Given: MPNA pyramid All edges congruent AO = 36, AO ⊥ (MNP) Find: m∠AMO, AΔANM
1 answer:
Answer:
m∠AMO ≈ 54.7°
AΔANM = 486√3
Step-by-step explanation:
The edges are congruent, so all four faces are congruent equilateral triangles. We'll say the length of each edge is 2r.
The height of the pyramid h is given to be 36.
The perpendicular distance from O to line MP is called the apothem (a). Using 30-60-90 triangles, b = 2a and r = a√3.
Use cosine to find m∠AMO.
cos(∠AMO) = b / (2r)
cos(∠AMO) = (2a) / (2a√3)
cos(∠AMO) = 1 / √3
m∠AMO ≈ 54.7°
Use Pythagorean theorem to find the apothem.
(2r)² = b² + h²
(2a√3)² = (2a)² + 36²
12a² = 4a² + 1296
8a² = 1296
a² = 162
a = 9√2
So the edge length is:
2r = 2√3 (9√2)
2r = 18√6
The area of the equilateral triangle ΔANM is half the apothem times the perimeter:
A = ½aP
A = ½ (9√2) (3 × 18√6)
A = 243√12
A = 486√3
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Answer:
11.51% probability that the sample average will be less than 182
Step-by-step explanation:
To solve this question, we have 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 and standard deviation
, the zscore of a measure X is given by:
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 random variable X, with mean and standard deviation
, a large sample size can be approximated to a normal distribution with mean
and standard deviation
In this problem, we have that:
What is the probability that the sample average will be less than 182
This is the pvalue of Z when X = 182. So
By the Central Limit Theorem
has a pvalue of 0.1151
11.51% probability that the sample average will be less than 182