Find the slope of the line passing through the points<br> (-4,-3) and (8,-9)

What is an equation of the line that passes through the points (-2, -5) and (-1, 1)?

Dennis_Churaev [7]

Answer: y=6x+7

Step-by-step explanation:

To find the equation of the line, we want to find the slope with the formula $m=\frac{y_2-y_1}{x_2-x_1}$ .

$m=\frac{1-(-5)}{-1-(-2)} =\frac{6}{1}=6$

Now that we know th eslope, we can start to fill out the equation. To find the y-intercept, we can plug in a given point and solve.

y=6x+b

1=6(-1)+b [multiply]

1=-6+b [add both sides by 6]

b=7

Now, we know the equation is y=6x+7.

8 0

3 years ago

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11. It took Mr. Owen 12 hours to build

Charra [1.4K]

Answer:

3 feet per hours

Step-by-step explanation:

To get unit rate divide foot by hours

$\frac{36}{12} = 3$

3 0

3 years ago

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Priscilla can make 4 bracelets in 13 minutes. At this rate, how many bracelets can she make in 26 minutes?

Degger [83]

Answer:

8

Step-by-step explanation:

To find the answer, multiply 4 and 2 together, since 13 is 2 times less than 26.

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Let's double check,

26 ÷ 13 = 2

so,

4 × 2 = 8

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Have a good day :)

4 0

3 years ago

A tree casts shadow 26 ft long. A 3 ft tall flowers casts a shadow 4 ft long. How tall is the tree?

Rufina [12.5K]

Answer:

19. 5 feets

Step-by-step explanation:

Shadow of tree = 26 feets

Height of flower = 3 feets

Shadow of flower = 4 feets

Height of sun Innthe sky:

Shadow of flower / height of flower

= 4/3 = 1.333333

Height of tree:

Shadow of tree / height of sun

26 feets / 1.33333

= 19.5 feets

Hence, height of tree = 19.5 feets

5 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

Find the slope of the line passing through the points (-4,-3) and (8,-9)