STATS.F/BUSN+ECON.PKG >C<
1st Edition
ISBN: 9781323767351
Author: MCCLAVE
Publisher: PEARSON C
expand_more
expand_more
format_list_bulleted
Concept explainers
Textbook Question
Chapter 14.6, Problem 14.33ACB
Annual U.S. craft beer production (cont’d). Refer to the beer production forecasts, Exercise 14.25 (p. 14-24). In part b you obtained forecasts of 2014 and 2015 craft beer production using Holt’s method with (w = .3. v = .7) and (w= .7, v = .3).
a. Calculate the forecast errors for the w = .3, v = .7 Holt forecasts.
b. Calculate the forecast errors for the w= .7, v = .3 Holt forecasts.
c Calculate MAD, MAPE, and RMSE for the w= .3, v = .7 Holt forecasts.
d. Calculate MAD, MAPE, and RMSE for the w= .7, v = .3 Holt forecasts.
e. Refer to parts c and d. Which forecast method do you recommend?
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solutionStudents have asked these similar questions
The article in the ASCE Journal of Energy Engineering (1999, Vol. 125, pp.59-75) describes a study of the thermal inertia properties of autoclaved aerated concrete used as a building material. Five samples of the material were tested in a structure, and the average interior temperatures (°C) reported were as follows: 23.01, 22.22, 22.04, 22.62, and 22.59. Test that the average interior temperature is equal to 22.5°C using alpha (a) = 0.05.
This problem is a test on what population parameter?
What is the null and alternative hypothesis?
What are the Significance level and type of test?
What standardized test statistic will be used?
What is the standard test statistic?
What is the Statistical Decision?
What is the statistical decision in the statement form?
You are observing the speeds of two CPUs, to find which one is expected to run faster. After a number of observations, you came up with the following results: CPU Speed Measurements 37 38 40 35 30 31 26 25 Number of Observations 18 15 CPU 1 CPU 2 10 10 10 5 0 2.0-24 2.5-2.9 3.5 - 3.9 4.0 - 4.5 3.0-3.4 Speed (GHz) A. Using this data, calculate the expected speed of each processor, and determine which of the two is faster. (Hint: when given a range of speeds, you can consider the average value within that range to be the speed at which the observations occurred).
Suppose your dependent variable is aggregate household demand for electricity for various cities. To correct for heteroskedasticity you should
Select one:
a. multiply observations by the square root of the city size
b. multiply observations by the city size
c. divide observations by the city size
d. divide observations by the square root of the city size
e. none of these
Chapter 14 Solutions
STATS.F/BUSN+ECON.PKG >C<
Ch. 14.1 - Explain in words how to construct a simple index.Ch. 14.1 - Explain in words how to calculate the following...Ch. 14.1 - Explain in words the difference between Laspeyres...Ch. 14.1 - The table below gives the prices for three...Ch. 14.1 - Refer to Exercise 14.4. The next table gives the...Ch. 14.1 - Annual median family income. The table below lists...Ch. 14.1 - Annual U.S. craft beer production. While overall...Ch. 14.1 - Quarterly single-family housing starts. The...Ch. 14.1 - Spot price of natural gas. The table shown in the...Ch. 14.1 - Employment in farm and nonfarm categories....
Ch. 14.1 - GOP personal consumption expenditures. The gross...Ch. 14.1 - GDP personal consumption expenditures (contd)....Ch. 14.1 - Weekly earnings for workers. The table in the next...Ch. 14.1 - Production and price of metals. The level or price...Ch. 14.2 - Describe the effect of selecting an exponential...Ch. 14.2 - A monthly time series is shown in the table to the...Ch. 14.2 - Annual U.S. craft beer production. Refer to the...Ch. 14.2 - Foreign fish production. Overfishing and pollution...Ch. 14.2 - Yearly price of gold. The price of gold is used by...Ch. 14.2 - Personal consumption in transportation. There has...Ch. 14.2 - OPEC crude oil imports. The data in the table...Ch. 14.2 - SP 500 Stock Index. Standard Poors 500 Composite...Ch. 14.5 - How does the choice of the smoothing constant w...Ch. 14.5 - Refer to Exercise 14.4 (p. 14-9). The table with...Ch. 14.5 - Annual U.S. craft beer production. Refer to...Ch. 14.5 - Quarterly single-family housing starts. Refer to...Ch. 14.5 - Consumer Price Index. The CPI measures the...Ch. 14.5 - OPEC crude oil imports. Refer to the annual OPEC...Ch. 14.5 - SP 500 Stock Index. Refer to the quarterly...Ch. 14.5 - SP 500 Stock Index (contd). Refer to Exercise...Ch. 14.5 - Monthly gold prices. The fluctuation of gold...Ch. 14.6 - Annual U.S. craft beer production. Refer to the...Ch. 14.6 - Annual U.S. craft beer production (contd). Refer...Ch. 14.6 - SP 500 Stock Index. Refer to your