The lateral area of the shape is the sum of the area of all lateral faces.
The area of the lateral face that is rectangle with sides 5 mi and 2 mi is
As you can see the shape has all four lateral faces of the same rectangular form with the same sides lengths, therefore,
Answer: correct choice is B.
Answer: 10 units²
Step-by-step explanation:
We can divide the shape along the y-axis to get 2 separate triangles. If we find the area of each and add them up, we can get the total area of the figure.
We can get each triangle's area using the formula
base length - 4 units
height - 4 units
base length - 2 units
height - 2 units
Total = 8 units² + 2 units² = 10 units²
Answer:
35.2% probability that the sample mean will be 246 pages or more
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 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 normally distributed random variable X, with mean and standard deviation
, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean
and standard deviation
.
For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.
In this question, we have that:
What the probability that the sample mean will be 246 pages or more?
This is 1 subtracted by the pvalue of Z when X = 246. So
By the Central Limit Theorem
has a pvalue of 0.6480.
1 - 0.6480 = 0.3520
35.2% probability that the sample mean will be 246 pages or more