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GalinKa [24]
3 years ago
11

A large manufacturing business has hired you as a fraud detection specialist. The first day on the job your boss tells you she h

as heard about something called Benford's Law that is used to detect fraud, and she wants to know more about it. She has asked you to explain what Benford's Law is and how it is applied.
Business
1 answer:
bezimeni [28]3 years ago
3 0

Answer:

Benford's Law predicts the frequency of leading digits using base-10 logarithms which predict that specific frequencies will decrease from 1 to 9.

It predicts that in a large set of data, the leading digits will be as following:

<u>Leading number</u>                         <u>Probability of appearance</u>

       1                                                              30%

       2                                                             18%

       3                                                             12%

       4                                                             10%

       5                                                              8%

       6                                                              7%

       7                                                              6%

       8                                                              5%

       9                                                              4%

Benford's Law is used by forensic accountants since people who fabricate data figures tend to distribute the leading digits uniformly. If you compare the distribution of the leading digits of the data sample with the expected distribution using Benford's Law you can detect any anomaly (e.g. if number 3 shows up 30% of the time instead of around 12%).

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a) For this case we have quantitative data since we have frequencies per each category.

b) For this case is better use percentages since we have frequency counts per each

c) First we need to calculate the total for the frequencies:

Total = 44+130+165+741= 1080 respondents

For this case we can calculate the percentage like this:

\% Strongly_{agree} = \frac{44}{1080} *100 =4.07\%

d) For this case the percentage of people who agree with allowing drivers of motor vehicles to talk on a hand-held cell phone while driving is just 4.07% and by the other hand the rest of the people correspond to 95.93%.

\frac{1036}{44}=23.55

The people who are NOT strongly agree is about 24 times greater than the peopl who strongly agrees.

So we can say that we don't have a general support for the claim.

Explanation:

For this case we have the following data given:

Number of respondents that they strongly agree with the statement = 44

Number of respondents that they somewhat agree with the statement = 130

Number of respondents that they somewhat disagree agree with the statement = 165

Number of respondents that they strongly disagree agree with the statement = 741

Part a

Do the responses for this statement provide categorical or quantitative data?

For this case we have quantitative data since we have frequencies per each category.

Part b

Would it make more sense to use averages or percentages as a summary of the responses for this statement?

For this case is better use percentages since we have frequency counts per each category so then not makes sense calculate averages for this case.

Part c

What percentage of respondents strongly agree with allowing drivers of motor vehicles to talk on a hand-held cell phone while driving?

First we need to calculate the total for the frequencies:

Total = 44+130+165+741= 1080 respondents

For this case we can calculate the percentage like this:

\% Strongly_{agree} = \frac{44}{1080} *100 =4.07\%

Part d

For this case the percentage of people who agree with allowing drivers of motor vehicles to talk on a hand-held cell phone while driving is just 4.07% and by the other hand the rest of the people correspond to 95.93%.

\frac{1036}{44}=23.55

The people who are NOT strongly agree is about 24 times greater than the peopl who strongly agrees.

So we can say that we don't have a general support for the claim.

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3 years ago
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