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About 77631 results. 1294 free access solutions
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Condition |
free/or 0.5$ |
| m6928 | After meeting with the regional sales managers, Lauretta Anderson, president of Cowpie Computers, Inc., you find that she believes that the probability that sales will grow by 10% in the next year is 0.70. After coming to this conclusion, she receives a report that John Cadariu of Minihard Software, Inc., has just announced a new operating system that will be available for customers in 8 months. From past history she knows that in situations where growth has eventually occurred, new operating systems have been announced 30% of the time.
However, in situations where growth has not eventually occurred, new operating systems have been announced 10% of the time. Based on all these facts, what is the probability that sales will grow by 10%? |
buy |
| m6929 | Aimed at finding substantial earnings decreases, a random sample of 23 firms with substantial earnings decreases showed that the mean return on assets 3 years previously was 0.058 and the sample standard deviation was 0.055. An independent random sample of 23 firms without substantial earnings decreases showed a mean return of 0.146 and a standard deviation 0.058 for the same period. Assume that the two population distributions are normal with equal standard deviations.
Test, at the 5% level, the null hypothesis that the population mean returns on assets are the same against the alternative that the true mean is higher for firms without substantial earnings decreases. |
buy |
| m6930 | Allied Financial is considering the possibility of adding one or more computer industry stocks to its portfolio. You are asked to consider the possibility of Seagate, Microsoft, and Tata Information systems. Data for this task are contained in the data file Return on Stock Price 60 Months. Compare the return on these three stocks by computing the beta coefficients and the mean and variance of the returns. What is your recommendation regarding these three stocks? |
buy |
| m6931 | Although the samples are actually related, an investigator ignores this fact in the statistical analysis and uses a t test for two independent samples. How will this mistake affect the probability of a type II error? |
buy |
| m6932 | Amalgamated Power, Inc., has asked you to estimate a regression equation to determine the effect of various predictor variables on the demand for electricity sales. You will prepare a series of regression estimates and discuss the results using the quarterly data for electrical sales during the past 17 years in the data file Power Demand.
a. Estimate a regression equation with electricity sales as the dependent variable, using the number of customers and the price as predictor variables. Interpret the coefficients.
b. Estimate a regression equation (electricity sales) using only number of customers as a predictor variable. Interpret the coefficient and compare the result to the result from part a.
c. Estimate a regression equation (electricity sales) using the price and degree days as predictor variables. Interpret the coefficients. Compare the coefficient for price with that obtained in part a.
d. Estimate a regression equation (electricity sales) using disposable income and degree days as predictor variables. Interpret the coefficients. |
buy |
| m6933 | American Travel Air has asked you to study flight delays during the week before Christmas at Midway Airport. The random variable X is the number of flights delayed per hour.
a. What is the cumulative probability distribution?
b. What is the probability of five or more delayed flights?
c. What is the probability of three through seven (inclusive) delayed flights? |
buy |
| m6934 | An accounting firm has 1200 clients. From a random sample of 120 clients, 110 indicated very high satisfaction with the firm s service. Find a 95% confidence interval for the proportion of all clients who are very highly satisfied with this firm. |
buy |
| m6935 | An administrator for a large group of hospitals believes that of all patients 30% will generate bills that become at least 2 months overdue. A random sample of 200 patients is taken.
a. What is the standard error of the sample proportion that will generate bills that become at least 2 months overdue?
b. What is the probability that the sample proportion is less than 0.25?
c. What is the probability that the sample proportion is more than 0.33?
d. What is the probability that the sample proportion is between 0.27 and 0.33? |
buy |
| m6936 | An agency offers preparation courses for a graduate school admissions test to students. As part of an experiment to evaluate the merits of the course, 12 students were chosen and divided into 6 pairs in such a way that the members of any pair had similar academic records. Before taking the test, one member of each pair was assigned at random to take the preparation course, while the other member did not take a course. The achievement test scores are contained in the Student Pair data file. Assuming that the differences in scores follow a normal distribution, test, at the 5% level, the null hypothesis that the two population means are equal against the alternative that the true mean is higher for students taking the preparation course. |
buy |
| m6937 | An agency offers students preparation courses for a graduate school admissions test. As part of an experiment to evaluate the merits of the course, 12 students were chosen and divided into six pairs in such a way that the two members of any pair had similar academic records. Before taking the test, one member of each pair was assigned at random to take the preparation course, while the other member took no course.
