A factor in determining the usefulness of an examination as a measure of demonstrated ability is the amount of spread that occurs in the grades. If the spread or variation of examination scores is very small, it usually means that the examination was either too hard or too easy. However, if the variance of scores is moderately large, then there is a definite difference in scores between "better," "average," and "poorer" students. A group of attorneys in a midwestern state has been given the task of making up this year's bar examination for the state. The examination has 500 total possible points, and from the history of past examinations, it is known that a standard deviation of around 60 points is desirable. Of course, too large or too small a standard deviation is not good. The attorneys want to test their examination to see how good it is. A preliminary version of the examination (with slight modifications to protect the integrity of the real examination) is given to a random sample of 20 newly graduated law students. Their scores give a sample standard deviation of 73 points. Using a 0.01 level of significance, test the claim that the population standard deviation for the new examination is 60 against the claim that the population standard deviation is different from 60. (a) What is the level of significance? State the null and alternate hypotheses. Ho: a = 60; H₁: or <60 Ho: o = 60; H: σ #60 60 (b) Find the value of the chi-square statistic for the sample. (Round your answer to two decimal places.) What are the degrees of freedom? Ho: o>60; H₁: a = 60 Ho: a = 60; H₁: o> What assumptions are you making about the original distribution? We assume a uniform population distribution. We assume a binomial population distribution. We assume a normal population distribution. We assume a exponential population distribution. (c) Find or estimate the P-value of the sample test statistic. P-value > 0.100 0.050 < P-value < 0.100 0.005 < P-value < 0.010 P-value < 0.005 0.025 < P-value < 0.050 0.010< P-value < 0.025

There are several possible explanations for the existence of a statistical relationship between two variables. Which is not a common explanation? A. Common Cause B. Confounding factor C. Coincidence D. None of the above

Are America's top chief executive officers (CEOs) really worth all that money? One way to answer this question is to look at row B, the annual company percentage increase in revenue, versus row A, the CEO's annual percentage salary increase in that same company. Suppose that a random sample of companies yielded the following data: Do these data indicate that the population mean percentage difference in corporate revenue (row B) is different from the population mean percentage increase in CEO salary? Use a 1% level of significance.     (A) Are the data statistically significant at level α? Will you reject or fail to reject the null hypothesis?      Since the interval containing the P-values has values that are larger than the level of significance, the data are not statistically significant and so we fail to reject the null hypothesis.       (a)Since the interval containing the P-values has values that are larger than the level of significance, the data…

You saw back in Chapter 2 that the mean, median, mode, and midrange are used to indicate where data is centered in a data set, or in other words what a typical value in the set is. A question that is often asked is, "If they're all supposed to do the same thing, why is there more than one?" Isn't one enough? In this exercise, you will be given two small sets of data. For each set, a. find the mean, median, mode and midrange b. in your opinion, decide which of the measures BEST represents all the values in the set (best indicates a typical value), and which one does this the WORST. c. post your responses and justify them by explaining why Don't forget to respond to at least one of your classmate's posts. With this exercise, "more is better." I'll elaborate after the deadline. • Set A: the salaries of 10 employees at a company (in thousands of dollars): 50, 50, 50, 50, 50, 50, 50, 50, 50, 500 • Set B: the grades of 9 students on an exam: 20, 25, 30, 35, 40, 45, 100, 100, 100

Buckle up! - How does seat belt use vary with drivers' ethnic group? It is well known that location and gender (males are less likely to buckle up) are factors. Here is the data and the mosaic plot for a random sample of male drivers observed in Houston. Ethnic group of driver Belted Not Belted Total Black 277 99 376 Hispanic 373 164 537 White 197 62 259 Total 847 325 1172 Ethnicity Hispanic Black White Use of Seat Belt wearing a seat belt not wearing a seat belt

The Bureau of Labor Statistics reports that the official unemployment rate for Black people was 10.4% and 4.7% for White people in February 2015. Select all correct answers for this question. O The samples of white and black people are independent. The explanatory variable is the unemployment rate. The response variable is the unemployment rate. The response variable is race.

Given a sample data set with a Variance of 12.25 and Mean of 4.0, what is the Coefficient of Variation of the data set.?

You just finished statistics class and are eager to collect and analyze your own data!  You run out and collect data on students' living arrangements (measured as either on-campus housing or off-campus housing) and whether they are involved in extra-curricular activities (measured as either involved or not involved).  You want to examine whether there is an equal distribution of students who live on- and off-campus among those are are involved or not involved in extra-curricular activities.  You will most likely use ___ to analyze your data.         Group of answer choices a z-test a two-sample t-test a one-sample t-test an ANOVA a correlation a chi-square test a z-score a one-predictor regression a two-predictor regression

Imagine a study comparing two groups:  undergrad vs. graduate students in terms of stress level. You find that 100% of the graduate students in your study are men and 100% of your undergraduate students are women. What effect does knowing the gender distribution have on your research conclusions?

Are America's top chief executive officers (CEOs) really worth all that money? One way to answer this question is to look at row B, the annual company percentage increase in revenue, versus row A, the CEO's annual percentage salary increase in that same company. Suppose that a random sample of companies yielded the following data:  B: Percent for company 5 8 13 16 14 20 4 13 A: Percent for CEO 2 –1 3 14 19 17 3 9 Do these data indicate that the population mean percentage increase in corporate revenue (row B) is different from the population mean percentage increase in CEO salary? Use a 1% level of significance. Are the data statistically significant at level α? Will you reject or fail to reject the null hypothesis? choose one:  a) Since the interval containing the P-values has values that are smaller than the level of significance, the data are statistically significant and so we reject the null hypothesis.   b) Since the interval containing…