What is the value of x?<br><br> Enter your answer in the box.

You lean a 30 foot ladder against your house and it reaches exactly to the top. The ladder makes a 24 degree angle with the grou

zhenek [66]

A right triangle is formed with the ladder as the hypotenuse. Since the angle made by the ladder with with ground is given, we can use trigonometric functions to solve for the height of the house.

If we let x be the height of the house and using sine function:
sin 24 = x/30
x = 30 sin 24
x = 12.20 ft

Therefore, the house is 12.20 ft tall

4 0

3 years ago

How do you write the rule for G(X)

zzz [600]

G(X) is used for < > sides in a square photo that represents two different numbers who hold the numerals of 0,0/1/2/3 etc… this square photo is most likely to use “Y” and “X” but the letters can be customized as they are just for holding

Still need more help of how this works?
“Y” represents “^” and “down”, “X” or G in this case is used for < >

Use ONE of these explanations to make this question I mostly recommend example.2 because it’s more briefly

mark brainliest if helped enough!
good luck!!!

4 0

3 years ago

A simple random sample of size equals 49 is obtained from a population with mu equals 88 and sigma equals 14. (a) Describe the

Gnoma [55]

Answer:

a) $\bar X \sim N(88,\frac{14}{\sqrt{49}}=2)$

b) $P(\bar X >91.2)=1-P(\bar X$

Step-by-step explanation:

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".

The central limit theorem states that "if we have a population with mean μ and standard deviation σ and take sufficiently large random samples from the population with replacement, then the distribution of the sample means will be approximately normally distributed. This will hold true regardless of whether the source population is normal or skewed, provided the sample size is sufficiently large".

The complement rule is a theorem that provides a connection between the probability of an event and the probability of the complement of the event. Lat A the event of interest and A' the complement. The rule is defined by: $P(A)+P(A') =1$