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3 years ago

What is the solution to 4w=2/3

2 answers:

7 0

4w = 2/3 Divide each side by 4 to get w by itself.

w = 2/3 ÷ 4 To divide fractions you multiply the reciprocal

w = 2/3 × 1/4 multiply across

w = 2/12 which reduces

w = 1/6

grigory [225]3 years ago

4 0

2/12 or 1/6. You have to divide 2/3 by 4 to get what w equals to.

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Can someone please help me

sergij07 [2.7K]

Answer:

m∠TSP = 53°

Step-by-step explanation:

m∠RSU and m∠TSP are vertical angles

3 0

3 years ago

One of two complementary angles measures 30 degrees more than three times the other. Find each angle.

Leviafan [203]

The two complementary angles are:

95° and 15°

Step-by-step explanation:

Let x be one angle

then the other angle will be 90-x

As the sum of complementary angles is 90

So,

then according to statement

$x = 3(90-x)+30\\x = 270-3x +30\\x = 300-3x\\x+3x = 300\\4x = 300\\x = \frac{300}[4}\\x = 75\\and\\90 -x = 90 - 75 = 15$

The two complementary angles are:

95° and 15°

Keywords: Angles, triangles

Learn more about angles at:

#LearnwithBrainly

7 0

3 years ago

A submarine is diving to a total depth of 45 feet. It descends 15% of the total depth in 1 minute. How deep will the submarine b

telo118 [61]

after 4 mins the sub reaches 27 feet

8 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

Firlakuza [10]

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, $0.9664 \times 100 = 96.64$

6 0

3 years ago

Solve for x.<br><br> −5x−4(x−6)=−3

zvonat [6]

- 5x - 4x + 24 = - 3
9x = 27
x = 3

3 0

3 years ago