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olga nikolaevna [1]
3 years ago
11

Evaluate the limit of lim/n->infinity 6n^2+5/3n^2

Mathematics
2 answers:
castortr0y [4]3 years ago
6 0

we are given

\lim_{n \to \infty} \frac{6n^2+5}{3n^2}

we can see that

degree of numerator = degree of denominator =2

so, we can divide both numerator and denominator by n^2

and we get

\lim_{n \to \infty} \frac{(6n^2+5)/n^2}{(3n^2/n^2)}

\lim_{n \to \infty} \frac{(6n^2/n^2)+(5/n^2)}{(3n^2/n^2)}

now, we can simplify it

\lim_{n \to \infty} \frac{6+(5/n^2)}{3}

now, we can plug n=inf

=  \frac{6+(5/(\infty))}{3}

=  \frac{6+0}{3}

=  \frac{6}{3}

=  2...............Answer

nikdorinn [45]3 years ago
5 0

\displaystyle \lim_{n\to \infty} \dfrac{6n^2+5}{3n^2 }=\\\\ \lim_{n\to \infty} \dfrac{n^2\left(6+\dfrac{5}{n^2}\right)}{3n^2 }=\\\\ \lim_{n\to \infty} \dfrac{6+\dfrac{5}{n^2}}{3}=\\\\ \dfrac{6+0}{3}=2

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Answer:

Given a square ABCD and an equilateral triangle DPC and given a chart with which Jim is using to prove that triangle APD is congruent to triangle BPC.

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Suppose that the population mean for income is $50,000, while the population standard deviation is 25,000. If we select a random
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Answer:

Probability that the sample will have a mean that is greater than $52,000 is 0.0057.

Step-by-step explanation:

We are given that the population mean for income is $50,000, while the population standard deviation is 25,000.

We select a random sample of 1,000 people.

<em>Let </em>\bar X<em> = sample mean</em>

The z-score probability distribution for sample mean is given by;

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            n = sample of people = 1,000

The Z-score measures how many standard deviations the measure is away from the mean. After finding the Z-score, we look at the z-score table and find the p-value (area) 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.

So, probability that the sample will have a mean that is greater than $52,000 is given by = P(\bar X > $52,000)

  P(\bar X > $52,000) = P( \frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } } > \frac{52,000-50,000}{\frac{25,000}{\sqrt{1,000} } } ) = P(Z > 2.53) = 1 - P(Z \leq 2.53)

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<em>Now, in the z table the P(Z </em>\leq<em> x) or P(Z < x) is given. So, the above probability is calculated by looking at the value of x = 2.53 in the z table which has an area of 0.9943.</em>

Therefore, probability that the sample will have a mean that is greater than $52,000 is 0.0057.

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