We want to get x by itself
First we will multiply both sides by 6 to cancel out the 6 on the left
5x = 120
We then divide by 5 on both sides to get x by itself
x = 24
Answer:
Step-by-step explanation:
x+y = 6
y = (6-x)
7x +12y = 52
7x+12(6-x) = 52
7x +72 -12x = 52
-5x = -20
x= 4 4 days at $7 = $28
2 days at $12 = $24
28+24 = 52
Let x represent the smaller angle. Then the larger one is 20+4x. Since they are complementary, their sum is 90. (All measures are degrees.)
90 = x + (20+4x)
90 = 5x +20
70 = 5x
14 = x
The smaller angle is 14°.
The larger angle is 76°.
The answer is a) equilateral triangle. If you want to inscribe a hexagon inside a circle, the tools or constructions that should be used is 6 equilateral triangles. If you draw a hexagon inscribed in a circle and draw radii to the corners of the hexagon, you will create triangles, six of them.<span>
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Answer:
Probability that the sample mean comprehensive strength exceeds 4985 psi is 0.99999.
Step-by-step explanation:
We are given that a random sample of n = 9 structural elements is tested for comprehensive strength. We know the true mean comprehensive strength μ = 5500 psi and the standard deviation is σ = 100 psi.
<u><em>Let </em></u>
<u><em> = sample mean comprehensive strength</em></u>
The z-score probability distribution for sample mean is given by;
Z =
~ N(0,1)
where,
= population mean comprehensive strength = 5500 psi
= standard deviation = 100 psi
The Z-score measures how many standard deviations the measure is away from the mean. After finding the Z-score, we look at the z-score table and find the p-value (area) 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.
Now, Probability that the sample mean comprehensive strength exceeds 4985 psi is given by = P(
> 4985 psi)
P(
> 4985 psi) = P(
>
) = P(Z > -15.45) = P(Z < 15.45)
= <u>0.99999</u>
<em>Since in the z table the highest critical value of x for which a probability area is given is x = 4.40 which is 0.99999, so we assume that our required probability will be equal to 0.99999.</em>