The achievement test scores are contained in the Student Pair data file. Assuming that the differences in scores are normally distributed, find a 98% confidence interval for the difference in means scores between those who took the course and those who did not. |
buy |
| m6938 | An agricultural economist believes that the amount of beef consumed (y) in tons in a year in the United States depends on the price of beef (x1) in dollars per pound, the price of pork (x2) in dollars per pound, the price of chicken (x3) in dollars per pound, and the income per household (x4) in thousands of dollars. The following sample regression was obtained through least squares, using 30 annual observations:
The numbers in parentheses under the coefficients are the estimated coefficient standard errors.
a. Interpret the coefficient on log x1.
b. Interpret the coefficient on log x2.
c. Test, at the 1% significance level, the null hypothesis that the coefficient on log x4 in the population regression is 0 against the alternative that it is positive.
d. Test the null hypothesis that the four variables (log x1, log x2, log x3, log x4) do not, as a set, have any linear influence on log y.
e. The economist is also concerned that, over the years, the increasing awareness of the effects of heavy red-meat consumption on health may have influenced the demand for beef. If this is indeed the case, how would this influence your view of the original estimated regression? |
buy |
| m6939 | An agricultural experiment designed to assess differences in yields of corn for four different varieties, using three different fertilizers, produced the results (in bushels per acre) shown in the following table:
a. Prepare the two-way analysis of variance table.
b. Test the null hypothesis that the population mean yields are identical for all four varieties of corn.
c. Test the null hypothesis that population mean yields are the same for all three brands of fertilizer. |
buy |
| m6940 | An aircraft company wanted to predict the number of worker-hours necessary to finish the design of a new plane. Relevant explanatory variables were thought to be the plane’s top speed, its weight, and the number of parts it had in common with other models built by the company. A sample of 27 of the company’s planes was taken, and the following model was estimated:
y = β0 + β1x1 + β2x2 + β3x3 + ε
where
y = design effort, in millions of worker-hours
x1 = plane’s top speed, in miles per hour
x2 = plane’s weight, in tons
x3 = percentage of parts in common with other models
The estimated regression coefficients were as follows:
b1 = 0.661 b2 = 0.065 b3 = -0.018
The total sum of squares and regression sum of squares were found to be as follows:
SST = 3.881 and SSR = 3.549
a. Compute and interpret the coefficient of determination.
b. Compute the error sum of squares.
c. Compute the adjusted coefficient of determination.
d. Compute and interpret the coefficient of multiple correlation. |
buy |
| m6941 | An aircraft company wanted to predict the number of worker-hours necessary to finish the design of a new plane. Relevant explanatory variables were thought to be the plane’s top speed, its weight, and the number of parts it had in common with other models built by the company. A sample of 27 of the company’s planes was taken, and the following model was estimated:
y = β0 + β1x1 + β2x2 + β3x3 + ε
where
y = design effort, in millions of worker-hours
x1 = plane’s top speed, in miles per hour
x2 = plane’s weight, in tons
x3 = percentage of parts in common with other models
The estimated regression coefficients were as follows:
b1 = 0.661 b2 = 0.065 b3 = -0.018
The estimated standard errors were as follows:
sb1 = 0.099 sb2 = 0.032 sb3 = 0.0023
a. Find 90% and 95% confidence intervals for β1.
b. Find 95% and 99% confidence intervals for β2.
c. Test against a two-sided alternative the null hypothesis that, all else being equal, the plane’s weight has no linear influence on its design effort.
d. The error sum of squares for this regression was 0.332.
