Please help extra points

40 pts and Brainliest pls give detailed answer :)

horsena [70]

Answer:

58 ft

Step-by-step explanation:

So I attached a diagram that illustrates the triangle that is formed. We know an angle, as well as the hypotenuse. We are looking for the height, or in other words the opposite side of the angle. There is a trigonometric function defined as: $sin(\theta) = \frac{opposite}{hypotenuse}$ . Using this we can plug in known values and solve for the opposite side, which I'll simply represent as x.

$sin(46) = \frac{x}{80}$

Multiply both sides by 80

$sin(46) * 80 = x$

Calculate sin(46) using a calculator (make sure it's in degree mode)

$0.7193398 * 80 = x$

Simplify

$57.547 \approx x$

Round this to the nearest foot

$58 \approx x$

4 0

2 years ago

Please help What is the value of x? A:12 B:15 C: 6 D: 30

pickupchik [31]

Answer: A, 12

Step-by-step explanation:

The line in the middle is a midsegment, making the two triangles similar by a ratio of two. So, dividing 60 by five will give you twelve

4 0

3 years ago

The mean height of women in a country (ages 20-29) is 64 4 inches A random sample of 50 women in this age group is selected What

Simora [160]

Answer:

0.0721 = 7.21% probability that the mean height for the sample is greater than 65 inches.

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