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omeli [17]
3 years ago
7

1. 2,000(x -0.03) = 6,000

Mathematics
1 answer:
Tasya [4]3 years ago
5 0
1. x=3.03
2.x=0.5
3.x=4/3
4.x=2
5.x=10
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The answer would be -13/3
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What is the answer to this questions it is worth 20 points
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<h2><u>Answer</u> : </h2>

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i.e. for 5 years = 10 megawatts

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Factor each completely : <br><br> NEED THIS ANSWER ASAP
Lelechka [254]

Answer:

4) 7k² + 9k

= k(7k + 9)

5) x² - 25

= (x)² - (5)².

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2 years ago
Consider the probability that no less than 92 out of 159 students will pass their college placement exams. Assume the probabilit
Yanka [14]

Answer:

0.2843 = 28.43% probability that no less than 92 out of 159 students will pass their college placement exams.

Step-by-step explanation:

I am going to use the binomial approximation to the normal to solve this question.

Binomial probability distribution

Probability of exactly x sucesses on n repeated trials, with p probability.

Can be approximated to a normal distribution, using the expected value and the standard deviation.

The expected value of the binomial distribution is:

E(X) = np

The standard deviation of the binomial distribution is:

\sqrt{V(X)} = \sqrt{np(1-p)}

Normal probability distribution

Problems of normally distributed samples can be solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the zscore of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

When we are approximating a binomial distribution to a normal one, we have that \mu = E(X), \sigma = \sqrt{V(X)}.

In this problem, we have that:

p = 0.55, n = 159. So

\mu = E(X) = 159*0.55 = 87.45

\sigma = \sqrt{V(X)} = \sqrt{np(1-p)} = \sqrt{159*0.55*0.45} = 6.27

Probability that no less than 92 out of 159 students will pass their college placement exams.

No less than 92 is more than 91, which is 1 subtracted by the pvalue of Z when X = 91. So

Z = \frac{X - \mu}{\sigma}

Z = \frac{91 - 87.45}{6.27}

Z = 0.57

Z = 0.57 has a pvalue of 0.7157

1 - 0.7157 = 0.2843

0.2843 = 28.43% probability that no less than 92 out of 159 students will pass their college placement exams.

5 0
3 years ago
A car is traveling at a speed of 75 km/h. compute the speed of the car in m/s.
MaRussiya [10]
1 km = 1000 m
1 h = 3600 s

75 km/h
75 *1000 m / 3600 s
75 * 5 m / 18 s
25 * 5 m / 6 s
125 m / 6 s
20.8 m/s

answer is c.
6 0
2 years ago
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