ISE Data Analytics For Accounting 3rd Edition Ryan A. Teeter, Vernon Richardson, Katie L. Terrell - Solutions

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Suppose that your friend Jamie calls you in a panic after testing positive for HIV. Jamie is understandably upset because doctors assure her that the OraQuick Advance Rapid test is nearly 100%accurate. Below is information about the HIV test from research involving over 12,000 subjects by the
Can you think of an example of an ‘impossible’ result in academic papers that you have read or data that you have used? It might be as a result of (a) Simpson’s Paradox, (b) a misunderstanding of Bayes’ Theorem, or (c) something else.
The data in Table 11.2 is made up admissions data from the paper on UC Berkeley’s admissions rates (Bickel et al., 1975).Do you think that there is gender discrimination going on at this university? Why, or why not?
Think of a research question in the social sciences. Now search for published research on this topic. Evaluate how strong the evidence exists testing your idea. Do the findings point in a similar direction?Have they been replicated? Do they use different methods (e.g.triangulation)? What new data
Design an experiment to test a research question in the social sciences. First, identify the specific causal relationship that you are testing. What is the counterfactual? Next, explain the type of design you are using (e.g. between-subjects, within-subjects or mixed designs). Where would you
Google Correlate (https://www.google.com/trends/correlate) allows you to search patterns over time and location, many of which are spurious correlations. Use the interactive tool to see what you can discover. Just remember that correlations only show linear associations, and that the link could be
One way to improve your ability to spot correlations is to play a fun, interactive game called Guess the Correlation developed by Omar Wagih. Originally designed to collect data on people’s ability to identify patterns from scatterplots, it’s also a great way of learning.The game works by
Take a league table used in the public sector and look at how it is constructed. How might you improve it so it tells you what you really want to know?
Should league tables be banned? Discuss in relation to schools, universities or another type of league table in the public sector.
Twenty-nine independent research teams were given an identical dataset and tasked with investigating a research question about racial bias in sports: ‘Are football players with darker skin tone more likely than those with lighter skin tone to receive red cards from referees?’ The results of
The data journalism website FiveThirtyEight (or 538, for the number of votes in the US Electoral College) has an interactive tool to help you understand p-hacking. Visit the website to see if you can‘Hack Your Way To Scientific Glory’ (https://projects.fivethirtyeight.com/p-hacking/) by getting
Investigate how the margin of sampling error (MoSE) from an opinion poll is affected by changes to the size of the sample and desired confidence level. Find an opinion poll reported in the news media by visiting a specific news site or searching for the word‘survey’ or ‘poll’. Calculate the
Without looking at the example earlier in this chapter (or doing so only briefly) sketch out an example of the modifiable areal unit problem on a piece of paper and compare your results with others.
Can you think an example where the ecological fallacy might benefit an individual? (Hint: let’s imagine you are only eligible for a scholarship if you live in a poor area.)
Name some uses of geodemographics, and write down a list of possible problems with this approach to understanding people and places (e.g. privacy, erroneous assumptions).
What are some of the problems associated with mapping election outcomes where a map is depicted using two colours as an either/or result (such as ‘yes’/‘no’ or ‘Republican’/‘Democratic’)?
If you had a dataset with a million geographic points in it, each one representing a crime in a particular city, how might you begin to understand the underlying spatial pattern of the points?
It is said that all maps lie in some way or another: do you agree?
How long is the coastline of Great Britain? This is not a trick question, and there is only really one correct answer!
How can a political party with far fewer votes than another party end up winning an election? There are in fact a variety of ways, but can you explain how this might happen from a geographical perspective, using a basic diagram?
Is Greenland bigger than Africa? If not, why does it appear that way on some maps? Try to answer this question with reference to map projections.
Return to your news source close at hand. This time, find a story that includes numbers but doesn’t include a graph. Think about how this might be addressed. What kinds of graphs might be included in this story? Would they help understanding, or would they just make the story more confusing?
Find a news source close at hand – it could be a physical newspaper or magazine, it could be an online news source, it could be a broadcaster (except this won’t work if it’s radio). Starting at the top, keep skimming through until you find a graph; on most days of the year, it shouldn’t
Is the elected body in your country (e.g. a parliament)representative in terms of socio-demographic characteristics of the adult population in your country? Compare proportions of populations by gender, age group, qualification levels, ethnic background, etc., in the elected body to proportions of
How would you construct a probability-based panel in a country which does not have one? The aim is to give all members of the country’s population the same chance to be selected. First, look at the webpages of some of the panels described in Box 4.2. Then, identify which sampling frame would give
Investigate the coverage of the electoral register in the UK as a sampling frame for a survey of the general, adult population.Specifically reflect on the following:1. Who has a right to vote in the UK?2. How does it differ for different elections? Who, in terms of nationalities, is on the
Select a question from the latest wave of The European Social Survey (ESS, www.europeansocialsurvey.org/) and create a social media poll (e.g. embedded in Twitter). Ask your networks to forward your poll. Compare your results of the ESS results for your country or the whole of Europe. What have the
Go to the webpages of the surveys listed below. Define the following aspects of the surveys: study units, target population, sampling frame, sample size and response rate.• European Quality of Life Survey: https://www.eurofound.europa.eu/surveys/european-quality-of-life-surveys• The Australian
Find a news story that’s been published online today where the headline features a number, and read the story in full, also making a note of any numbers the story might include. First, rewrite the headline so that the number sounds as dramatic as possible, using as many techniques from this
Pick one of the headlines from the Daily Express listed at the start of the chapter, and search for the original story online. If you’re able to find it (and if you’re not, try a different one), read the original story.Having done so, is the number in the headline a big number? Why, or why not?
