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essentials business analytics
Questions and Answers of
Essentials Business Analytics
Approximately 50,000 new titles, including new editions, are published each year in the United States, giving rise to a $25 billion industry in 2001. In terms of percentage of sales, this industry
When you think of political persuasion, you may think of the effortsthat political campaigns undertake to persuade you that their candidate is betterthan the other candidate. In truth, campaigns are
In late 2013, the taxi company Yourcabs.com in Bangalore, India, was facing a problem with the drivers using their platform—not all drivers were showing up for their scheduled calls. Drivers would
CRISA is an Asian market research agency that specializes in tracking consumer purchase behavior in consumer goods (both durable and nondurable).In one major research project, CRISA tracks numerous
Exeter, Inc., is a catalog firm that sells products in a number of different catalogs that it owns. The catalogs number in the dozens but fall into nine basic categories:1. Clothing 2. Housewares 3.
Forecasting transportation demand is important for multiple purposes such as staffing, planning, and inventory control. The public transportation system in Santiago de Chile has gone through a major
You are a data scientist recently hired by Universal Bank, a mid-sized bank in the southern United States. Most of your work to this point has involved pulling reports fromdatabases, but now you have
Impact of September 11 on Air Travel in the United States. The Research and Innovative Technology Administration’s Bureau of Transportation Statistics conducted a study to evaluate the impact of
Performance on Training and Holdout Data. Two different models were fit to the same time series. The first 100 time periods were used for the training set, and the last 12 periods were treated as a
Forecasting Department Store Sales. The file DepartmentStoreSales.csv contains data on the quarterly sales for a department store over a six-year period (data courtesy of Chris Albright).a. Create a
The file ApplianceShipments.csv contains the series of quarterly shipments (in million dollars) of US household appliances between 1985 and 1989 (data courtesy of Ken Black).a. Create a
Canadian Manufacturing Workers Workhours. The time plot in Figure 17.9 describes the average annual number of weekly hours spent by Canadian manufacturing workers (data are available in
Souvenir Sales. The file SouvenirSales.csv contains monthly sales for a souvenir shop at a beach resort town in Queensland, Australia, between 1995 and 2001. [Source: Hyndman and Yang (2018).] Back
Shampoo Sales. The file ShampooSales.csv contains data on the monthly sales of a certain shampoo over a three-year period. [Source: Hyndman and Yang (2018).a. Create a well-formatted time plot of the
Analysis of Canadian Manufacturing Workers’ Workhours. The time plot in Figure 18 . 22 describes the average annual number of weekly hours spent by Canadian manufacturing workers
Toys “R” US Revenues. Figure 18 . 23 is a time plot of the quarterly revenues of Toys “R” US between 1992 and 1995 (thanks to Chris Albright for suggesting the use of these data, which are
Figure18 . 25 shows the series of Walmart daily closing prices between February 2001 and February 2002 (thanks to Chris Albright for suggesting the use of these data, which are publicly available,
Shipments of Household Appliances. The time plot in Figure 18 . 31 shows the series of quarterly shipments (in million dollars) of US household appliances between 1985 and 1989 (dataare available in
Australian Wine Sales. Figure 18 .32 shows time plots of monthly sales of six types of Australian wines (red, rose, sweet white, dry white, sparkling, and fortified) for 1980–1994. [Data are
Relation Between Moving Average and Exponential Smoothing. Assume that we apply a moving average to a series, using a very short window span. If we wanted to achieve an equivalent result using simple
For a given time series of sales, the training set consists of 50 months. The first five months’ data are shown below:a. Compute the sales forecast for January 1999 based on a moving average with w
