Please help!! Greatly appreciated <3

I DO NOT UNDERSTAND SOMEONE PLEASE HELP

sammy [17]

Answer:

a = 12cm

Third option

Step-by-step explanation:

Use the pythagorean theorem because this is a right triangle and you are looking for a missing side.

The formula is:

a² + b² = c², where "a" and "b" are sides, but "c" is the hypotenuse (longest side).

We know the hypotenuse and one other side.

Substitute side "b" and "c".

a² + 5² = 13²

a² + 25 = 169 Isolate "a"

a² = 169 - 25 Subtract 25 from both sides

a² = 144 Find the square root of both sides

a = √144

a = 12

The mssing side, "a", is 12 cm long.

8 0

3 years ago

if the population of a country increases by 35% every decade by what percentage does it increase by every year

VikaD [51]

Answer:

hi

have a good day for you

7 0

3 years ago

According to 2013 report from Population Reference Bureau, the mean travel time to work of workers ages 16 and older who did not

gregori [183]

Answer:

a) 48.80% probability that his travel time to work is less than 30 minutes

b) The mean is 30.7 minutes and the standard deviation is of 3.83 minutes.

c) 13.13% probability that in a random sample of 36 NJ workers commuting to work, the mean travel time to work is above 35 minutes

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 $s = \frac{\sigma}{\sqrt{n}}$ .