Using the same data, a simple linear regression of design effort on the percentage of common parts was fitted, yielding an error sum of squares of 3.311. Test, at the 1% level, the null hypothesis that, taken together, the variable’s top speed and weight contribute nothing in a linear sense to explaining the changes in the variable, design effort, given that the variable percentage of common parts is also us |
buy |
| m6942 | An aircraft company wanted to predict the number of worker-hours necessary to finish the design of a new plane. Relevant explanatory variables were thought to be the plane’s top speed, its weight, and the number of parts it had in common with other models built by the company. A sample of 27 of the company’s planes was taken, and the following model was estimated:
y = β0 + β1x1 + β2x2 + β3x3 + ε
where
y = design effort, in millions of worker-hours
x1 = plane’s top speed, in miles per hour
x2 = plane’s weight, in tons
x3 = percentage of parts in common with other models
The estimated regression coefficients were as follows:
b1 = 0.661 b2 = 0.065 b3 = -0.018
The total sum of squares and regression sum of squares were found to be as follows:
SST = 3.881 and SSR = 3.549
a. Test the null hypothesis:
H0: β1 = β2 = β3 = 0
b. Set out the analysis of variance table. |
buy |
| m6943 | An aircraft company wanted to predict the number of worker-hours necessary to finish the design of a new plane. Relevant explanatory variables were thought to be the plane’s top speed, its weight, and the number of parts it had in common with other models built by the company. A sample of 27 of the company’s planes was taken, and the following model was estimated:
y` = β0 + β1x1i + β2x2i + β3x3i + εi
where
yi = design effort, in millions of worker-hours
x1i = plane’s top speed, in miles per hour
x2i = plane’s weight, in tons
x3i = percentage number of parts in common with other models
The estimated regression coefficients were as follows:
b0 = 2 b1 = 0.661 b2 = 0.065 b3 = -0.018
Interpret these estimates. |
buy |
| m6944 | An ambulance service receives an average of 15 calls per day during the time period 6 p.m. to 6 a.m. for assistance.
For any given day what is the probability that fewer than 10 calls will be received during the 12-hour period? What is the probability that more than 17 calls during the 12-hour period will be received? |
buy |
| m6945 | An analyst attempting to predict a corporation s earnings next year believes that the corporation s business is quite sensitive to the level of interest rates. He believes that, if average rates in the next year are more than 1% higher than this year, the probability of significant earnings growth is 0.1. If average rates next year are more than 1% lower than this year, the probability of significant earnings growth is estimated to be 0.8. Finally, if average interest rates next year are within 1% of this year s rates, the probability for significant earnings growth is put at 0.5. The analyst estimates that the probability is 0.25 that rates next year will be more than 1% higher than this year and 0.15 that they will be more than 1% lower than this year.
a. What is the estimated probability that both interest rates will be 1% higher and significant earnings growth will result?
b. What is the probability that this corporation will experience significant earnings growth?
c. If the corporation exhibits significant earnings growth, what is the probability that interest rates will have been more than 1% lower than in the current year? |
buy |
| m6946 | An analyst believes that the only important determinant of banks returns on assets (Y) is the ratio of loans to deposits (X). For a random sample of 20 banks, the sample regression line
y = 0.97 + 0.47x
was obtained with coefficient of determination 0.720.
a. Find the sample correlation between returns on assets and the ratio of loans to deposits.
b. Test against a two-sided alternative at the 5% significance level the null hypothesis of no linear association between the returns and the ratio. |
buy |
| m6947 | An analyst forecasts corporate earnings, and her record is evaluated by comparing actual earnings with predicted earnings. Define the following:
actual earnings = predicted earnings + forecast error.
If the predicted earnings and forecast error are independent of each other, show that the variance of predicted earnings is less than the variance of actual earnings. |
buy |
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