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Ksju [112]
3 years ago
11

A mechanic charges her clients for her services on a relation of the total bill f (h) to the number of hours worked h. The best

interpretation of 125 In the function is f (h) = 125 + 20h.
A: she charges a flat fee of $125

B: she charges $125 for a tire change

C: she charges $125 per day

D: she charges $125 per hour ​
Mathematics
1 answer:
soldi70 [24.7K]3 years ago
3 0

Answer:

  A: she charges a flat fee of $125

Step-by-step explanation:

The $125 is a fee that is not associated with hours worked. There is insufficient information in the problem statement to tell the reason for that fee, except that we know it is not the hourly charge. Perhaps the best assumption is that it is a flat fee.

Apparently, she charges a flat fee of $125.

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nataly862011 [7]

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Step-by-step explanation:

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8 0
3 years ago
1 4/9 divided by -2/9
Varvara68 [4.7K]

Answer:

6 1/2

Step-by-step explanation:

change 1 4/9 into a improper fraction, which is 13/9, and when dividing fractions flip the second number upside down then multiply. 13/9 times -2/9 is -117/18. simplify, which is 13/2, which is also equal to 6 1/2. hope this helped

7 0
3 years ago
A data mining routine has been applied to a transaction dataset and has classified 88 records as fraudulent (30 correctly so) an
chubhunter [2.5K]

Answer:

The classification matrix is attached below

Part a

The classification error rate for the records those are truly fraudulent is 65.91%.

Part b

The classification error rate for records that are truly non-fraudulent is 96.64%

Step-by-step explanation:

The classification matrix is obtained as shown below:

The transaction dataset has 30 fraudulent correctly classified records out of 88 records, that is, 30 records are correctly predicted given that an instance is negative.

Also, there would be 88 - 30 = 58 non-fraudulent incorrectly classified records, that is, 58 records are incorrectly predicted given that an instance is positive.

The transaction dataset has 920 non-fraudulent correctly classified records out of 952 records, that is, 920 records are correctly predicted given that an instance is positive.

Also, there would be 952 - 920 = 32 fraudulent incorrectly classified records, that is, 32 records incorrectly predicted given that an instance is negative.

That is,

                                                                            Predicted value

                           Active value                 Fraudulent       Non-fraudulent

                              Fraudlent                         30                       58

                          non-fraudulent                   32                     920

The classification matrix is obtained by using the information related to the transaction data, which is classified into fraudulent records and non-fraudulent records.

The error rate is obtained as shown below:

The error rate is obtained by taking the ratio of \left( {b + c} \right)(b+c) and the total number of records.

The classification matrix is, shown above

The total number of records is, 30 + 58 + 32 + 920 = 1,040

The error rate is,

\begin{array}{c}\\{\rm{Error}}\,{\rm{rate}} = \frac{{b + c}}{{{\rm{Total}}}}\\\\ = \frac{{58 + 32}}{{1,040}}\\\\ = \frac{{90}}{{1,040}}\\\\ = 0.0865\\\end{array}  

The percentage is 0.0865 \times 100 = 8.65

(a)

The classification error rate for the records those are truly fraudulent is obtained by taking the rate ratio of b and \left( {a + b} \right)(a+b) .

The classification error rate for the records those are truly fraudulent is obtained as shown below:

The classification matrix is, shown above and in the attachment

The error rate for truly fraudulent is,

\begin{array}{c}\\FP = \frac{b}{{a + b}}\\\\ = \frac{{58}}{{30 + 58}}\\\\ = \frac{{58}}{{88}}\\\\ = 0.6591\\\end{array}  

The percentage is, 0.6591 \times 100 = 65.91

(b)

The classification error rate for records that are truly non-fraudulent is obtained by taking the ratio of d and \left( {c + d} \right)(c+d) .

The classification error rate for records that are truly non-fraudulent is obtained as shown below:

The classification matrix is, shown in the attachment

The error rate for truly non-fraudulent is,

\begin{array}{c}\\TP = \frac{d}{{c + d}}\\\\ = \frac{{920}}{{32 + 920}}\\\\ = \frac{{920}}{{952}}\\\\ = 0.9664\\\end{array}

The percentage is, 0.9664 \times 100 = 96.64

8 0
3 years ago
The diagram below represents which percent?
nirvana33 [79]

Answer:

80%

Step-by-step explanation:

There are 4 shaded sections and 1 unshaded section, so five sections in total.

4 sections are shaded, so the fraction would be 4/5.

Dividing 4/5 gets you 0.8, move the decimal point two places over to get the percent (80%).

4 0
3 years ago
Read 2 more answers
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