Introducing Hr Analytics With Machine Learning Empowering Practitioners Psychologists And Organizations 1st Edition Christopher M Rosett ,Austin Hagerty - Solutions

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7. Example 1.4 in Chapter 1 described a scenario for new product sales that can be characterized by a formula called a Gompertz curve: S = aebect. Develop a spreadsheet for calculating sales using this formula for t = 0 to 160 in increments of 10 when a = 20000, b = -10, and c = -0.04.
6. A pharmaceutical manufacturer has projected net profits for a new drug that is being released to the market over the next five years:Year Net Profit 1 $(675,000,000)2 $(445,000,000)3 $(175,000,000)4 $125,000,000 5 $530,000,000 Use a spreadsheet to find the net present value of these cash flows
5. A manager needs to identify some information from the Purchase Orders Excel file but has only the order number. Modify the Excel file to use the VLOOKUP function to find the item description and cost per order for the following order numbers: A1567, C8854, and A0207.
4. The Excel file Credit Risk Data provides information about 425 bank customers who had applied for loans. The data include the purpose of the loan, checking and savings account balances, number of months as a customer of the bank, months employed, gender, marital status, age, housing status and
3. The Excel file President’s Inn Guest Database provides a list of customers, rooms they occupied, arrival and departure dates, number of occupants, and daily rate for a small bed-and-breakfast inn during one month.6 Room rates are the same for one or two guests; however, additional guests must
2. The Excel file Store and Regional Sales Database provides sales data for computers and peripherals showing the store identification number, sales region, item number, item description, unit price, units sold, and month when the sales were made during the fourth quarter of 2011.5 Modify the
1. The Excel file Science and Engineering Jobs shows the number of jobs in thousands in the year 2000 and projections for 2010 from a government study. Use the Excel file to compute the projected increase from the 2000 baseline and also the percentage increase for each occupational category.
• Use Excel features and spreadsheet engineering to ensure the quality of your spreadsheets.
• Use basic and advanced Excel functions.
• Use Excel features such as split screen, paste special, show formulas, and displaying grid lines and headers in your applications.
• Copy formulas from one cell to another or to a range of cells.
• Apply relative and absolute addressing in Excel formulas.
• Write correct formulas in an Excel worksheet.
• Find buttons and menus in the Excel 2010 ribbon.
14. The demand for airline travel is quite sensitive to price. Typically, there is an inverse relationship between demand and price; when price decreases, demand increases and vice versa. One major airline has found that when the price (P) for a round trip between Chicago and Los Angeles is $600,
13. A manufacturer of mp3 players is preparing to set the price on a new model.Demand is thought to depend on the price and is represented by the model D 2,000 3P The accounting department estimates that the total costs can be represented by C 5,000 4D Develop a model for the total profit.
12. Automobiles have different fuel economies (mpg), and commuters drive different distances to work or school. Suppose that a state Department of Transportation(DOT) is interested in measuring the average monthly fuel consumption of commuters in a certain city. The DOT might sample a group of
11. 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
10. Return on investment (ROI) is computed in the following manner: ROI is equal to turnover multiplied by earnings as a percent of sales. Turnover is sales divided by total investment.Total investment is current assets (inventories, accounts receivable, and cash)plus fixed assets. Earnings equal
9. Suppose that a manufacturer can produce a part for $9.00 with a fixed cost of$4,000. The manufacturer can contract with a supplier in Asia to purchase the part at a cost of $12.00, which includes transportation.a. If the anticipated production volume is 1,000 units, compute the total cost of
8. Four key marketing decision variables are price (P), advertising (A), transportation(T), and product quality (Q). Consumer demand (D) is influenced by these variables. The simplest model for describing demand in terms of these variables is D k pP aA tT qQ where k, p,a, t, and q are
7. A bank developed a model for predicting the average checking and savings account balance as balance 17,732 367 age 1300 years education 0.116 household wealth.a. Explain how to interpret the numbers in this model.b. Suppose that a customer is 36 years old, is a college graduate (so
6. A survey handed out to individuals at a major shopping mall in a small Florida city in July asked the following:• gender• age• ethnicity• length of residency• overall satisfaction with city services (using a scale of 1–5, going from poor to excellent)• quality of schools (using a
5. Identify each of the variables in the Excel file Credit Approval Decisions as categorical, ordinal, interval, or ratio.
4. Classify each of the data elements in the Sales Transactions database (Figure 1.1)as categorical, ordinal, interval, or ratio data.
3. Suggest some metrics that a manager of a fast-food restaurant, such as McDonald’s or Chipotle, might want to collect. Describe how the manager might use the data to facilitate better decisions.
2. Suggest some metrics that a hotel might want to collect about their guests. How might these metrics be used with business analytics to support decisions at the hotel?
1. 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
• List and explain the steps in the problem-solving process.
• Explain the difference between a deterministic and stochastic decision model.
• Define the terms optimization, objective function, and optimal solution.
• Explain the difference between uncertainty and risk.
• Use predictive models to compute model outputs.
• Use influence diagrams to build simple mathematical models.
• Define and provide an example of an influence diagram.
• Define and list the elements of a decision model.
• Explain the concept of a model and various ways a model can be characterized.
• Describe the four groups of data classification, categorical, ordinal, interval, and ratio, and provide examples of each.
• Explain the difference between a discrete metric and continuous metric, and provide examples of each.
• Define a metric and explain the concepts of measurement and measures.
• Explain the difference between a data set and a database.
• State examples of how data are used in business.
• Explain and provide examples of descriptive, predictive, and prescriptive analytics.
• Summarize the evolution of business analytics and explain the concepts of business intelligence, operations research and management science, and decision support systems.
• State some typical examples of business applications in which analytics would be beneficial.
• Explain why analytics is important in today’s business environment.
The following table displays the possible payoffs from a particular investment and the indifference probabilities for an investor.a. Assume that the lowest payoff is assigned a utility of 0 and that the greatest payoff is assigned a utility of 10.Use these values to calculate utilities for each of
