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3 years ago

I WILL AWARD BRAINLIEST!! Given: ∆ABC≅DEF Find: BC, BA, m∠D

Mathematics

2 answers:

seropon [69]3 years ago

8 0

Answer:

Using CPCTC, we know that congruent parts of the congruent triangles are congruent.

Given: ∆ABC ≅ ∆DEF

BC ≅ FE ⇒ CPCTC. IF FE = 5 (Given), & FE ≅ BC (CPCTC) ∴ BC = 5 (Transitive Property of Equality.)

BA ≅ DE ⇒ CPCTC. IF DE = 11 (Given) & DE ≅ BA (CPCTC) ∴ BA = 11 (Transitive Property of Equality.)

m∠D ≅ m∠A ⇒ CPCTC. Congruent Parts of Congruent Triangles are Congruent. If ∆ABC ≅ ∆DEF (given), then through CPCTC, m∠D ≅ m∠A.

charle [14.2K]3 years ago

7 0

Answer:

BC = 5

BA11

angle D = 27

Step-by-step explanation:

If the triangles are similar

ABC ≅ DEF

That means AB ≅ DE

BC ≅ EF

and CA ≅ FD

We want to find AB so it is equal to DE

BC = EF = 5

BA = AB = DE =11

We also know the angles are equal

A = D

B = E

C = F

Angle A = angle D = 27

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natulia [17]

Answer: C) Angles A and J

Step-by-step explanation:

Corresponding angles are kind of angles that are in the same position, angles a and J are both right and top corner of the parallelogram.

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3 years ago

Find the maximum profit and the number of units that must be produced and sold in order to yield the maximum profit. Assume that

V125BC [204]

Answer:

-1.39

Step-by-step explanation:

Revenue and cost as a function of units sold are $u(x) = 9x-2x^{2}$ and $c(x)=x^{3}-3x^{2}+4x+1$ respectively.

we are have to know for which value or input units are these functions at maximum which translates to for how many units is the revenue maximum and for how many same units is our cost minimum.

5 0

4 years ago

The length of RT is 4x-4.Given that point S is between point R and T,

Monica [59]

Answer:

RS = 32

Step-by-step explanation:

Set-up equation like this -- 2x+6+16=4x-4

Solve for x

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7 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

How do I simplify this by combining like terms

pickupchik [31]

You would simplify this expression by adding the coefficients 14 and -5.
$14x^{2} -5^{2}\\ 9x^{2}$

7 0

3 years ago