Suppose we want to put the following data into the appropriate income statement format:Revenues 50000 Expenses Cost of Goods Sold 20000 Research and Development Expenses 10000 Selling, General, and Administrative Expenses 10000 Interest Expense 3000 Required:1.. Add a comma as a 1000 separator for
Write your fifth question and provide an answer based on your analysis.
Write your fourth question and provide an answer based on your analysis.
Write your third question and provide an answer based on your analysis.
Write your second question and provide an answer based on your analysis.
Write your first question and provide an answer based on your analysis.
What have you learned from completing the analyses in Question Sets 1, 2, and 3?
Brainstorm at least four other data items (e.g., economy, type of customer, etc.) that would be helpful in predicting the next year’s percentage of sales returned.
What are the drawbacks of using one year of data to forecast a future year?
Looking at your regression output, was the relationship between 2014 and 2015 percentage of sales returned significant? How can you tell?
What unforeseen factors could impact seasonality that managers would need to consider instead of solely relying on the results from their predictive analytics?
Does the R Square give you confidence that this is a strong predictive model?
What is the coefficient for 2014?
What is the R Square?
How does it help companies to rely on seasonality and past performance if those items exist in their data?
Click through each state and determine which state has the most variability in percentage of sales (do not consider “U,” which stands for undefined)?
Based on the line chart, does 2014 seem to be useful in predicting 2015’s percentage of sales returned?
Based on these line charts, does it seem more beneficial to predict percentage of sales returned on a state-bystate basis or in aggregate form?
Write your fifth question and provide an answer based on your analysis.
Write your fourth question and provide an answer based on your analysis.
Write your third question and provide an answer based on your analysis.
Write your second question and provide an answer based on your analysis.
Write your first question and provide an answer based on your analysis.
If there is at least one state that does not fit the pattern of having a higher average percentage of returned sales in January than the rest of the year, what would your next diagnostic analysis steps be to determine why there is an anomaly?
Do you expect January to be the month with the highest average return of sales for online transactions? Why?
What is the average percentage of returned sales for Wyoming (WY) non-holiday transactions?
What is the average percentage of returned sales for Iowa (IA) holiday transactions?
What is the average percentage of returned sales for non-holiday online transactions?
Provide three insights about the percentage of returned sales that you can derive from the hypothesis test in Part 1 and/or the dashboards you created in Part 2.
What is the average percentage of returned sales for the non-holiday time period?
Microsoft Excel Only: Based on the p-values (or the tstatistic and critical values), are the returns as a percentage of sales in January significantly greater, less than, or the same as the returns as a percentage of sales for the rest of the year?
What would your recommendations be to Dillard’s regarding the differences in January returns and the rest of the year?
What additional data would be interesting to add to your diagnostic analysis about the percentage of returned sales?
If the difference is statistically significant, how would you display the results visually to Dillard’s?
Why does the statistical significance matter? Would your analysis and recommendations to Dillard’s be different if the difference is not statistically significant?
Write your fifth question and provide an answer based on your analysis.
Write your fourth question and provide an answer based on your analysis.
Write your third question and provide an answer based on your analysis.
Write your second question and provide an answer based on your analysis.
Write your first question and provide an answer based on your analysis.
Use the slicer (Excel) or the visualization filter(Tableau) to assess for seasonality in percentage of returned sales for online transactions versus in-person transactions. What changes do you observe? Why do you think the pattern is different?
Why did this exercise have you assess average percentage of returned sales and not sum, which is the default aggregate in both Excel and Tableau?
What is the average percentage of returned sales for Oklahoma (OK)?
What is the average percentage of returned sales for inperson transactions?What is the average percentage of returned sales for online transactions?Which one has a higher average percentage of returned sales?
Which month has the lowest average percentage of returned sales?
After executing these queries you can confirm whether your assumptions that you made in the thought questions were accurate. Which month has the highest average percentage of returned sales?
Do you expect percentage of returned sales to vary much across states? Why?
Do you think the trend over time of average percentage of returned sales for online transactions is similar to or different from the average percentage of returned sales for in-person transactions? Why?
Which month do you expect average percentage of returned sales to be the highest? The lowest? Why?
Predict returned sales in future periods using predictive analytics.
Illustrate hypothesis testing using diagnostic analytics to compare and contrast sales returns around the holiday season.
Analyze returned sales to find explanatory (independent)variables using descriptive and exploratory analytics.
Write your fifth question and provide an answer based on your analysis.
Write your fourth question and provide an answer based on your analysis.
Write your third question and provide an answer based on your analysis.
Write your second question and provide an answer based on your analysis.
Write your first question and provide an answer based on your analysis.
While you still have your auditor hat on, what are some additional analyses you could perform to understand whether the purchase process is being followed or controls are functioning properly?
Why aren’t the other purchases suspicious?
How might an outlier be used to focus the auditors on high-risk transactions?
Looking at the missing orders visual, which of the invoices received warrants further investigation by the auditors?
Looking at the outliers visual, which supplier(s) had an abnormally high dollar amount of purchases?
What statistical tools can the company use to diagnose behavior that is outside of normal behavior?
What do you consider “abnormally high”? Are these suspicious?
Would management want these numbers to be higher or lower?
How about erroneous payments as a percentage of total payments?
In your opinion, what would be an appropriate benchmark for the average number of discount dollars lost as a percentage of available discount dollars?
Are there any KPIs that would be appropriate here?
What are some analyses you could perform that would provide insight into how efficiently your company is processing payments to suppliers?
What risks are present if you take too long to pay our accounts payable?

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ISE Data Analytics For Accounting 3rd Edition Ryan A. Teeter, Vernon Richardson, Katie L. Terrell - Solutions

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