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2 years ago

PLEASE HELP, DUE SOON!! Your teacher is giving a test. The test will have 40

Mathematics

2 answers:

fenix001 [56]2 years ago

6 0

Answer: There will be 20, 2 point questions and 8, 5 point questions.

Step-by-step explanation:

Divide 40 with 2 and you'll get 20. Divide 40 with 5, you'll get 8.

*hope this helped*

Drupady [299]2 years ago

4 0

Answer:

2 point questions would be 42.5

5 point questions would be 17

Step-by-step explanation:

40 + 2x = 125

Subtract 40 on both sides

40-40 + 2x = 125-40

You'll end up with:

2x= 85

So you'll have to do the opposite of multiplication for both sides, which is division.

2x/2 = 85/2 -------------> x= 42.5

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

40 + 5y = 125

Subtract 40 on both sides

40-40 + 5y = 125

You'll end up with

5x = 85

So you'll have to do the opposite of multiplication for both sides, which is division.

5x/5 = 85/5 ----------------> x= 17

I hope this helped !! :)

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A data mining routine has been applied to a transaction dataset and has classified 88 records as fraudulent (30 correctly so) an

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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,

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

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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,

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

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3 years ago

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3 years ago

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