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hjlf
3 years ago
5

write the equation of a line in slope intercept form that has a slope of 2/7 and has a y-intercept of 9

Mathematics
1 answer:
Rama09 [41]3 years ago
4 0

Answer:

y=2/7x+9

Step-by-step explanation:

Slope-intercept form is written y=mx+b.

y= also known as f(x), and is always by itself in slope-intercept form.

m= the slope.

x= the variable written to the right of the slope.

b= the y-intercept.

We know that the slope is 2/7 and the y-intercept in the equation is 9. Therefore, we can plug these numbers into the equation. So...

y=2/7x+9

is the correct equation written in slope-intercept form.

Hope this helps!! Have an amazing day (^人^)

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Suppose that the world's current oil reserves is
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  A)  R = 1900 -24t

  B)  1684 billion barrels

  C) 79.17 years

Step-by-step explanation:

<h3>A)</h3>

Reserves start at 1900 billion barrels and decrease by 24 billion barrels each year. The value for t=0 is 1900; the value for t=1 is 24 less.

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<h3>B)</h3>

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Ricardo and Tammy practice putting golf balls. Ricardo makes 47% of his putts and Tammy makes 51% of her putts. Suppose that Ric
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Answer:

0.3821 = 38.21% probability that Ricardo makes a higher proportion of putts than Tammy.

Step-by-step explanation:

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

Normal probability distribution

When the distribution is normal, we use 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.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean \mu = p and standard deviation s = \sqrt{\frac{p(1-p)}{n}}

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By the Central Limit Theorem, we have that:

\mu_R = 0.47, s_R = \sqrt{\frac{0.47*0.53}{25}} = 0.0998

Tammy makes 51% of her putts, and attempts 30 putts.

By the Central Limit Theorem, we have that:

\mu_T = 0.51, s_T = \sqrt{\frac{0.51*0.49}{30}} = 0.0913

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This is the probability that the subtraction of R by T is larger than 0. The mean and standard deviation of this distribution are, respectively:

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1 - 0.6179 = 0.3821

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