Please answer the following questions below: Answers are giving in the manuals. I just need to you to shorten and edit them where it is not word from word. You can put each answer in excel sheet Chapter 8: Question(s) 8-1, 8-8, 8-12, 8-15, 8-22, 8-26, 8-2

SOLUTIONS CHAPTER 8

Transforming Data into Evidence (Part 1)

COVERAGE OF LEARNING OBJECTIVES

Questions

8-1. Data are simply items of information.

8-2. Qualitative data cannot be objectively measured, such as observations (sights, sounds, and smells) and words (documents and interviews).

8-3. Quantitative data can be measured and expressed numerically, such as profit, weight, time, and age.

8-4. A forensic accountant seeks to identify data that are sufficient to support an expert opinion and are relevant to the specific objectives of an engagement.

8-5. The purpose of data analysis is to drill down to the essence or meaning of the information. This exposes specific insights that may not be apparent when the data are viewed as a whole.

8-6. Rule 702 of the Federal Rules of Evidence and Rule 201 of the AICPA’s Code of Professional Conduct influence the accumulation of sufficient relevant data in the following manner: Rule 702 sets forth a requirement that an opinion be based on sufficient facts or data derived from the use of reliable principles and methods. Rule 201 requires CPAs to obtain sufficient evidence to afford a reasonable basis for conclusions or recommendations.

8-7. There is a tenuous relationship between the complexity of a forensic accounting technique and its effectiveness. Indeed, more complex is not synonymous with more effective. Increased complexity poses challenges when presenting results to a jury or other untrained audiences.

8-8. Sufficient data means data of adequate quantity and quality to support the engagement opinion. Both quantity and quality are required, because greater quantities of poor data do not compensate for a lack of quality inherent in the data.

8-9. In forensic accounting, relevance is determined by the requirements of an engagement and must be substantive enough to make a fact more or less probable than would otherwise be the case.

8-10. The availability of data impacts the consideration of data sufficiency as it influences the method of analysis. For example, when data is limited, an indirect method might be employed, as opposed to the application of a direct method when available data is plentiful.

8-11. A standard of proof impacts the threshold of sufficiency, as the standard of beyond a reasonable doubt is a higher standard than a preponderance of the evidence (which requires a reasonable degree of professional certainty, implying > 50%). The data sufficiency threshold is based on the accumulated set of evidence, not on individual components of the evidence set.

8-12. The terms tool, method, and technique as they apply to forensic accounting are defined in the chapter as follows:

1. A tool is an instrument that creates leverage in processing, understanding, and/or illustrating data. Examples in the chapter include relationship charts, link analysis, and timelines.

2. A method is a process that determines what data are examined and how such data are processed. Methods are more targeted in their application than tools. Examples of methods are the net worth method, descriptive statistics that describe a data distribution, and data mining methods.

3. A technique is a particular approach for applying a tool or method in a specific situation.

8-13. Three operating constraints that impact data analysis presented in the chapter are:

1. Time constraints. A data analysis limitation related to the amount of time available to perform the analysis. Within a given time horizon, larger amounts of data increase the impact of this constraint.

2. Access to data. The ease of access impacts this constraint, for data cannot be analyzed unless it is available and obtainable within the engagement time frame.

3. Technological resources. This relates to the amount of technological power available to a forensic accountant during the data analysis time frame. Technological resources include computers, software, cameras, and recording devices; their availability can increase the ability of a forensic accountant to analyze data, and vice versa.

8-14. Students will select three potential data limitations that must be considered by a forensic accountant to determine whether available data are useful for a specific engagement. These will be selected from among the following five data limitations set forth in the chapter:

1. Missing data. The analyst must consider whether all relevant data have been disclosed. Knowing what data is not disclosed provides an opportunity for such data to be obtained by alternative means.

2. Altered data. It is possible that data have been altered. This may occur before the data leaves the possession of the source, while it is being transported, or while it is in the possession of the analyst. Alterations may be intentional or unintentional.

3. Different forms of the same data. The same data may be available in more than one form. An analyst should be aware of the various forms in which the data exist and any differences among them.

4. Different definitions of the same data. Data may be known by different names. A forensic accountant will normally receive only what is specifically requested, and nothing more. Thus, getting the document’s nomenclature correct is a key to success in this area.

5. Nonexistent data. Data may not exist in any form. This may be because it was never converted to a tangible or digital form, or was in tangible or digital form but was only retained for a certain period of time.

