Test Bank Data Analytics for Accounting, 3rd Edition by Vernon Richardson, Ryan Teeter(2025).

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,Test .Bank .Data .Analytics .for .Accounting, .3rd .Edition .by .Vernon .Richardson, .Teeter



Chapter .01 .3e Answers .Included

TRUE/FALSE .- .Write .'T' .if .the .statement .is .true .and .'F' .if .the .statement .is .false.
1) Data .analytics .is .the .process .of .evaluating .data .with .the .purpose .of .drawing
.conclusions .to .address .business .questions.

⊚ true
⊚ false


2) The .process .of .data .analytics .aims .to .transform .raw .information .into .data .to .create .value.
⊚ true
⊚ false


3) Data .analytics .has .the .potential .to .transform .the .manner .in .which .companies .run
.their .businesses, .however .it .is .not .practical .in .the .near .future.

⊚ true
⊚ false


4) Auditors .can .use .social .media .to .hear .what .customers .are .saying .about .a .company
.and .compare .this .to .inventory .obsolescence .and .other .estimates.

⊚ true
⊚ false


5) Data .analytics .allows .auditors .to .glean .insights .that .are .beneficial .to .the .client,
.without .breeching .independence.

⊚ true
⊚ false


6) The .predictive .analytics .is .an .important .aspect .of .data .analytics .for .auditors, .but .is
.not .applicable .for .tax .accountants.

⊚ true
⊚ false


7) The .I .in .IMPACT .Cycle .represents .Identify .the .Question.

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, ⊚ true
⊚ false


8) The .M .in .IMPACT .Cycle .represents .Master .the .Data.
⊚ true
⊚ false


9) The .P .in .IMPACT .Cycle .represents .Predict .the .Results.
⊚ true
⊚ false


10) The .A .in .IMPACT .Cycle .represents .Analyze .the .Data.
⊚ true
⊚ false


11) The .C .in .IMPACT .Cycle .represents .Continuously .Track.
⊚ true
⊚ false


12) The .T .in .IMPACT .Cycle .represents .Track .Outcomes.
⊚ true
⊚ false


13) The .IMPACT .cycle .is .iterative, .as .insights .are .gained, .outcomes .are .tracked, .and
.new .questions .are .identified.

⊚ true
⊚ false


14) Data .analysis .through .data .manipulation .is .performing .basic .analysis .to .understand
.the .quality .of .the .underlying .data .and .its .ability .to .address .the .business .question.

⊚ true
⊚ false



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, 15) To .be .proficient .in .data .analysis, .accountants .need .to .become .data .scientists.
⊚ true
⊚ false


16) By .developing .an .analytics .mindset, .accountants .will .be .able .to .recognize .when .and
.how .data .analytics .can .address .business .questions.

⊚ true
⊚ false


17) While .it .is .important .for .accountants .to .clearly .articulate .the .business .problem,
.drawing .appropriate .conclusions, .based .on .the .data, .should .be .left .to .statisticians.

⊚ true
⊚ false


18) Analytic-minded .accountants .should .report .results .of .analysis .in .an .accessible .way
.to .each .varied .decision .maker .and .their .specific .needs.

⊚ true
⊚ false


MULTIPLE .CHOICE .- .Choose .the .one .alternative .that .best .completes .the .statement .or
.answers .the .question.
19) With .a .goal .to .give .organizations .the .information .they .need .to .make .sound .and
.timely .business .decisions, .data .analytics .often .involves .all .of .the .following . except:


A) technologies.
B) statistics.
C) strategies.
D) databases.



20) Patterns .discovered .from . blank .enable .businesses .to .identify
.opportunities .and .risks .and .better .plan .for . blank.




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