exponential...Ch. 14.6 - SP 500 Stock Index (contd). Refer to your Holt...Ch. 14.6 - Monthly gold prices. Refer to the monthly gold...Ch. 14.6 - US school enrollments. The next table reports...Ch. 14.8 - The annual price of a finished product (in cents...Ch. 14.8 - Retail sales in Quarters 14 over a 10-year period...Ch. 14.8 - What advantage do regression forecasts have over...Ch. 14.8 - Mortgage interest rates. The level at which...Ch. 14.8 - Price of natural gas. Refer to Exercise 14.9 (p....Ch. 14.8 - A gasoline tax on carbon emissions. In an effort...Ch. 14.8 - Predicting presidential elections. Researchers at...Ch. 14.8 - Life insurance policies in force. The table below...Ch. 14.8 - Graphing calculator sales. The next table presents...Ch. 14.8 - Prob. 14.47ACICh. 14.9 - Define autocorrelation. Explain why it is...Ch. 14.9 - For each case, indicate the decision regarding the...Ch. 14.9 - What do the following Durbin-Watson statistics...Ch. 14.9 - Company donations to charity. Refer to the Journal...Ch. 14.9 - Forecasting monthly car and truck sales. Forecasts...Ch. 14.9 - Predicting presidential elections. Refer to the...Ch. 14.9 - Mortgage interest rates. Refer to the data on...Ch. 14.9 - Price of natural gas. Refer to the annual data on...Ch. 14.9 - Life insurance policies in force. Refer to the...Ch. 14.9 - Modeling the deposit share of a retail bank....Ch. 14 - Insured Social Security workers. Workers insured...Ch. 14 - Insured Social Security workers (contd). Refer to...Ch. 14 - Retail prices of food items. In 1990, the average...Ch. 14 - Demand for emergency room services. With the...Ch. 14 - Mortgage interest rates. Refer to the annual...Ch. 14 - Price of Abbott Labs stock. The yearly closing...Ch. 14 - Price o f Abbott Labs stock (contd). Refer to...Ch. 14 - Prob. 14.65ACICh. 14 - Prob. 14.66ACICh. 14 - Quarterly GOP values (contd). Refer to Exercise...Ch. 14 - Prob. 14.68ACICh. 14 - Prob. 14.69ACICh. 14 - Prob. 14.70ACICh. 14 - IBM stock prices. Refer to Example 14.1 (p. 14-5)...Ch. 14 - Prob. 14.72ACI
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.Similar questions
- Given a two-tailed test, α = .05, N = 12 and H0 : ρ ≠ 0, which of these is the correct rcv? (You should refer to a table of critical values of r for this question.) A. –.497 B. ±.576 C. .576 D. ±.497arrow_forwardFor 50 randomly selected speed dates, attractiveness ratings by males of their female date partners (x) are recorded along with the attractiveness ratings by females of their male date partners (y); the ratings range from 1 to 10. The 50 paired ratings yield x=6.4, y=6.0, r=−0.170, P-value=0.238, and y=7.31−0.198x. Find the best predicted value of y (attractiveness rating by female of male) for a date in which the attractiveness rating by the male of the female is x=8. Use a 0.01 significance level. The best predicted value of y when x=8 isarrow_forwardWhich of the following is the correct alternative hypothesis for a non-directional independentmeasures t-test? A. M – μ = 0 B. M1 – M2 = 0 C. μ1 – μ2 = 0 D. M1 – M2 ≠ 0 E. μ1 – μ2 ≠ 0arrow_forward
- For 50 randomly selected speed dates, attractiveness ratings by males of their female date partners (x) are recorded along with the attractiveness ratings by females of their male date partners (y); the ratings range from 1 to 10. The 50 paired ratings yield x=6.3, y=6.0, r=−0.228, P-value=0.111, and y=7.81−0.280x. Find the best predicted value of y(attractiveness rating by female of male) for a date in which the attractiveness rating by the male of the female is x=5. Use a 0.10 significance level. The best predicted value of ywhen x=5 is nothing. (Round to one decimal place as needed.)arrow_forwardConsider the following model:? = ?? + ?,known as the Classical Linear Regression Model (CLRM), where y is the dependent variable, X is the set of independent variables, ? is the vector of parameters to be estimated and ? is the error term. Present and discuss the R2 and the adjusted R2. Discuss pros and cons of each of the two statistics.arrow_forwardBased on the EViews results above, answer the following questions.a. What is your comments on the diagnostic tests of the model? i. Autocorrelation test ii. Heteroscedasticity test iii. Normalityarrow_forward
