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Over [174]
3 years ago
11

(a) The area of a rectangular parking lot is 7802 m².

Mathematics
1 answer:
Serhud [2]3 years ago
4 0

Answer:

A) Length = 94 m

B) Width = 79 m

Step-by-step explanation:

A)

The area of a parking lot is 7802 m²

Area = length x width

7802 = length x 83

length = 7802 ÷ 83

length = 94 m

b)

The perimeter of a pool is 353 m

Perimeter = 2(length + width)

352 = 2(97 + width)

352 = 194 + 2width

2width = 352 - 194

2width = 158

width = 158/2

width = 79 m

-Chetan K

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Burka [1]

Answer:

  (c)  y < x^2 -5x

Step-by-step explanation:

A quadratic inequality is one that involves a quadratic polynomial.

<h3>Identification</h3>

The degree of a polynomial is the value of the largest exponent of the variable. When the degree of a polynomial is 2, we call it a <em>quadratic</em>.

For the following inequalities, the degree of the polynomial in x is shown:

  • y < 2x +7 . . . degree 1
  • y < x^3 +x^2 . . . degree 3
  • y < x^2 -5x . . . degree 2 (quadratic)

<h3>Application</h3>

We see that the degree of the polynomial in x is 2 in ...

   y < x^2 -5x

so that is the quadratic inequality you're looking for.

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<em>Additional comment</em>

When a term involves only one variable, its degree is the exponent of that variable: 5x^3 has degree 3. When a term involves more than one variable, the degree of the term is the sum of the exponents of the variables: 8x^4y3 has degree 4+3=7.

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2 years ago
2<br> y + 7 = 5(x - 3)<br> What is the standard form for this?
lesya [120]

Answer:

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Step-by-step explanation:

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3 years ago
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Step-by-step explanation:

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Answer:

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Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal probability distribution:

Problems of normally distributed samples are 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.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

In this problem, we have that:

\mu = 111.4, \sigma = 0.5, n = 23, s = \frac{0.5}{\sqrt{23}} = 0.1043

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Z = 0

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X = 111.2

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

Z = \frac{111.2 - 111.4}{0.1043}

Z = -1.92

Z = -1.92 has a pvalue of 0.0274.

0.5 - 0.0274 = 0.4726

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