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8_murik_8 [283]
3 years ago
12

Finish the following table for the given function with x as thr independent variable.

Mathematics
2 answers:
konstantin123 [22]3 years ago
5 0
The answer is c.0.1,0.05.0.025.
We can find these by substituting the x values on the table given into the equation; h(x)=1/x.
jolli1 [7]3 years ago
5 0

Answer:

C

Step-by-step explanation:

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Mr. Shaw wants to replace the flooring his family room. The floor has an area of 262.8 square feet. If the room is 18 feet long,
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14.6

Step-by-step explanation:

The area of a rectangle is area=length*width

so we can substitute the numbers here, 262.8=18w

divide 262.8 by 18 to isolate the variable.

You get 14.6.

The width is 14.6.

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A model for my number has 6 ones blocks, 2 hundreds blocks and 3 tens blocks what number am i?
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If you invest $1,600 at 5.35% for 18 months how much simple interest is earned​
valentinak56 [21]

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Step-by-step explanation:

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3 years ago
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I need help pls explain
vladimir1956 [14]
For 1. The bike is going 24 miles in 3 hours. To figure out how many miles it went in 1 hour you divide 24/3 which is 8 miles. If the bike went 8 miles per hour then you may now multiply it by 10 to find the total mileage in 10 hours. 10x8=80
8 0
3 years ago
An exit poll in an election is a survey taken of voters just after they have voted. One major use of exit polls has been so that
3241004551 [841]

Answer:

P(A) = 0.39

Step-by-step explanation:

We are given;

P(W|A) = 0.7

P(W|A^c ) = 0.3

We are told that 60% of the respondents said they voted for A. Thus;

P(A|W) = 60% = 0.6

Now, using the principle of drawing lots, we can be able to find the probability of the event that they are willing to participate in the exit poll which is P(W).

Thus;

P(W) = [P(W|A) × P(A)] +[P(W∣A^c) × P(A^c)]

Now, P(A^c) can be expressed as 1 - P(A)

Thus, we now have;

P(W) = [P(W|A) × P(A)] + [P(W∣A^c) × (1 - P(A)]

Plugging in the relevant values gives;

P(W) = 0.7P(A) + 0.3(1 - P(A))

P(W) = 0.7P(A) + 0.3 - 0.3P(A)

P(W) = 0.3 + 0.4P(A)

Now,using Baye's theorem, we can find an expression for P(A|W)

Thus;

P(A|W) = [P(A ∩ W)]/P(W)

This can be further expressed as;

P(A|W) = [P(A) × P(W|A)]/P(W)

Plugging in relevant values, we have;

0.6 = 0.7P(A)/(0.3 + 0.4P(A))

Cross multiply to get;

0.6(0.3 + 0.4P(A)) = 0.7P(A)

0.18 + 0.24P(A) = 0.7P(A)

0.18 = 0.7P(A) - 0.24P(A)

0.46P(A) = 0.18

P(A) = 0.18/0.46

P(A) = 0.39

7 0
3 years ago
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