<span>In
the fairest school 20% are below 16 years old
1/3 are teachers which is equals to = 21
Let’s start solving:
=> 1/3 of 100% = ( 100 / 3 = 33.33% )
thus 33.33% = 21
=> 21 x 3 = 63, is the total number of people in the school.
Let’s try solving the number of people below 16 years old
Then there are 20% of it:
=> 63 * .20 = 12.6
Thus, there are around 13 people who are 16 years old younger.</span>
Mean: average of the numbers. Add them up, divide by how many numbers/entries there are.
-2 + -1 + 0 + 0 + 0 + 0 + 2 + 4 = 3
3 divided by 8 = 0.375
Your mean is 0.375
Median: write the data in numerical order, find the middle number.
-2, -1, 0, 0, 0, 0, 2, 4
In this data set, there are an even number of entries, so we average the middle two numbers. Thankfully, here, the middle two are the same, so your median is 0.
Mode: the number that appears the most often in the data set
Your mode is also 0, because there are more zeroes than any other number in the data set.
Range: the distance on a number line between the highest and lowest number.
The distance between -2 and 4 is 6.4 - (-2) = 6
Please LMK if you have questions
Answer:
11x + 12
Step-by-step explanation:
9x + 3x = 11x
8 + 4 = 12
Answer:
1963.2 pounds (lbs.)
Step-by-step explanation:
Things to understand before solving:
- - <u>Normal Probability Distribution</u>
- The z-score formula can be used to solve normal distribution problems. In a set with mean ц and standard deviation б, the z-score of a measure X is given by:

The Z-score reflects how far the measure deviates from the mean. After determining the Z-score, we examine the z-score table to determine the p-value associated with this z-score. This p-value represents the likelihood that the measure's value is less than X, or the percentile of X. Subtracting 1 from the p-value yields the likelihood that the measure's value is larger than X.
- - <u>Central Limit Theorem</u>
- The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean ц and standard deviation б , the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean ц and standard deviation

As long as n is more than 30, the Central Limit Theorem may be applied to a skewed variable. A specific kind of steel cable has an average breaking strength of 2000 pounds, with a standard variation of 100 pounds.
This means, ц = 2000 and б = 100.
A random sample of 20 cables is chosen and tested.
This means that n = 20, 
Determine the sample mean that will exclude the top 95 percent of all size 20 samples drawn from the population.
This is the 100-95th percentile, or X when Z has a p-value of 0.05, or X when Z = -1.645. So 
- By the Central Limit Theorem


<h3>Answer:</h3>
The sample mean that will cut off the top 95% of all size 20 samples obtained from the population is 1963.2 pounds.