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Serga [27]
3 years ago
6

The tax rate on Jerome James 112000 vacation home is 25 Mills the property is assessed at full value how much will Jerome pay in

taxes this year
Mathematics
2 answers:
zaharov [31]3 years ago
4 0

Answer: $2,800

Step-by-step explanation:

Given: The assessment value of Jerome's home= $112,000

We know that to calculate the property tax, we need to multiply the assessment value of the property by the mill rate and then divide by 1,000.

Then, the property tax is given by :-

\text{Property tax}=\dfrac{\$112,000\times25}{100}\\\\\Rightarrow=\text{Property tax}=\$2,800

Therefore, Jerome pay $2,800 as property tax in this year.

emmainna [20.7K]3 years ago
4 0

Answer:

Property tax=$2800

Step-by-step explanation:

Given: The assessment value of Jerome's home is given as =112000

Solution: Since we know that in order to calculate the property tax, we need to multiply the assessment value of the property by the mill rate and also divide by 1000.

Then, the property tax is given as :-

Property tax=\frac{112000{\times}25}{100}

Property tax=$2800

Thus, Jerome pay $2,800 as property tax in this year.

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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}  

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

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