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stepladder [879]
3 years ago
6

Find the values of the six trigonometric functions for angle G.

Mathematics
2 answers:
EleoNora [17]3 years ago
6 0

Answers:

  • sin(G) = 3/5
  • cos(G) = 4/5
  • tan(G) = 3/4
  • csc(G) = 5/3
  • sec(G) = 5/4
  • cot(G) = 4/3

==============================================

Explanation:

For a right triangle, the sine of a reference angle is equal to the opposite over hypotenuse.

sin(angle) = opposite/hypotenuse

cosine involves adjacent over hypotenuse

cos(angle) = adjacent/hypotenuse

tangent involves opposite over adjacent

tan(angle) = opposite/hypotenuse

-----------------

In short, we have this list so far

  • sin(angle) = opposite/hypotenuse
  • cos(angle) = adjacent/hypotenuse
  • tan(angle) = opposite/hypotenuse

The other three trig functions are reciprocals of these first three. Cosecant is the reciprocal of sine, secant is the reciprocal of cosine, and cotangent is the reciprocal of tangent.

Meaning, the other three trig ratios are

  • csc(angle) = hypotenuse/opposite
  • sec(angle) = hypotenuse/adjacent
  • cot(angle) = adjacent/opposite

--------------------

So,

  • sin(G) = opposite/hypotenuse = FH/FG = 24/40 = 3/5
  • cos(G) = adjacent/hypotenuse = GH/FG = 32/40 = 4/5
  • tan(G) = opposite/adjacent = FH/GH = 24/32 = 3/4

and

  • csc(G) = hypotenuse/opposite = FG/FH = 40/24 = 5/3
  • sec(G) = hypotenuse/adjacent = FG/GH = 40/32 = 5/4
  • cot(G) = adjacent/opposite = GH/FH = 32/24 = 4/3
solmaris [256]3 years ago
6 0

Answer:

Step-by-step explanation:

Hope this helps u!!

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Answer:

a) By the Central Limit Theorem, it is approximately normal.

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To solve this question, we need to understand the normal probability distribution and the central limit theorem.

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Problems of normal distributions can be solved using the z-score formula.

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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.

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The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

Mean of 36 hours and a standard deviation of 5.5 hours.

This means that \mu = 36, \sigma = 5.5

a. What can you say about the shape of the distribution of the sample mean?

By the Central Limit Theorem, it is approximately normal.

b. What is the standard error of the distribution of the sample mean? (Round your answer to 4 decimal places.)

Sample of 9 means that n = 9. So

s = \frac{\sigma}{\sqrt{n}} = \frac{5.5}{\sqrt{9}} = 1.8333

The standard error of the distribution of the sample mean is 1.8333.

c. What proportion of the samples will have a mean useful life of more than 38 hours?

This is 1 subtracted by the pvalue of Z when X = 38. So

Z = \frac{X - \mu}{\sigma}

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

Z = \frac{38 - 36}{1.8333}

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Z = 1.09 has a pvalue of 0.8621

1 - 0.8621 = 0.1379

0.1379 = 13.79% of the samples will have a mean useful life of more than 38 hours.

d. What proportion of the sample will have a mean useful life greater than 34.5 hours?

This is 1 subtracted by the pvalue of Z when X = 34.5. So

Z = \frac{X - \mu}{s}

Z = \frac{34.5 - 36}{1.8333}

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0.8621 - 0.2061 = 0.656

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