The table below shows the optimal smoothing constants from applying exponential smoothing to data, using automated model selection [Note: Such automated selection can be performed in RapidMiner with
The time plot in Figure 19 . 17 shows the series of quarterly shipments (in million dollars) of US household appliances between 1985 and 1989 (data are available in ApplianceShipments.csv, data
The time plot in Figure 19.18 describes monthly sales of a certain shampoo over a three-year period. [Data are available in ShampooSales.csv, Source: Hyndman and Yang (2018).]Which of the following
Figure 19.19is a time plot of quarterly natural gas sales (in billions of BTU) of a certain company, over a period of four years (data is available in NaturalGasSales.csv, data courtesy of George
Figure 19.20 shows time plots of monthly sales of six types of Australian wines (red, rose, sweet white, dry white, sparkling, and fortified) for 1980– 1994. [Data are available in
Consider an undirected network for individuals A, B, C, D, and E. A is connected to B and C. B is connected to A and C. C is connected to A, B, and D. D is connected to C and E. E is connected to
Network Density and Size. Imagine that two new nodes are added to the undirected network in the previous exercise.a. By what percent has the number of nodes increased?b. By what percent has the
Link Prediction. Consider the network shown in Figure 20.13.a. Using the number of common neighbors score, predict the next link to form (that is, suggest which new link has the best chance of
Consider the case of a website that caters to the needs of a specific farming community and carries classified ads intended for that community. Anyone, including robots, can post an ad via a web
In this problem, you will use the data and scenario described in this chapter’s example. The task is to cluster the auto posts.a. Following the example in this chapter, preprocess the documents,
In this exercise, you will recreate some of the analysis done in this chapter for the COMPAS recidivism case, using the data in COMPAS-clean.csv. After partitioning the data into training and
Classifying Phrases as Toxic. In 2017, Google’s Jigsaw research group launched Perspectives, a project that developed a classification algorithm to identify toxic speech on public social media
Predictive Policing. Predpol is an algorithm that predicts crime occurrence by location in nearly real time, using historical data on crime type, crime location, and crime date/time as predictors.
Bank Product Marketing This problem uses the dataset bank-bias-data.csv. 13 A bank with operations in the United States and Europe is seeking to promote a new term deposit product with a direct
Calculating Distance with Categorical Predictors. This exercise with a tiny dataset illustrates the calculation of Euclidean distance and the creation of binary dummies. The online education company
Personal Loan Acceptance. Universal Bank is a relatively young bank growing rapidly in terms of overall customer acquisition. The majority of these customers are liability customers (depositors) with
The file UniversalBank.csv contains data on 5000 customers of Universal Bank. The data include customer demographic information (age, income, etc.), the customer’s relationship with the bank
Competitive Auctions on eBay.com. The file eBayAuctions.csv contains information on 1972 auctions that transacted on eBay.com during May–June 2004. The goal is to use these data to build a model
Predicting Delayed Flights. The file FlightDelays.csv contains information on all commercial flights departing the Washington, DC area and arriving at New York during January 2004. For each flight,
Predicting Prices of Used Cars (Regression Trees). The file ToyotaCorolla.csv contains the data on used cars (Toyota Corolla) on sale during late summer of 2004 in the Netherlands. It has 1436
Financial Condition of Banks. The file banks.csv includes data on a sample of 20 banks. The “Financial Condition” column records the judgment of an expert on the financial condition of each bank.