8-15. First-, second-, third-, and fourth-party data are defined in the chapter as:

1. First-party data are obtained from an individual or an entity. Examples include the subject company in a business valuation, the plaintiff in an economic damages claim, and the victim of a suspected fraud. First-party data are preferable for two reasons: They are direct and accessible.

2. Second-party data are obtained from individuals or entities that are related or connected to the subject. Such a relationship may be personal (such as family or friends) or business (such as co-owners, employees, customers, vendors, or external accountants).

3. Third-party data are obtained from entities that maintain records regarding the subject, such as financial institutions and government agencies. The primary advantage of this data source is that it is outside the subject’s ability to manipulate. This type of data can come from a protected source or from public records.

4. Fourth-party data are obtained from reference sources, such as news articles, academic journals, trade publications, case law, transaction databases, and government statistics. This information does not reflect the actual activity of the subject. Rather, it is used to gain insight regarding the environment in which the subject operates, including the local geographic market, the industry, and the broader economy.

8-16. The reliability of first-, second-, third-, and fourth-party data to a forensic accountant is a key element of sufficiency and is related to the data’s source. First-party data are vulnerable from a reliability perspective, as such data may not be entirely accurate or objective and is more susceptible to manipulation.

Second-party data generally have higher reliability than first-party data as these data are generated by parties related to a first-party. Examples include compilation, review, and audited financial statements prepared by CPAs for a first-party person or firm. Another example is tax returns that are filed with the government under penalties of perjury and thus may have higher potential reliability.

Third-party data are generally considered reliable because they are outside the control of the subject. Examples are bank statements and vendor invoices.

Fourth-party data reliability is variable, and such data are dependent on the quality of the source being used in an examination.

8-17. The benefits of a written data analysis plan include: (1) it forces the analyst to explicitly consider data constraints; (2) it helps the analyst remain on task, avoiding any unnecessary efforts that consume valuable time and resources; (3) it provides a standard against which to monitor the progress of the data analysis; and (4) it facilitates a detailed description of the analysis, which is a necessary component for communicating results at the completion of an engagement.

8-18. It is important to identify the proper universe of data prior to commencing data analysis because if the universe is not properly defined, a forensic accountant cannot select a meaningful sample for detailed analysis.

8-19. The U.S. v. Poe and the U.S. v. Shafer cases presented in this chapter illustrate two different universes of data. In U.S. v. Poe, the forensic accountant’s challenge was to process an abundance of data. In contrast, in U.S. v. Shafer, the forensic accountant faced an absence of existing data, which required the creation of new data. Thus, whether data are abundant or sparse, planning is important to successful analysis.

8-20. The data gathering effort is impacted by the nature of the engaging party. In a corporate investigation, the engaging party may be able to provide necessary data or provide access to persons who can assist in obtaining needed data.

On the other hand, in a civil investigation the availability of data depends on the engaging party. If a forensic accountant is engaged by the party who has possession of the data, then obtaining the data may be as simple as requesting it from the client through the engaging attorney. On the other hand, if engaged by a party who does not have possession of the data, the engaging attorney will use a forensic accountant’s request letter to draft discovery requests.

8-21. If an opposing party fails to comply with requests for data, a forensic accountant might secure data needed for the analysis process by having an attorney obtain a subpoena (aimed at securing a person for testimony) or a subpoena duces tecum (directed at the production of documents and other data).

8-22. The four things a forensic accountant should consider when drafting a formal request for information are:

1. The specific nature of the data requested, such as the form of the data (paper or digital), the form of paper data (original or copy), the time periods for which data are needed, and the parties to which the request applies

2. The need for supporting documentation, such as schedules, attachments, or other items

3. Plans to conduct interviews or site visits

4. A statement about whether alternative forms of data are acceptable, such as a computer listing of invoices as a substitute for a copy of the invoice.

8-23. Factors that impact the data preparation efforts of a forensic accountant include where the data comes from, how data will be transformed, and how the information will be staged for later use. This task can be both time- and labor-intensive.

8-24. The purpose of preparing an inventory of data collected in a forensic engagement is to provide a checklist that can be used to ensure all requested data are received, to identify missing/needed data, to provide insight into the types of analysis procedures that might be applied to the data, and to provide insight into how tests might be sequenced throughout the analysis time frame. In addition, the inventory can be continuously updated and thus serve as an accomplishment indicator as the engagement progresses.

