Spreadsheet Modeling & Decision Analysis: A Practical Introduction To Business Analytics, Loose-leaf Version
8th Edition
ISBN: 9781337274852
Author: Ragsdale, Cliff
Publisher: South-Western College Pub
expand_more
expand_more
format_list_bulleted
Concept explainers
Videos
Textbook Question
Chapter 1, Problem 18QP
Consider the spreadsheet model shown in Figure 1.2. Is this model descriptive, predictive, or prescriptive in nature, or does it not fall into any of these categories?
Figure 1.2
Example of a simple spreadsheet model
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solution
Students have asked these similar questions
Provide an explanation of the operation of predictive analytics and a practical application of the method.
What type of analytics seeks to recognize what is going on as well as the likely forecast and make decisions to achieve the best performance possible?
domain
predictive
prescriptive
descriptive
What does the robustness of a data mining method refer to?
its ability to construct a prediction model efficiently given a large amount of data
its speed of computation and computational costs in using the mode
its ability to overcome noisy data to make somewhat accurate predictions
its ability to predict the outcome of a previously unknown data set accurately
Provide an explanation for the operation of predictive analytics and a scenario in which it might be useful.
Chapter 1 Solutions
Spreadsheet Modeling & Decision Analysis: A Practical Introduction To Business Analytics, Loose-leaf Version
Ch. 1 - Prob. 1QPCh. 1 - Prob. 2QPCh. 1 - Prob. 3QPCh. 1 - Prob. 4QPCh. 1 - What is the relationship between business...Ch. 1 - What kinds of spreadsheet applications would not...Ch. 1 - Prob. 7QPCh. 1 - Prob. 8QPCh. 1 - What is a dependent variable?Ch. 1 - What is an independent variable?
Ch. 1 - Can a model have more than one dependent variable?Ch. 1 - Can a decision problem have more than one...Ch. 1 - Prob. 13QPCh. 1 - Prob. 14QPCh. 1 - In what ways are descriptive models different from...Ch. 1 - Prob. 16QPCh. 1 - Prob. 17QPCh. 1 - Consider the spreadsheet model shown in Figure...Ch. 1 - Prob. 19QPCh. 1 - Prob. 20QPCh. 1 - Prob. 21QPCh. 1 - Prob. 22QPCh. 1 - Prob. 23QPCh. 1 - Prob. 24QPCh. 1 - Prob. 25QPCh. 1 - Prob. 26QPCh. 1 - Prob. 27QP
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, management and related others by exploring similar questions and additional content below.Similar questions
- The Baker Company wants to develop a budget to predict how overhead costs vary with activity levels. Management is trying to decide whether direct labor hours (DLH) or units produced is the better measure of activity for the firm. Monthly data for the preceding 24 months appear in the file P13_40.xlsx. Use regression analysis to determine which measure, DLH or Units (or both), should be used for the budget. How would the regression equation be used to obtain the budget for the firms overhead costs?arrow_forwardUnder what conditions might a firm use multiple forecasting methods?arrow_forwardWhat are the basic assumptions in contrast to causal techniques when using predictive time series techniques?arrow_forward
- How does predictive analytics benefit CRM? Give examples of predictive analytics models used in CRM for sales forecasting or customer churn prediction.arrow_forwardWhich of the following is true about using forecasts? Forecast accuracy decreases the farther into the future you are trying to predict. Forecasts become more accurate when predicting further into the future. Forecasts are useless when the future will look radically different from the past. The more complex the forecast, the more accurate are the predictions. The accuracy of forecasts does not vary from one application to another.arrow_forwardwhat are the differences between the following models? 1) Moving average models 2) Simple exponential smoothing 3) Holt's exponential smoothing 4) Winter's exponential smoothing 5) The Bass model In your answer, write down the equation for each model. What does each variable mean? Finally, why would I use one model as opposed to the others? For example, the Bass Model is used to forecast the adoption rate for new innovations, or sigmoid shaped growth.arrow_forward
- What is the difference between a causal model and a time-series model?arrow_forwardBusiness analytics can be of three types: descriptive, predictive, and prescriptive. Describe each of those. Imagine you are a data analyst in FedRetail, an online retail shop. Your manager wants a forecast of the sell in the upcoming Christmas season. What kind of analysis you should do to find out your manager's query? Explain.arrow_forwardDetermine the type of business analytics for the following scenarios. A. Imagine you are a meteorologist. You have to foretell the weather for the next two weeks by analysing the data from the satellites. Here, you have to apply advanced statistical, information software, or operations research methods to identify predictive variables and build predictive models. Discuss in detail which type of business analytics will be suitable for this scenario.arrow_forward
- What are the basic types of forecasts? What are their strengths and weaknesses?arrow_forwardWhich of the following is not true of qualitative forecasting methods? a. They generally work best when combined with a quantitative approach b. They are more objective than quantitative methods c. They are largely non-mathematical d. They are not restricted to only the quantifiable data e. They come with the danger of biasing the forecast due to subjectivity Explain both true and false options brieflyarrow_forwardWhat are the principles of the forecasting process ?arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
MarketingMarketingISBN:9780357033791Author:Pride, William MPublisher:South Western Educational Publishing
Contemporary MarketingMarketingISBN:9780357033777Author:Louis E. Boone, David L. KurtzPublisher:Cengage Learning
Practical Management ScienceOperations ManagementISBN:9781337406659Author:WINSTON, Wayne L.Publisher:Cengage,
Marketing
Marketing
ISBN:9780357033791
Author:Pride, William M
Publisher:South Western Educational Publishing
Contemporary Marketing
Marketing
ISBN:9780357033777
Author:Louis E. Boone, David L. Kurtz
Publisher:Cengage Learning
Practical Management Science
Operations Management
ISBN:9781337406659
Author:WINSTON, Wayne L.
Publisher:Cengage,
Introduction to Forecasting; Author: Ekeeda;https://www.youtube.com/watch?v=5eIbVXrJL7k;License: Standard YouTube License, CC-BY