EBTM 350 Ch1 Homework
A bank developed a model for predicting the average checking and savings account balance as: Balance = -17,257 + 358*age + 1,243*years education + 0.135*household wealth. Suppose that a customer is 39 years old, is a college graduate (16 yrs education), and has a household wealth of $110,000. What is the predicted bank balance?
$31,443 [-17257+(358*39)+(1243*16)+(.135*110,000)]
A bank developed a model for predicting the average checking and savings account balance as: Balance = -17,257 + 358*age + 1,243*years education + 0.135*household wealth. The number -17,257 means...
...does not have a meaningful interpretation.
A bank developed a model for predicting the average checking and savings account balance as: Balance = -17,257 + 358*age + 1,243*years education + 0.135*household wealth. The number 358 means...
...that the average account balance increases by $358 for each year increase in age.
A bank developed a model for predicting the average checking and savings account balance as: Balance = -17,257 + 358*age + 1,243*years education + 0.135*household wealth. The number .135 means...
...that the average bank account balance increases by $0.135 for each $1 increase in household wealth.
A bank developed a model for predicting the average checking and savings account balance as: Balance = -17,257 + 358*age + 1,243*years education + 0.135*household wealth. The number 1,243 means...
...that the average bank account balance increases by $1,243 for each year increase in education
A supermarket has been experiencing long lines during peak periods of the day. The problem is noticeably worse on certain days of the week, and the peak periods sometimes differ according to the day of the week. There are usually enough workers on the job to open all cash registers. The problem the supermarket manager faces is knowing when to call some of the workers who are stocking shelves up to the front to work the checkout counters. Use this information to answer the given questions. What data would be needed when developing the model to facilitate good decisions? Select all that apply. A.Number of customers served per hour B. Day of the week C. Time of day D. Customer height
A, B, and C all relate to the problem. D does not relate to the problem.
An automobile company would like to determine the number of vehicles it could sell next year based on the proposed price. Which analytics tools would most likely be used for this scenario? A. Predictive B. Descriptive C. Prescriptive
A. Predictive (determine future sales)
A logistics company wants to better understand the relative profitability of its numerous customers over the past three years. Which analytics tools would most likely be used for this scenario? A. Predictive B. Prescriptive C. Descriptive
C. Descriptive (past three years=historical data)
How would one go about selecting the appropriate model? A. Obtain estimates for future marketing effort and demand and use a model to see if the predictions are accurate. B. Select a model that appears to make intuitive sense and fit the model to the data. C. Collect two data values each for marketing effort and demand and fit the data to a model. D. Collect a large amount of data for marketing effort and demand and fit the data to a model.
D. Collect a large amount of data for marketing effort and demand and fit the data to a model.
What does the model for b=0 tell about the relationship between demand and marketing effort?
Demand does not depend on marketing effort.
A financial advisor would like to develop the best mix of stocks, bonds, and other investments for a client to achieve a comfortable level of risk. Which analytics tools would most likely be used for this scenario? A. Descriptive B. Prescriptive C. Predictive
Prescriptive (best option)
A large service firm wishes to determine how to invest the cash received from its financial product to achieve the best return. Which analytics tools would most likely be used for this scenario? A. Descriptive B. Predictive C. Prescriptive
Prescriptive (best return)
Total marketing effort is a term used to describe the critical decision factors that affect demand: price, advertising, distribution, and product quality. Let the variable x represent total marketing effort. A typical model that is used to predict demand as a function of total marketing effort is D = ax^b. Suppose that a is a positive number. Different models result from varying the constant b. Sketch the graphs of these models for b=0, b=1, 0<b<1, b<0, and b>1. Match the graph to the model above.
b=0 - Straight horizontal line b=1 - Increasing line 0<b<1 - curving up with diminishing returns (like left side of n) b<0 - curving down with diminishing returns (like left side of u) b>1 - curving up exponentially (like right side of u)
What does the model for b>1 tell about the relationship between demand and marketing effort?
As marketing efforts increase, demand increases at an increasing rate.
What does the model for 0<b<1 tell about the relationship between demand and marketing effort?
As marketing efforts increase, demand increases with diminishing returns.
What does the model for b=1 tell about the relationship between demand and marketing effort?
As marketing effort increases, demand increases linearly.
What does the model for b<0 tell about the relationship between demand and marketing effort?
As marketing efforts increase, demand decreases with diminishing returns.