8-25. Key considerations in creating a database for data analysis purposes include determining which specific data fields are needed for data entry, how data accuracy will be maintained, and how data will be standardized to ensure it is presented in a consistent manner.

8-26. Three types of relationship charts are genograms, organizational charts, and entity charts. A genogram is a map of family or personal relationships. An organizational chart presents responsibility or authority relationships within an organization. An entity chart illustrates relationships among entities, which might include structure and ownership.

8-27. A flow chart sets forth flows of information, goods, or money through an organization. It can also illustrate an operating process. It is useful in a forensic engagement as it may disclose additional subjects that should be investigated.

8-28. Link analysis is a method of identifying relationships among objects. This tool is useful to a forensic accountant for mapping known relationships, which might reveal hidden relationships or links related to the parties associated with an issue being investigated in a forensic accounting engagement.

8-29. Ripple theory is the tracing of incremental effects related to some initial stimulus (event). This concept might benefit a forensic accountant by disclosing additional data related to the “ripples” that might be collected and analyzed by a forensic accountant.

8-30. A timeline is a summary of events arranged in chronological order along a line.

8-31. A timeline might serve these four purposes during the course of a forensic engagement:

1. Definition of scope limitations. Engagements can be limited in scope to certain time periods. When this is the case, a timeline is critical for establishing and maintaining boundaries for the universe of data.

2. Visual summary. A timeline provides a visual summary of key facts and events related to the engagement. Because people have a tendency to think in chronological terms, this is a useful tool for familiarizing various parties with the background of a case.

3. Analytical tool. In addition to summarizing information, timelines can also be used to identify missing information. While a timeline sets forth what is known, it may also serve as a basis for discerning what is not known. For example, a large gap in a timeline may indicate the need for further investigation of that specific time interval. This tool can also offer insight regarding potential causal relationships.

4. Presentation tool. Timelines may be used not just to summarize the facts but rather to weave them into a story. Based on the same set of facts, it is possible to create multiple stories or explanations.

8-32. Factors that should be considered when creating a timeline are: (1) the specific information to include (which is dependent on the purpose for which it is being developed, such as a presentation tool for a management group or a jury), (2) the number of events to be included, and (3) the spacing scale on the timeline. If the precise timing of events is important, a constant scale is appropriate. On the other hand, if the sequence of events is the most important attribute, then a constant scale is not required.

8-33. When assessing the reliability of timeline data, a forensic accountant must consider the source of each timeline component. To obtain accurate time, any device that has a clock will provide needed data; for example, computers, phones, cash registers, and ATMs. Other sources of time include bank check processing stamps, receipts from businesses, and email documents. A forensic accountant must be aware that timing information is vulnerable to manipulation, such as adjusting computer clocks and intentionally misdating documents.

8-34. Two reasons why an interview should be transcribed by the person who conducts the interview are that it ensures the record of a conversation is as accurate as possible and it allows for the inclusion of contextual items. Also, it provides a first opportunity for a forensic accountant to extract meaning from the data.

8-35. Selection is determining what information to include in an interview transcript, whereas reduction is determining how the information obtained in the interview is reduced to words. Examples of the latter include how to present pauses and emotions, how to express emphasis in spoken words, how to handle overlapping talk and interruptions, and how to present utterances, such as uh-huh or throat clearing.

Multiple-Choice Questions

Select the best response to the following questions related to the role of data analysis in a forensic accounting engagement:

8-36. B

8-37. B

8-38. D

8-39. B

8-40. C

8-41. A

8-42. D

8-43. C

8-44. B

8-45. A

Select the best response to the following questions related to framing the data analysis task, selecting data sources, and planning for data analysis:

8-46. D

8-47. B

8-48. A

8-49. C

8-50. A

8-51. B

8-52. C

8-53. A

8-54. D

8-55. C

Select the best response to the following questions related to data collection and data preparation:

8-56. A

8-57. A

8-58. D

8-59. B

8-60. A

8-61. A

8-62. B

8-63. C

8-64. A

8-65. A

Select the best response to the following questions related to data analysis tools:

8-66. D

8-67. A

8-68. A

8-69. A

8-70. A

8-71. C

8-72. A

8-73. B

8-74. D

8-75. B

Workplace Applications

8-76. The timeline constructed by students will vary in terms of the tool used to develop it (PowerPoint, Excel, Word). The purpose of this exercise is to provide students with an opportunity to develop and assess a timeline. Students can find sources of instruction on how to accomplish this by conducting a Google search. Useful guidance from Microsoft and Youtube will be common sources.

