Solve the proportion 15/6 = 10/p
2 answers:
Answer:
p = 4
Step-by-step explanation:
The usually recommended procedure for solving a proportion is to "cross multiply", then divide by the coefficient of the variable. (Solve the remaining one-step equation.)
<h3>Cross multiply</h3>This means multiply both sides of the equation by the product of the denominators:
(15/6)(6p) = (10/p)(6p) . . . . "cross multiply"
15p = 60 . . . . . . simplify
<h3>Second step</h3>Now, divide by the coefficient of the variable.
15p/15 = 60/15
p = 4
The solution is p = 4.
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<em>Additional comment</em>
If the variable is in the <em>numerator</em> of the proportion, using cross multiplication, you will find that you end up multiplying and dividing by the other denominator. To solve it in that case, you only need to multiply by the denominator under the variable.
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For example, to solve ...
2/5 = p/10
you only need to multiply by 10. You don't need to multiply by 50, then divide by 5.
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Any proportion can be written 4 ways:
This suggests another strategy: invert the whole proportion, then solve it as one with p in the numerator:
6/15 = p/10 ⇒ p = 10(6/15) = 4
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Answer:
0.1587 = 15.87% probability that the average fracture strength of 100 randomly selected pieces of this glass exceeds 14.2.
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 and standard deviation
, the z-score 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 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 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.
The fracture strength of tempered glass averages 14 (measured in thousands of pounds per square inch) and has standard deviation 2.
This means that
Sample of 100:
This means that
What is the probability that the average fracture strength of 100 randomly selected pieces of this glass exceeds 14.2?
This is 1 subtracted by the p-value of Z when X = 14.2. So
By the Central Limit Theorem
has a p-value of 0.8413.
1 - 0.8413 = 0.1587
0.1587 = 15.87% probability that the average fracture strength of 100 randomly selected pieces of this glass exceeds 14.2.