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svet-max [94.6K]
3 years ago
13

Amanda has $75 in her savings accountwhile Julie has $30 in her savings account Amanda adds $5 per week into her allowance and J

ulie saves $14 per week. How much money will they have when they have the same amount of money ?
please explain <3
Mathematics
1 answer:
ELEN [110]3 years ago
5 0

Answer:

$100

Step-by-step explanation:

Every week Amanda adds $5 and every week Julia adds $14. So all you have ti do is add $5 to Amanda's account and $14 to Julia's account until you have the same amount of money for the both of them.

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what is the correct way to write three hundred nine million, fifty-eight thousand, three hundred four?
oksian1 [2.3K]

-- sitting erect, shoulders back, chest out, head up, spine straight

-- pen held loosely and comfortably in your hand

-- forearm resting lightly on the table

-- digit characters formed neatly and clearly, with uniform size and slant

                <em>3 0 9, 0 5 8, 3 0 4</em> .


3 0
3 years ago
Find the sine of angle S. Reduce the answer to the lowest terms.
NeX [460]

Answer:

\sin e\text{ S = }\frac{3}{5}

Explanation:

Here, we want to get the value of sine S

The sine of an angle is the ratio of the opposite side to the hypotenuse side

The hypotenuse side is the side that faces the right angle which is the small box. It is the longest side of the triangle and it measures 10

The opposite is the side that faces the angle which is 6

We have the sine as:

\frac{6}{10}\text{ = }\frac{3}{5}

8 0
10 months 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
Asphere has a diameter of 10 in. What is the volume of the sphere?
Pavel [41]

Answer:\frac{500}{3}π in^{3}

Step-by-step explanation: diameter=10 in

radius=\frac{diameter}{2}=\frac{10}{2}=5 in

volume=\frac{4}{3}r^{3}

=\frac{4}{3}    X 5^{3}  x π =\frac{500}{3}π in^{3}

3 0
3 years ago
The square on the right is a scaled copy of the square on the left. Identify the scale factor. Express your answer as a fraction
ivanzaharov [21]

Answer:

Step-by-step explanation:

23 /8

The scale factor is the number you multiply each side of the object to get each side of the image. Let's call the scale factor x.

8x=23

x=23/8

The scale factor is 23/8

6 0
1 year ago
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