Refer to Problem 24.Find the second-best solution. How does it compare to the optimal solution found in Problem 24? Why might the second-best solution be preferred?Problem 24In this problem, we revisit the Martin-Beck plant location problem described in Problem 10.The management of Martin-Beck has
King City Inc. manufactures machine tools. The production planner who oversees the production of two of King City’s machines needs to determine how many of each to produce this month. The two machines, TopLathe and BigPress, each require a certain common component. Each TopLathe requires 10 of
Discuss the current state of data legislation in your country and the world. Which countries have most recently created legislature to protect employees specifically?How do you expect that to impact HR Analytics functions of the future?
Provide two examples (not necessarily at work or in HR) where algorithms have replaced human decision-making. Choose one you think has benefitted society and one which has caused challenges. Discuss why for each.
Discuss a time when bias went unnoticed in the creation of a new process, assessment, or data model. Why was it missed? How was the bias discovered and remedied?
Think of a time when a change at a job did more harm than good. Explain what happened, and why the negative impact was missed.
Think of a time when an assessment or model did not measure what it was supposed to or did not measure it well. What happened? Why did the measurement miss the mark? What were some of the repercussions of the mismeasurement?
Define the construct chasm. Provide three examples of HR metrics which have large construct chasms and discuss how you might bridge the gap to measure them well.
Choose the three model maintenance techniques you think are the most important.Why did you choose them?
Choose three of the most important considerations during model deployment.Why are these more important than other considerations?
Explain the results review and how it is different from the business case.
How do feature engineering and data wrangling work together? Why is this relationship so important?
Explain the structure and importance of the Business Loop, the Data Loop, and the Tuning Loop.
What are some advantages of binning, lagging, and z-scores? Provide an example of when you might use each.
Choose two different data types and enumerate the advantages and challenges of each.
Name four different types of HR data systems. Explain how data is typically structured for that type of system.
What is the difference between validity and reliability? Create two examples of how each might manifest as a challenge in HR data.
Why is data quality a challenge with HR data? What are some ways to combat this challenge and what are the associated risks?
What are the three major ways an analytics project provides value to a stakeholder?Create an example for each.
What are the eight attributes necessary to frame the project? Why is each important?
Discuss what you think are the two most critical aspects of understanding the business and the two most critical aspects of understanding the data. How are they similar and how are they different? How are they interdependent?
Name and define the three A's of a machine learning projects and the two categories within each.
What Makes Machine Learning Projects Unique in HR
Name one benefit and one weakness of both Waterfall and Agile approaches to project management and how they apply to machine learning projects.
Explain the triple constraint. Why is it so important?
Create two examples of machine learning projects: (1) where project management is necessary and (2) where project management is not necessary. Explain what the differences in the projects are and why they should use different approaches.
Which of the attributes which make machine learning project unique is most impactful in HR? Why?
Name three of the seven reasons to do project management well you think are most important and explain why you think they are more important than the other four.
Choose two unsupervised methods.• Explain in general how they work.• Create a detailed example of how you might use each in an applied setting.
What is the difference between a measure of central tendency, a measure of variability, and a measure of relative position? Why might you use each?
Explain confirmation bias and how descriptive statistics can contribute to it.
Why are descriptive statistics so important?
Why are systematic samples so important in HR Analytics? Name and explain four major considerations when building systematic samples.
Explain the difference between independent and dependent variables. Create two examples of something to study and define which variables are independent and which are dependent.
Create operational definitions of three things you would like to measure. Include all component parts necessary to define the phenomena.
What is the difference between exploratory, constructive, and empirical research?Give examples of when you might use each.
Consider a challenge you have tried to solve at a job. Break the problem down into its component parts: how many problems were there in total and how did they relate to each other? Frame these distinct pieces into individual questions or problems to solve.
What is the difference between deductive and inductive reasoning? What is the value of each?
Why is standard deviation so important? Give two examples of how it might be used in an applied setting.
Why are distributions an important part of descriptive statistics? Provide two examples of common HR data which do not demonstrate normal distributions.
Choose three supervised methods.• Explain in general how they work.• Create a detailed example of how you might use each in an applied setting.
What is the difference between supervised and unsupervised learning? Which is more commonly used in HR?
What is overfitting? Why is it so important to watch out for?
Explain what transparency is and why it is usually so important in HR Analytics.
Name four major considerations for machine learning and explain why they are important.
What is the difference between machine learning and inferential statistics? Why does it matter?
How does the literal nature of computers limit them? How have advances in computing enabled machine learning to remove these limitations?
What are the three main functions of a traditional computer? What are the two metrics by which those functions are measured?
What is the difference between statistically significant and practically significant?Give two examples of when you might need each.
Create two examples of how you have (or might) use the scientific method at a company. Specifically, focus on what makes the approach scientific.
Create two examples of how you have (or might) use the scientific method at a company. Specifically, focus on what makes the approach scientific.
Discuss some pros and cons you see of integrating machine learning into an HR Analytics strategy.
How does machine learning stand to influence HR Analytics Ikigai?

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Introducing Hr Analytics With Machine Learning Empowering Practitioners Psychologists And Organizations 1st Edition Christopher M Rosett ,Austin Hagerty - Solutions

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