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earnstyle [38]
3 years ago
11

Please help me this is my end of the year work

Mathematics
1 answer:
alexandr1967 [171]3 years ago
8 0

Answer:

Triangle, pentagon, heptagon, and decagon.

Step-by-step explanation:

REMEMBER THIS:

DECAGON: 10 SIDES

HEPTAGON: 7 SIDES

PENTAGON: 5 SIDES

TRIANGLE: 3 SIDES

EXTRA INFO:

HEXAGON: 6 SIDES

QUADRILATERAL: 4 SIDES

OCTAGON: 8 SIDES

NONAGON: 9 SIDES

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A it is a many to one function
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The circles centered at points A, C, and D have radii of length AC.
natita [175]

it is the second one

Step-by-step explanation:

3 0
2 years ago
Two pupils each drew a triangle with one side of 6 cm , one side of 10 cm and one side of 7 cm. Must their triangles be congruen
7nadin3 [17]

Answer:

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Step-by-step explanation:

they can be either side because the numbers are different in the angles

5 0
3 years ago
Suppose that bugs are present in 1% of all computer programs. A computer de-bugging program detects an actual bug with probabili
lawyer [7]

Answer:

(i) The probability that there is a bug in the program given that the de-bugging program has detected the bug is 0.3333.

(ii) The probability that the bug is actually present given that the de-bugging program claims that bugs are present on both the first and second tests is 0.1111.

(iii) The probability that the bug is actually present given that the de-bugging program claims that bugs are present on all three tests is 0.037.

Step-by-step explanation:

Denote the events as follows:

<em>B</em> = bugs are present in a computer program.

<em>D</em> = a de-bugging program detects the bug.

The information provided is:

P(B) =0.01\\P(D|B)=0.99\\P(D|B^{c})=0.02

(i)

The probability that there is a bug in the program given that the de-bugging program has detected the bug is, P (B | D).

The Bayes' theorem states that the conditional probability of an event <em>E </em>given that another event <em>X</em> has already occurred is:

P(E|X)=\frac{P(X|E)P(E)}{P(X|E)P(E)+P(X|E^{c})P(E^{c})}

Use the Bayes' theorem to compute the value of P (B | D) as follows:

P(B|D)=\frac{P(D|B)P(B)}{P(D|B)P(B)+P(D|B^{c})P(B^{c})}=\frac{(0.99\times 0.01)}{(0.99\times 0.01)+(0.02\times (1-0.01))}=0.3333

Thus, the probability that there is a bug in the program given that the de-bugging program has detected the bug is 0.3333.

(ii)

The probability that a bug is actually present given that the de-bugging program claims that bug is present is:

P (B|D) = 0.3333

Now it is provided that two tests are performed on the program A.

Both the test are independent of each other.

The probability that the bug is actually present given that the de-bugging program claims that bugs are present on both the first and second tests is:

P (Bugs are actually present | Detects on both test) = P (B|D) × P (B|D)

                                                                                     =0.3333\times 0.3333\\=0.11108889\\\approx 0.1111

Thus, the probability that the bug is actually present given that the de-bugging program claims that bugs are present on both the first and second tests is 0.1111.

(iii)

Now it is provided that three tests are performed on the program A.

All the three tests are independent of each other.

The probability that the bug is actually present given that the de-bugging program claims that bugs are present on all three tests is:

P (Bugs are actually present | Detects on all 3 test)

= P (B|D) × P (B|D) × P (B|D)

=0.3333\times 0.3333\times 0.3333\\=0.037025927037\\\approx 0.037

Thus, the probability that the bug is actually present given that the de-bugging program claims that bugs are present on all three tests is 0.037.

4 0
3 years ago
Please help me with this Imma on a time limit
Rus_ich [418]
Y=12.5x
because 12.5 is the constant and this is a directly proportional equation

8 0
3 years ago
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