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erik [133]
3 years ago
8

7. If the longer leg of a right triangle is twice as long as the shorter leg, what is the ratio of

Mathematics
1 answer:
kicyunya [14]3 years ago
5 0

Answer: The ratio is 2.39, which means that the larger acute angle is 2.39 times the smaller acute angle.

Step-by-step explanation:

I suppose that the "legs" of a triangle rectangle are the cathati.

if L is the length of the shorter leg, 2*L is the length of the longest leg.

Now you can remember the relation:

Tan(a) = (opposite cathetus)/(adjacent cathetus)

Then there is one acute angle calculated as:

Tan(θ)  =  (shorter leg)/(longer leg)

Tan(φ) = (longer leg)/(shorter leg)

And we want to find the ratio between the measure of the larger acute angle and the smaller acute angle.

Then we need to find θ and φ.

Tan(θ) = L/(2*L)

Tan(θ) = 1/2

θ = Atan(1/2) = 26.57°

Tan(φ) = (2*L)/L

Tan(φ) = 2

φ = Atan(2) = 63.43°

Then the ratio between the larger acute angle and the smaller acute angle is:

R = (63.43°)/(26.57°) = 2.39

This means that the larger acute angle is 2.39 times the smaller acute angle.

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What is the discontinuity and zero of the function f(x) = the quantity of 3 x squared plus x minus 4, all over x minus 1? A. Dis
Firlakuza [10]

Answer:

The correct option is D. Discontinuity at (1, 7), zero at (negative four thirds, 0)  

Step-by-step explanation:

\text{The function is given to be : }f(x)=\frac{3x^2+x-4}{x-1}\\\\\implies f(x)=\frac{(3x+4)(x-1)}{(x-1)}

To find the point of discontinuity :

Put the denominator equal to 0

⇒ x - 1 = 0

⇒ x = 1

Also, if the factor (x - 1) gets cancel, then it becomes a hole rather than a asymptote , ⇒ y = 3x + 4 at x = 1

⇒ y = 7

So, Point of discontinuity : (1, 7)

And the zero is : after cancelling the factor (x - 1) put the remaining factor = 0

⇒ 3x + 4 = 0

⇒ 3x = -4

⇒ x = negative four thirds ( zero of the function)

Therefore, The correct option is D. Discontinuity at (1, 7), zero at (negative four thirds, 0)

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How does the definition of the prefixes mono-,bi-, and tri- help when naming polynomials
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Answer:

They let you know the number of numbers there are/will be.

Step-by-step explanation:

Mono, being one, means there will only be one number is the equation.

Bi, being two, means there will be two numbers in the equation.

and tri, being three, means there are three numbers in the equation.

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2. The time between engine failures for a 2-1/2-ton truck used by the military is
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Answer:

A truck "<em>will be able to travel a total distance of over 5000 miles without an engine failure</em>" with a probability of 0.89435 or about 89.435%.

For a sample of 12 trucks, its average time-between-failures of 5000 miles or more is 0.9999925 or practically 1.

Step-by-step explanation:

We have here a <em>random variable</em> <em>normally distributed</em> (the time between engine failures). According to this, most values are around the mean of the distribution and less are far from it considering both extremes of the distribution.

The <em>normal distribution</em> is defined by two parameters: the population mean and the population standard deviation, and we have each of them:

\\ \mu = 6000 miles.

\\ \sigma = 800 miles.

To find the probabilities asked in the question, we need to follow the next concepts and steps:

  1. We will use the concept of the <em>standard normal distribution</em>, which has a mean = 0, and a standard deviation = 1. Why? With this distribution, we can easily find the probabilities of any normally distributed data, after obtaining the corresponding <em>z-score</em>.
  2. A z-score is a kind of <em>standardized value</em> which tells us the <em>distance of a raw score from the mean in standard deviation units</em>. The formula for it is: \\ z = \frac{x - \mu}{\sigma}. Where <em>x</em> is the value for the raw score (in this case x = 5000 miles).
  3. The values for probabilities for the standard normal distribution are tabulated in the <em>standard normal table</em> (available in Statistics books and on the Internet). We will use the <em>cumulative standard normal table</em> (see below).

With this information, we can solve the first part of the question.

The chance that a truck will be able to travel a total distance of over 5000 miles without an engine failure

We can "translate" the former mathematically as:

\\ P(x>5000) miles.

The z-score for x = 5000 miles is:

\\ z = \frac{5000 - 6000}{800}

\\ z = \frac{-1000}{800}

\\ z = -1.25

This value of z is negative, and it tells us that the raw score is 1.25 standard deviations <em>below</em> the population mean. Most standard normal tables are made using positive values for z. However, since the normal distribution is symmetrical, we can use the following formula to overcome this:

\\ P(z

So

\\ P(z

Consulting a standard normal table available on the Internet, we have

\\ P(z

Then

\\ P(z1.25)

\\ P(z1.25)

However, this value is for P(z<-1.25), and we need to find the probability P(z>-1.25) = P(x>5000) (Remember that we standardized x to z, but the probabilities are the same).

In this way, we have

\\ P(z>-1.25) = 1 - P(z

That is, the complement of P(z<-1.25) is P(z>-1.25) = P(x>5000). Thus:

\\ P(z>-1.25) = 1 - 0.10565

\\ P(z>-1.25) = 0.89435  

In words, a truck "<em>will be able to travel a total distance of over 5000 miles without an engine failure</em>" with a probability of 0.89435 or about 89.435%.

We can see the former probability in the graph below.  

The chance that a fleet of a dozen trucks will have an average time-between-failures of 5000 miles or more

We are asked here for a sample of <em>12 trucks</em>, and this is a problem of <em>the sampling distribution of the means</em>.

In this case, we have samples from a <em>normally distributed data</em>, then, the sample means are also normally distributed. Mathematically:

\\ \overline{x} \sim N(\mu, \frac{\sigma}{\sqrt{n}})

In words, the samples means are normally distributed with the same mean of the population mean \\ \mu, but with a standard deviation \\ \frac{\sigma}{\sqrt{n}}.

We have also a standardized variable that follows a standard normal distribution (mean = 0, standard deviation = 1), and we use it to find the probability in question. That is

\\ z = \frac{\overline{x} - \mu}{\frac{\sigma}{\sqrt{n}}}

\\ z \sim N(0, 1)

Then

The "average time-between-failures of 5000" is \\ \overline{x} = 5000. In other words, this is the mean of the sample of the 12 trucks.

Thus

\\ z = \frac{\overline{x} - \mu}{\frac{\sigma}{\sqrt{n}}}

\\ z = \frac{5000 - 6000}{\frac{800}{\sqrt{12}}}

\\ z = \frac{-1000}{\frac{800}{\sqrt{12}}}

\\ z = \frac{-1000}{230.940148}

\\ z = -4.330126

This value is so low for z, that it tells us that P(z>-4.33) is almost 1, in other words it is almost certain that for a sample of 12 trucks, its average time-between-failures of 5000 miles or more is almost 1.

\\ P(z

\\ P(z

\\ P(z

The complement of P(z<-4.33) is:

\\ P(z>-4.33) = 1 - P(z or practically 1.

In conclusion, for a sample of 12 trucks, its average time-between-failures of 5000 miles or more is 0.9999925 or practically 1.

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Step-by-step explanation: what are the dimensions

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