1. Students should observe a progression of educational experiences that lead to a DBA degree, as well as post-DBA studies.

2. Each item of education should be presented.

3. Students might omit the CPA exam as it is not an educational event, but rather a professional achievement.

4. A chronological scale is used, but because the timing of events is not critical; a constant scale is not employed.

5. The gaps between educational events are caused by a variety of factors. The gap between high school and college graduation is the result of four years in the Air Force. The gap between the undergraduate degree and the MBA is attributable to the beginning of a career: four years with Ernst & Ernst, CPAs, and the first three years of a banking career. The gap between the MBA and the DBA is attributable to the continuation of a twenty-year banking career and a movement to college teaching as a result of retirement from banking and a move to higher education.

6. The data are from a first-party source—one of the authors.

This exercise illustrates the valuable timeline attribute as a visual summary and provides insight about causal relationships. It also illustrates how timeline gaps might lead to further investigation to determine the reasons for the gaps.

The following are provided as illustrations of timeline presentation approaches. Students will develop alternatives using their creative talents.

Timeline Developed in Excel

BornStarted Grade SchoolGraduated High School

Undergraduate Degree in

Accounting and Passed CPA

Exam

Earned MBA with Concentration

in Finance

Earned DBA with Concentration in

Management

Post Doctoral Studies Added Concentration in Accounting

1946195219641971197819972002

Defiance, Ohio

Ney Elementary

Fairview High

Ball State UniversityUniversity of Toledo

Nova Southeastern

University

Nova Southeastern

University

Timeline Developed in Word

SHAPE \* MERGEFORMAT

Timeline Developed in PowerPoint

8-77. 1. The type of chart presented in the article makes it easier for a forensic accountant to figure out how the Madoff organizational structure might have enabled the conduct of Madoff’s Ponzi scheme. This is accomplished by highlighting the separation of functions and authority in a typical feeder fund structure, compared to the Madoff structure where B A Madoff Investment Advisory apparently acted as fund manager, administrator, and custodian—functions that are separated in the typical feeder fund structure.

A forensic accountant might benefit from this type of visual in two ways. First, it illustrates the complicated flow of funds from an investor to the investor’s share of a fund in the fund’s accounting records. Second, a forensic accountant can compare the typical structure to the Madoff structure. Doing so highlights the opportunity for one person in the Madoff organization to control the fund, the accounting for the fund, and the physical custody of the fund’s assets, making the perpetration of a fraud much more likely.

2. The data for this question is from an article; thus, it is a fourth-party source.

8-78. The Mattco Forge, Inc. v. Arthur Young & Co. case timeline of major events is:

1985 Mattco Forge sues GE in federal court.

1987 GE files a counterclaim against Mattco.

1989 Case dismissed without prejudice in March.

1989 Mattco sues Arthur Young for malpractice.

1991 Arthur Young was granted summary judgment—case dismissed.

1992 Mattco appeals and the California Court of Appeals reversed the dismissal.

1994 Case tried in California District Court. Mattco wins.

1997 Califiornia Appeals Court reverses District Court Decision and appeal denied.

1. The events students will select for inclusion in their timeline should include most of the major court events listed above. There are numerous motions and court decisions surrounding each of the key court dates, but they are not presented as they are not part of the major aspects of a lawsuit’s story.

2. Since time is not an important aspect of the story, the chronological scale need not be constant.

3. The learning objective is to provide students with an opportunity to consider which events should be included in a timeline. The primary consideration for selection of timeline elements is the audience to whom the timeline will be presented.

8-79. The organizational chart for the student’s college or university will vary from institution to institution. The purpose of this exercise is to provide students with an opportunity to prepare an organization chart and to consider the relationship and authority structure of a particular institution.

1. Students will obtain information from a variety of sources. Possible sources are the institution’s senior managers, web site, published internal materials, or the report to an accreditation body.

2. Students should obtain a clear picture of how management of the educational institution is structured, who fills each key position on the management team, and who reports to whom.

3. The specific learning related to this exercise should include: how to find the needed data, how to construct the organizational chart, and how the chart provides an understanding of how the senior management group is structured, which should provide insights into who is responsible for key functions within the organization.

