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tatyana61 [14]
1 year ago
8

Is the ordered pair (0, 4) a solution of the inequality y≤x−3? Explain.

Mathematics
2 answers:
matrenka [14]1 year ago
8 0

The given ordered pair is not the solution for y ≤ x − 3.

<h3>What is linear inequality?</h3>

Linear inequality refers to the relation between a linear algebraic expression to some known value that contains inequality sign.

Unlike a linear equation it can have a range of values inside an interval.

The inequality is given as y ≤ x - 3.

The x coordinate for the ordered pair (0,4) is 0.

And, the y coordinate is 4.

Substitute the value of x and y in the given inequality as follows,

y ≤ x - 3

=> 4 ≤ 0 - 3

=> 4 ≤ -3

Which is not true.

Hence, the ordered pair (0, 4) is not solution of the inequality y ≤x − 3.

To know more about linear inequality click on,

brainly.com/question/11897796

#SPJ1

Andrew [12]1 year ago
4 0

The ordered pair (0,4) does not satisfy the inequality thus, it will be not the solution to the given inequality.

<h3>What is inequality?</h3>

A mathematical phrase in which the sides are not equal is referred to as being unequal. In essence, a comparison of any two values reveals whether one is less than, larger than, or equal to the value on the opposite side of the equation.

As per the given inequality,

y ≤ x - 3

Put x = 0

y ≤ 0 - 3

y ≤ -3

Since 4 ≤ -3 is the wrong statement thus it will not satisfy the inequality.

Hence "The ordered pair (0,4) does not satisfy the inequality thus, it will be not the solution to the given inequality".

For more about inequality,

brainly.com/question/20383699

#SPJ1

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Answer:

40.1% probability that he will miss at least one of them

Step-by-step explanation:

For each target, there are only two possible outcomes. Either he hits it, or he does not. The probability of hitting a target is independent of other targets. So we use the binomial probability distribution to solve this question.

Binomial probability distribution

The binomial probability is the probability of exactly x successes on n repeated trials, and X can only have two outcomes.

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}

In which C_{n,x} is the number of different combinations of x objects from a set of n elements, given by the following formula.

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This means that p = 0.95

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This means that n = 10

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Either he hits all the targets, or he misses at least one of them. The sum of the probabilities of these events is decimal 1. So

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P(X < 10) = 1 - P(X = 10) = 1 - 0.5987 = 0.401

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