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Allushta [10]
3 years ago
7

write the equation of the line (in slope-intercept form) that passes through the points (2,3 and (5,7)

Mathematics
1 answer:
AfilCa [17]3 years ago
8 0

Answer:

The answer to your question is    y = 4/3x + 1/3

Step-by-step explanation:

Data

Point A = (2, 3)

Point B = (5, 7)

Process

1.- Calculate the slope

x1 = 2    y1 = 3

x2 = 5    y2 = 7

m = (y2 - y1)/(x2 - x1)

- Substitution

  m = (7 - 3)/(5 - 2)

- Slope

  m = 4/3

2.- Find the equation of the line

     y - y1 = m(x - x1)

     y - 3 = 4/3(x - 2)

     y - 3 = 4/3x - 8/3

     y = 4/3x - 8/3 + 3

     y = 4/3x - 8/3 + 9/3

     y = 4/3x + 1/3

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Step-by-step explanation:

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Of the total population of American households, including older Americans and perhaps some not so old, 17.3% receive retirement
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Answer:

47.54% probability that more than 20 households but fewer than 35 households receive a retirement income

Step-by-step explanation:

We use the binomial aproxiation to the normal to solve this question.

Binomial probability distribution

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

The expected value of the binomial distribution is:

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The standard deviation of the binomial distribution is:

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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 = 0.173, n = 120. So

\mu = E(X) = np = 120*0.173 = 20.76

\sigma = \sqrt{V(X)} = \sqrt{np(1-p)} = \sqrt{120*0.173*0.827} = 4.14

In a random sample of 120 households, what is the probability that more than 20 households but fewer than 35 households receive a retirement income?

We are working with discrete values, so this is the pvalue of Z when X = 35-1 = 34 subtracted by the pvalue of Z when X = 20 + 1 = 21.

X = 34

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

Z = \frac{34 - 20.76}{4.14}

Z = 3.2

Z = 3.2 has a pvalue of 0.9993

X = 21

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

Z = \frac{21 - 20.76}{4.14}

Z = 0.06

Z = 0.06 has a pvalue of 0.5239

0.9993 - 0.5239 = 0.4754

47.54% probability that more than 20 households but fewer than 35 households receive a retirement income

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Answer:

y = 42

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i think

7 0
3 years ago
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