- Betty, an employee of Shining Sun Daycare Centerread an article in Healthy Child Magazine sayingthat the average 3-year-old child is 37 in. tall.Betty works with 10 3-year-olds at Shining Sun,so later that week, she measured the height ofeach child who had just turned or was about toturn 3 years old. Here are the descriptive statisticsfor the sample: M = 35, s = 3.1. State the nondirectional hypothesis.2. Determine the critical t for a = .05.3. Calculate t. Show your calculations.4. Is the height of 3-year-olds in Shining SunDaycare Center significantly different fromthe height given in the magazine?arrow_forwardConsider the following two formulations of the bivariate PRF, where ui and εi are both mean-0 stochastic disturbances (i.e random errors): yi = β0 + β1xi + u yi = α0 + α1(xi − x¯) + ϵ a) Write the OLS estimators of β1 and α1. Are the two estimators the same? b) What is the advantage, if any, of the second model over the first?arrow_forwardHenry performed a two-tailed test for an experiment in which N = 24. He could not find his table of t critical values, but he remembered the tcv at df= 13. He decided to compare his tobt with this tcv. Is he more likely to make a Type I or a Type II error in this situation?arrow_forward
- For 50 randomly selected speed dates, attractiveness ratings by males of their female date partners (x) are recorded along with the attractiveness ratings by females of their male date partners (y); the ratings range from 1 to 10. The 50 paired ratings yield x=6.3, y=6.0, r=−0.257, P-value=0.072, and y=7.92−0.300x. Find the best predicted value of y (attractiveness rating by female of male) for a date in which the attractiveness rating by the male of the female is x=3. Use a 0.05 significance level. The best predicted value of y when x=3 is? (Round to one decimal place as needed.)arrow_forwardFor 50 randomly selected speed dates, attractiveness ratings by males of their female date partnerS (x) are recorded along with the attractiveness ratings by females of their male date partners (y); the ratings range from 1 to 10. The 50 paired ratings yield *= 6.3, y = 6.1. r= - 0.283, P.value = 0.046, and g = 8.39 - 0.369x. Find the best predicted value of y (attractiveness rating by female of male) for a date in which the attractiveness rating by the male of the female is x= 4. Use a 0.01 significance level. see score The best predicted value of g when x= 4 is 7. (Round to one decimal place as needed.)arrow_forwardFor 50 randomly selected speed dates, attractiveness ratings by males of their female date partners (x) are recorded along with the attractiveness ratings by females of their male date partners (y); the ratings range from 1 to 10. The 50 paired ratings yield *= 6.4. y = 6.0, r= - 0.279, P-value = 0.050, and g = 8.27 - 0.357x. Find the best predicted value of y (attractiveness rating by female of male) for a date in which the attractiveness rating by the male of the female is x=7. Use a 0.10 significance level. The best predicted value of y when x = 7 is (Round to one decimal place as needed.)arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
- MATLAB: An Introduction with ApplicationsStatisticsISBN:9781119256830Author:Amos GilatPublisher:John Wiley & Sons IncProbability and Statistics for Engineering and th...StatisticsISBN:9781305251809Author:Jay L. DevorePublisher:Cengage LearningStatistics for The Behavioral Sciences (MindTap C...StatisticsISBN:9781305504912Author:Frederick J Gravetter, Larry B. WallnauPublisher:Cengage Learning
- Elementary Statistics: Picturing the World (7th E...StatisticsISBN:9780134683416Author:Ron Larson, Betsy FarberPublisher:PEARSONThe Basic Practice of StatisticsStatisticsISBN:9781319042578Author:David S. Moore, William I. Notz, Michael A. FlignerPublisher:W. H. FreemanIntroduction to the Practice of StatisticsStatisticsISBN:9781319013387Author:David S. Moore, George P. McCabe, Bruce A. CraigPublisher:W. H. Freeman
MATLAB: An Introduction with Applications
Statistics
ISBN:9781119256830
Author:Amos Gilat
Publisher:John Wiley & Sons Inc
Probability and Statistics for Engineering and th...
Statistics
ISBN:9781305251809
Author:Jay L. Devore
Publisher:Cengage Learning
Statistics for The Behavioral Sciences (MindTap C...
Statistics
ISBN:9781305504912
Author:Frederick J Gravetter, Larry B. Wallnau
Publisher:Cengage Learning
Elementary Statistics: Picturing the World (7th E...
Statistics
ISBN:9780134683416
Author:Ron Larson, Betsy Farber
Publisher:PEARSON
The Basic Practice of Statistics
Statistics
ISBN:9781319042578
Author:David S. Moore, William I. Notz, Michael A. Fligner
Publisher:W. H. Freeman
Introduction to the Practice of Statistics
Statistics
ISBN:9781319013387
Author:David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:W. H. Freeman
Correlation Vs Regression: Difference Between them with definition & Comparison Chart; Author: Key Differences;https://www.youtube.com/watch?v=Ou2QGSJVd0U;License: Standard YouTube License, CC-BY
Correlation and Regression: Concepts with Illustrative examples; Author: LEARN & APPLY : Lean and Six Sigma;https://www.youtube.com/watch?v=xTpHD5WLuoA;License: Standard YouTube License, CC-BY