Identifying Good System Administrators. A management consultant is studying the roles played by experience and training in a system administrator’s ability to complete a set of tasks in a
Sales of Riding Mowers. A company that manufactures riding mowers wants to identify the best sales prospects foran intensive sales campaign. In particular, the manufacturer is interested in
Competitive Auctions on eBay.com. The file eBayAuctions.csv contains information on 1972 auctions transacted on eBay.com during May–June 2004. The goal is to use these data to build a model that
Credit Card Use. Consider the hypothetical bank data in Table 11. 4 on consumers’ use of credit card credit facilities. Create a small worksheet in Excel to illustrate one pass through a simple
Neural Net Evolution. A neural net typically starts out with random values for bias and weights; hence, it produces essentially random predictions when presented with its first case. What is the key
Car Sales. Consider the data on used cars (ToyotaCorolla.csv) with 1436 records and details on 38 attributes, including Price, Age, KM, HP, and other specifications. The goal is to predict the price
Direct Mailing to Airline Customers. East–West Airlines has entered into a partnership with the wireless phone company Telcon to sell the latter’s service via direct mail. The file
Personal Loan Acceptance. Universal Bank is a relatively young bank growing rapidly in terms of overall customer acquisition. The majority of these customers are liability customers with varying
Identifying Good System Administrators. A management consultant is studying the roles played by experience and training in a system administrator’s ability to complete a set of tasks in a
eBay Auctions—Boosting and Bagging. The file eBayAuctions.csv contains information on 1972 auctions that transacted on eBay.com during May–June 2004. The goal is to use these data to build
Predicting Delayed Flights (Boosting). The file FlightDelays.csv contains information on all commercial flights departing the Washington, DC area and arriving at New York during January 2004. For
Hair Care Product—Uplift Modeling. This problem uses the dataset in Hair-CareProduct.csv, courtesy of SAS. In this hypothetical case, a promotion for a hair care product was sent to some members
Satellite Radio Customers. An analyst at a subscription-based satellite radio company has been given a sample of data from their customer database, with the goal of finding groups of customers who
Identifying Course Combinations. The Institute for Statistics Education at Statistics.com offers online courses in statistics and analytics and is seeking information that will help in packaging and
Cosmetics Purchases. The data shown in Table 15 .12 and the output in Figure 15 . 9 are based on a subset of a dataset on cosmetic purchases (Cosmetics.csv) at a large chain drugstore. The store
Course Ratings. The Institute for Statistics Education at Statistics.com asks students to rate a variety of aspects of a course as soon as the student completes it. The Institute is contemplating
An equities analyst is studying the pharmaceutical industry and would like your help in exploring and understanding the financial data collected by her firm. Her main objective is to understand the
The file EastWestAirlinesCluster.csv contains information on 3999 passengers who belong to an airline’s frequent flier program. For each passenger, the data include information on their mileage
Predicting Boston Housing Prices. The file BostonHousing.csv contains information collected by the US Bureau of the Census concerning housing in the area of Boston, Massachusetts. The dataset
Predicting Software Reselling Profits. Tayko Software is a software catalog firm that sells games and educational software. It started out as a software manufacturer and then added third-party titles
The following problem takes place in the United States in the late 1990s, when many major US cities were facing issues with airport congestion, partly as a result of the 1978 deregulation of
Predicting Prices of Used Cars. The file ToyotaCorolla.csv contains data on used cars (Toyota Corolla) on sale during late summer of 2004 in the Netherlands. It has 1436 records containing details on
Assuming that machine learning techniques are to be used in the following cases, identify whether the task required is supervised or unsupervised learning.a. Deciding whether to issue aloan to an
Describe the difference in roles assumed by the validation partition and the holdout partition.
Consider the sample from a database of credit applicants in Table 2.5. Comment on the likelihood that it was sampled randomly and whether it is likely to be a useful sample. OBS CHECK DURATION
Consider the sample from a bank database shown in Table 2.6; it was selected randomly from a larger database to be the training set. Personal Loan indicates whether a solicitation for a personal loan
Using the concept of overfitting, explain why when a model is fit to training data, zero error with those data is not necessarily good.
