error because it is based on sample data. The conclusion will never reject a true null hypothesis. The conclusion is always free from error if the correct procedure is foll

What is the correct interpretation of the significance level a in a hypothesis test? The probability that H, is true given that Ho is NOT rejected The probability that Ho is true given that Ho is rejected The probability of NOT rejecting Ho given that H, is true The probability of rejecting Ho given that Ho is true

The term "p-value," which comes into play in the analysis and conclusions steps of the scientific method, can be defined as: O The probability that the alternative hypothesis is true. O The probability that the null hypothesis is true. O The probability of obtaining your data, or something even more extreme, if the null hypothesis is true. The probability that you should reject your alternative hypothesis.

Which one of the following statements is incorrect:   A. A type I error consists of rejecting the null hypothesis when it is true B. A type II error consists of accepting the null hypothesis when it is false C. You can control simultaneously both the Type I and Type II error probabilities when the sample size is fixed D. Hypothesis testing and confidence intervals are related concepts

An educator claims that the average salary of substitute teachers in the school districts in his county is less than $90 per day. A random sample of 8 schools districts is selected and the daily salaries are shown below. What is the test statistic for this hypothesis test?               $90  $86  $90  $85  $100  $85  $90  $85  An educator claims that the average salary of substitute teachers in the school districts in his county is less than $90 per day. A random sample of 8 schools districts is selected and the daily salaries are shown below. What is the test statistic for this hypothesis test?               $90  $86  $90  $85  $100  $85  $90  $85  0.2756 0.5512 -0.626 -1.860 0.7244

Which of the statements are correct? I. The chi-square goodness-of-fit test uses n - 1 degrees of freedom. II. A condition for using the chi-square goodness-of-fit test is that all expected counts must be at least five. III. A condition for using the chi-square goodness-of-fit test is the observations are based on a random sample. OI only Oll only OI and II only O II and III only O I, II, and III