4. Data sources will be first-party for data obtained from senior managers.

Chapter Problems

8-80. As students prepare for an in-class discussion about how a genogram might be useful in understanding relationships in a forensic examination, they will discover the following information related to Tiger Woods:

1. Tiger Woods’s mother is Kutilda Punsawad; his father is Earl Woods.

2. Tiger has stepbrothers, Earl, Jr., Kevin, and Royce.

3. Cheyenne Woods is related to Tiger, as she is the daughter of Earl Woods, Jr.

4. Earl Woods and his first wife (Barbara Gray) were divorced.

5. Tiger married Elin Nordegren in 2004.

6. The green line that looks like a railroad track running between Earl and Tiger signifies that they are best friends.

7. This type of diagram might facilitate courtroom testimony related to a forensic engagement by providing a way to summarize existing relationships. This makes it easier to explain to a trier of fact.

Note: Students may need to perform additional Internet searches to understand the meaning of some of the genogram symbols.

8-81. Students will obtain different journal or magazine articles that display a timeline. Their memo that describes the timeline should address the following:

1. The topic presented in the timeline they selected

2. The story the timeline tells

3. The specific information presented for key data points, with an explanation of why it is important enough to be included on the timeline

4. The type of scale used: constant or nonconstant

5. What the student learned about the structure and impact of timeline presentations

8-82. Students will find two articles on link analysis. The memo they prepare will vary based on the particular articles they reference but should explain the methodology set forth in the articles and how understanding link analysis might be useful in a forensic accounting engagement.

Case

8-83. Students will reflect on house sale data that has been collected for sales of homes in Fort Wayne, Indiana, from July 31, 2011, to December 31, 2011. The data were collected to try to determine what factors influence the selling price of homes. Based on each student’s analysis of the data, suggested responses for each question are:

1. Specific types of data collected are: home price, home square footage, age of home, extras (household items remaining: washer, dryer, drapes, etc.). Other items that might be of interest will vary by student, but might include location, maintenance level of the home, and colors used inside and outside of home.

2. The data is coded without the use of commas and such coding is consistent from item to item.

3. The best way to determine which items are important to a home’s price is to run a regression analysis. A multiple regression, run in SPSS, yields the following: r-squared is .864 which indicates high model reliability. The only significant independent variable is square footage.

4. The data are from a third-party source, a database prepared by a local government.

While performing a regression analysis may be beyond the scope of individual instructor’s course requirements, this case provides a basis for alerting students to data analysis methods a forensic accountant might employ. For example, in a business valuation of a nonpublicly traded company, a regression of factors related to similar publicly traded firms might yield useful results.

Model Summary
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.929a	.864	.825	20405.78898
a. Predictors: (Constant), RETax, Extras, Age, SquareFtt

ANOVAb
Model	Sum of Squares	df	Mean Square	F	Sig.
1	Regression	3.693E10	4	9.233E9	22.174	.000a
	Residual	5.830E9	14	4.164E8
	Total	4.276E10	18
a. Predictors: (Constant), RETax, Extras, Age, SquareFt b. Dependent Variable: Price

Coefficientsa
Model	Unstandardized Coefficients	Standardized Coefficients	t	Sig.
	B	Std. Error	Beta
1	(Constant)	-30333.086	42224.252		-.718	.484
	SquareFt	90.736	22.592	.926	4.016	.001
	Age	748.723	974.316	.101	.768	.455
	Extras	-1965.787	3153.555	-.072	-.623	.543
	RETax	5.288	26.329	.044	.201	.844
a. Dependent Variable: Price

1946 1952 1964 1971 1978 1997 2002

Born

Defiance

Ohio

Started

Grade

School

Ney,

Ohio

Graduated

Fairview

High

School

Graduated

College

Ball State

University

---------------

Accounting

Major

Earned

MBA

University

of Toledo

-------------

Finance

Specialty

Earned

DBA

Nova

Southeastern

University

Management

Concentration

Post

Doctoral

Studies

Nova

Southeastern

University

Accounting

Concentration

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Copyright © 2015 Pearson Education, Inc.

BornStarted Grade SchoolGraduated High School

Undergraduate Degree in

Accounting and Passed CPA

Exam

Earned MBA with Concentration

in Finance

Earned DBA with Concentration in

Management

Post Doctoral Studies Added Concentration in Accounting

1946195219641971197819972002

Defiance, Ohio

Ney Elementary

Fairview High

Ball State UniversityUniversity of Toledo

Nova Southeastern

University

Nova Southeastern

University