a distribution has the five number summary shown below. what is the range of the distriution? 14,46,52,67,85

C) Millennium Park has an outdoor concert theater. Before a concert, the area reserved for special seating is roped off in the s

Trava [24]

Answer:

The converse of Pythagorean Theorem states:

If the square length of the longes side of a triangle is equal to the sum of the squares of the other two sides, then it's a right triangle.

We use the converse of Pythagorean Theorem to prove that a triangle is a right triangle. It's like the inverse use of the theorem. Often, this theorem is used to find the length of a side of a triangle when we already know it's a right triangle. However, when we don't know that is a right triangle, we use the converse to prove it.

Step-by-step explanation:

I did it Edge 2021. Good Luck:)<3

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3 years ago

In a certain section of Southern California, the distribution of monthly rent for a one-bedroom apartment has a mean of $2,275 a

KATRIN_1 [288]

Answer:

100% probability of selecting a sample of 65 one-bedroom apartments and finding the mean to be at least $2,095 per month

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 normal distributions can be solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the z-score 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 p-value, 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 $s = \frac{\sigma}{\sqrt{n}}$ .