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Scorpion4ik [409]
3 years ago
11

Answer !! ( PLEASE SHOW WORK FOR NUMBER 5.) ( ZOOM IN TO SEE BETTER)

Mathematics
1 answer:
deff fn [24]3 years ago
5 0

Answer:

12+2x

Step-by-step explanation:

2(10)+2(x-4)

20+2x-8

12+2x

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Find the volume of the cylinder.<br> Either enter an exact answer in terms of π or use 3.14 for π
Alex787 [66]

Answer:

Volume of the cylinder = 62.80 units^3

Step-by-step explanation:

Height of the Cylinder(h)=5 units

Radius(r)=2 units

Volume of a cylinder=\pi *r*r*h

     Putting the values in the formula;

Volume of the cylinder =\pi *2*2*5

                      As,   \pi =\frac{22}{7}=3.14                        

Volume of the cylinder=  3.14*2*2*5

                                 =3.14*2*2*5\\\\=3.14*4*5\\\\=3.14*20\\\\=62.80units^3                              

The Volume of the cylinder is 62.80 units^3

7 0
2 years ago
What is the area of the semicircle?
Serggg [28]

Step-by-step explanation:

Area (semi-circle)= \frac{r^2\pi }{2}

A = \frac{(11)^2\pi }{2}

A=\frac{121\pi }{2}

A=\frac{379.94}{2}

A=189.97

The area of the semi-circle is 189.97

6 0
2 years ago
Solve the simultaneous equations 4x-3y=19 and 2x+3y=23​
kogti [31]
The answer is x=7 and y=3

6 0
2 years ago
Read 2 more answers
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
Which of the points listed below is not on the line with equation 7y+2=3x-5
kicyunya [14]

Answer: Second option.

Step-by-step explanation:

Given the folllowing Linear Equation:

7y+2=3x-5

You need to substitute the coordinates of each point given in the options into the equation and then evaluate.

1) Substituting  (2, -\frac{1}{7}) into the equation, you get:

7(-\frac{1}{7})+2=3(2)-5\\\\-1+2=6-5\\\\1=1\ (TRUE)

2) Substituting the point (3, -\frac{3}{7}). you get:

7(-\frac{3}{7})+2=3(3)-5\\\\-3+2=9-5\\\\-1=4\ (FALSE)

3) Apply the same procedure using the point (1, -\frac{4}{7}):

 7(-\frac{4}{7})+2=3(1)-5\\\\-4+2=3-5\\\\-2=-2\ (TRUE)

4)  Apply the same procedure using the point (-1, -\frac{10}{7})

 7(-\frac{10}{7})+2=3(-1)-5\\\\-10+2=-3-5\\\\-8=-8\ (TRUE)

5) Substituting  (0,-1) into the equation:

 7(-1)+2=3(0)-5\\\\-7+2=-0-5\\\\-5=-5\ (TRUE)

Therefore, the point (3, -\frac{3}{7})  is not on the given line.

8 0
3 years ago
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