Discuss how one might use business analytics in their personal life. Select all that apply. A. A golf player might use statistics to help to diagnose problems and improve their game. B. An automobile owner can predict when the next maintenance will be due by recording things such as the miles driven and gas mileage. This would help them budget accordingly. C. A store might keep track of inventory and use it to decide what items are in demand. D. A reporter could analyze social media posts to see what types of people are more likely to share unverified news stories.
All of the above (A,B,C, and D)
A supermarket has been experiencing long lines during peak periods of the day. The problem is noticeably worse on certain days of the week, and the peak periods sometimes differ according to the day of the week. There are usually enough workers on the job to open all cash registers. The problem the supermarket manager faces is knowing when to call some of the workers who are stocking shelves up to the front to work the checkout counters. Use this information to answer the given questions. How might business analytics help the supermarket manager? Select all that apply. A. The manager can use analytics to schedule the minimum necessary or predicted number of workers for cash registers in order to ensure that none of the cash registers are idle. B. A model might be developed to find the number of checkout counters to open to ensure a reasonable wait time or maximize customer throughput. C. A model can be developed to forecast customer demand for a set amount of time in the future. D. The manager can use analytics by examining historical data on customer flow during each hour of each day of the week and month. E. Business analytics can help to predict customer demand at the checkout counters and determine the appropriate number to have open.
B, C, D, and E all relate to the problem A does not relate to the problem as minimizing workers and idling registers are not related to calling workers to work registers.
A human resource manager needs to understand whether the company's current employee mix has the skills and capabilities needed to achieve the goals laid out by a new strategic plan. Which analytics tools would most likely be used for this scenario? A. Prescriptive B. Descriptive C. Predictive
B. Descriptive (use current/historical data to ifnd relationships/trends)
What assumptions are implied? Are they reasonable? Select all that apply. A. Demand cannot be measured. This assumption is not reasonable. B. Marketing effort and demand are not related. This assumption is not reasonable. C. Marketing effort and demand can both be clearly measured. This assumption is reasonable. D. The model applies to past observations for marketing effort and demand. This assumption is reasonable. E. There are no other factors that affect demand. This assumption is not reasonable.
C and E A - Demand can be measured B - Marketing effort and demand are related D - No idea why it is wrong
The chief financial officer for a small manufacturing firm would like to estimate the net profit that the firm could expect over the next three years. Which analytics tools would most likely be used for this scenario? A. Descriptive B. Prescriptive C. Predictive
C. Predictive (estimate future profit)
A baseball team would like to set ticket prices for different sections in its stadium to attract the highest number of fans throughout the season. Which analytics tools would most likely be used for this scenario? A. Descriptive B. Predictive C. Prescriptive
C. Prescriptive (implied best prices for each section)
A disaster relief agency needs to allocate its budget for the next year among various relief efforts and programs. Which analytics tools would most likely be used for this scenario? A. Predictive B. Descriptive C. Prescriptive
C. Prescriptive (implied best way to allocate funds among different programs)
One of the earliest operations research groups during World War II was conducting a study on the optimum utilization of Spitfire and Hurricane aircraft during the Battle of Britain. Whenever one of these planes returned from battle, the locations of the bullet holes on it were carefully plotted. By repeatedly recording these data over time, and studying the clusters of data, the group was able to estimate the regions of the aircraft most likely to be hit by enemy gunfire, with the objective of reinforcing these regions with special armor. What difficulties are involved with this study? A. The locations of bullet holes may change if the enemy changes tactics. B. Reinforcing these regions of the aircraft would make it more difficult to record locations of bullet holes in the future. C. The locations of bullet holes may not be precise, due to the need for repairing aircraft so they could be sent up again. D. The study was only observing planes that returned safely. Planes that were shot down could not be analyzed.
D. The study was only observing planes that returned safely. Planes that were shot down could not be analyzed.
The best decision is the (manufacturing or outsourcing) because it has the (higher variable cost, lower variable cost, higher fixed cost, lower fixed cost, higher total cost, or lower total cost).
Outsourcing because lower total cost
Suppose that a manufacturer can produce a part for $11.00 with a fixed cost of $2,000. Alternately, the manufacturer could contract with a supplier in Asia to purchase the part at a cost of $12.00, which includes transportation. If the anticipated production volume is 1,000 units, compute the total cost of manufacturing.
The total cost of manufacturing is $13000. 2000+(11*1000)
Suppose that a manufacturer can produce a part for $11.00 with a fixed cost of $2,000. Alternately, the manufacturer could contract with a supplier in Asia to purchase the part at a cost of $12.00,which includes transportation. If the anticipated production volume is 1,000 units, compute the total cost of outsourcing.
The total cost of outsourcing is $12000. (12*1000)