Plss help for 18 ASAP

Solve please! You have to just find the value of x using the angle .

maksim [4K]

Answer:

x=55°

Step-by-step explanation:

x=90-35

x=55°

(because its x+35=90°)

6 0

3 years ago

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Find an equation to the line perpendicular to 4x + 36y =80 an goes through the point (3,6) write answer in form y= Mx+b

Veronika [31]

Answer:

$\textbf{y = 9x + 21 }\\$

Step-by-step explanation:

$\textup{Given equation is: $4x + 36y = 80 $}\\\textup{This can be written in the form of $y = mx + a$ as follows}\\$ 36y = -4x + 80 $\\$ \implies y = \frac{80}{36} - \frac{4}{36}x $\\$ \implies y = \frac{-1}{9}x + \frac{20}{9} $\\\textup{This means that the slope of this line is $m = \frac{-1}{9}$}\\$

$\textup{Then the slope of the line perpendicular to this line would be \textbf{negative reciprocal of m}.}\\$i.e.,$ \textup{Slope of the perpendicular line would be $m_1 = \frac{-1}{\frac{-1}{9}}$}\\$\implies m_1 = 9$\\$

$\textup{The perpendicular line passes through the point $(3,6)$}\\\textup{Using the \textbf{point-slope formula}, we get:}\\$

$$$ y - y_1 = m(x - x_1) $$$ \implies y - 6 = 9(x - 3) $\\\textup{After solving this reduces to $y = 9x + 21$ }$

8 0

3 years ago

The ratio of students who wear glasses to the total number of students in the class is 2:5 if there are 14 students who wear gla

vazorg [7]

Answer:

35 students in the class.

Step-by-step explanation:

If there are 5 students in the class, then 2 of them would wear glasses and 3 of them wouldn't. (Equation 1)

Now, there are 14 students how are wearing glasses.

We just times the whole Equation 1 by 7.

If there are 5 x 7 = 35 students in the class, then 2 x 7 = 14 of them would wear glasses and 3 x 7 = 21 of them wouldn't.

So, there are 35 students.

8 0

2 years ago

Stats help please! Can’t figure out how to solve

mariarad [96]

This is unreadable...

8 0

3 years ago

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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

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