In fitting a model to classify prospects as purchasers or nonpurchasers, a certain company drew the training data from internal data that include demographic and purchase information. Future data to
A dataset has 1000 records and 50 attributes with 5% of the values missing, spread randomly throughout the records and attributes. An analyst decides to remove records with missing values. About how
Normalize the data in Table 2.7, showing calculations. Age Income ($) 25 49,000 56 156,000 65 99,000 32 192,000 41 49 39,000 57,000
Two models are applied to a dataset that has been partitioned. Model A is considerably more accurate than model B on the training data, but slightly less accurate than model B on the validation
The dataset ToyotaCorolla.csv contains data on used cars on sale during the late summer of 2004 in the Netherlands. It has 1436 records containing details on 38 attributes, including Price, Age,
Sort the West Roxbury data by YR BUILT and report any anomalies. Discuss the implications for the analysis done in this chapter, and possible steps to take
Shipments of Household Appliances: Line Charts. The file ApplianceShipments.csv contains the series of quarterly shipments (in millions of dollars) of US household appliances between 1985 and
Sales of Riding Mowers: Scatter Plots. A company that manufactures riding mowers wants to identify the best sales prospects for an intensive sales campaign. In particular, the manufacturer is
Laptop Sales at a London Computer Chain: Bar Charts and Boxplots. The file LaptopSalesJanuary2008.csv contains data forall sales of laptops at a computer chain in London in January 2008. This is a
Laptop Sales at a London Computer Chain: Interactive Visualization. The next exercises are designed for using an interactive visualization tool. The file LaptopSales.csv is a comma-separated file
The dataset on American college and university rankings (available from www.dataminingbook.com) contains information on 1302 American colleges and universities offering an undergraduate program. For
Chemical Features of Wine. Figure 4.14 shows the PCA output on data (nonnormalized) in which the attributes represent chemical characteristics of wine, and each case is a different wine.a. The data
A machine learning process has been applied to a transaction dataset and has classified 88 records as fraudulent (30 correctly so)and 952 as non-fraudulent (920 correctly so). Construct the confusion
Suppose that this process has an adjustable threshold (cutoff) mechanism by which you can alter the proportion of records classified as fraudulent. Describe how moving the threshold up or down would
Consider Figure 5.15, the decile lift chart for the transaction data model, applied to new data.a. Interpret the meaning of the first and second bars from the left.b. Explain how you might use this
FiscalNote is a startup founded by a Washington, DC entrepreneur and funded by a Singapore sovereign wealth fund, the Winklevoss twins of Facebook fame, and others. It uses machine learning
A large number of insurance records are to be examined to develop a model for predicting fraudulent claims. Of the claims in the historical database, 1% were judged to be fraudulent. A sample is
A firm that sells software services has been piloting a new product and has records of 500 customers who have either bought the services or decided not to. The target value is the estimated profit
Construct a spreadsheet that makes the calculations required to analyze the decision in the WGT example. Include in the spreadsheet the calculation of the expected profit for each action and the
What modules will we need to build?The four short cases we have analyzed in this chapter (Retirement Planning, Draft TV Commercials, Icebergs for Kuwait, and Racquetball Racket) are reproduced with
What are the key relationships in the problem? Draw their graphs.The four short cases we have analyzed in this chapter (Retirement Planning, Draft TV Commercials, Icebergs for Kuwait, and Racquetball
What are the parameters of the problem?The four short cases we have analyzed in this chapter (Retirement Planning, Draft TV Commercials, Icebergs for Kuwait, and Racquetball Racket) are reproduced
Refer to the ERP Decision case. Design a spreadsheet that will assist the Board in evaluating the net benefits of implementing the ERP system.The above exercises refer to the cases in the back of
Refer to the Retirement Planning case. Review the problem statement and influence chart that were generated for this case in conjunction with the corresponding exercise in Chapter 2. (If this has not
Refer to the Draft TV Commercials case. Review the problem statement and influence chart that were generated for this case in conjunction with the corresponding exercises in Chapter 2. (If this has
Refer to the Icebergs for Kuwait case. Review the problem statement and influence chart that were generated for this case in conjunction with the corresponding exercises in Chapter 2. (If this has
Refer to the Racquetball Racket case. Review the problem statement and influence chart that were generated for this case in conjunction with the corresponding exercises in Chapter 2. (If this has not
Refer to the ERP Decision case. From the corresponding exercise in Chapter 3, review the design of a spreadsheet that will assist the Board in understanding the likely costs and benefits of
Refer to the Retirement Planning case. From the corresponding exercise in Chapter 3, review the design of a spreadsheet for this problem.a. Develop a base case. You may create any data you need for
Refer to the Draft TV Commercials case. From the corresponding exercise in Chapter 3, review the design of a spreadsheet for this problem.a. Develop a base case. You may create any data you need for
Refer to the Icebergs for Kuwait case. From the corresponding exercise in Chapter 3, review the design of a spreadsheet for this problem.a. Develop a base case. You may create any data you need for
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