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daser333 [38]
3 years ago
8

In ΔKLM, the measure of ∠M=90°, KM = 40, LK = 41, and ML = 9. What ratio represents the tangent of ∠K?

Mathematics
1 answer:
melomori [17]3 years ago
5 0

Answer:

The ratio representing the tangent of ∠K is 40 : 9.

Step-by-step explanation:

Consider the right-angles triangle KLM below.

The angle M is 90°.

KM = perpendicular (<em>p</em>) = 40

ML = base (<em>b</em>) = 9

LK = hypotenuse (<em>h</em>) = 41

The tangent of an angle is the ratio of the perpendicular length to the length of the base.

Compute the tangent of ∠K as follows:

tan (K)=\frac{p}{b}=\frac{40}{9}

Thus, the ratio representing the tangent of ∠K is 40 : 9.

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25

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Find the vertex of the parabola whose equation is y=x^2+6x+2
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(-3, 2) because you take the derivative and youll get y'=2x+6 then solve for x and that is -3 then put -3 in the original equation and you get 2
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A. Economic theory describes the relationship between inflation and unemployment as:
Ludmilka [50]

Answer:

1: The correction option is B) Negative

Explanation

In economic theory, the Philips curve depicts the relationship between unemployment and inflation as a negative one. In order words, when inflation goes up, unemployment reduces.

The logic behind that thinking is, that inflation, which is the general increase in prices of goods/commodities and services is good for business. Business owners are quick to adjust to higher prices regardless of how it is induced and sometimes even profit from it in sectors not affected by inflation. So in such sectors, as business improves,  it is assumed that there is a requirement to being in more hands to help with the expansion of the business.

2. The correct option is B) Holds for certain time periods

Explanation

Social scientists and researchers have plotted the data across various periods (20 years) using data from the US economy.

The following results emerged:

  • the traditional relationship between inflation and unemployment held in 2001 during the mild recession triggered by the 9/11 situation. Unemployment took an upward spiral averaging an increase of 6% while inflation nosedived by 2.5%;
  • Another snapshot was taken in the mid-2000s. This time unemployment went belly-up by several degrees, while inflation took off in the opposite direction by almost 5% before receding in 2006 when unemployment bottomed;
  • In another analysis, the consumer price index took a steep downward dive during the Great Recession. This time, unemployment took a bullish charge, going up as much as 10%
  • This negative relationship failed to hold between 2012 to 2015. Both factors developed a positive relationship and moved in the same direction;
  • There has also been a loss of strength in the negative relationship as also seen in recent times. Specifically, between 2016 to 2019 where unemployment has steadily receded to 50-year lows, with inflation remained steady at an average of 2%.  

So the correct answer is B.

3. The correct answer is True:

Explanation

As seen from the analysis above, the negative relationship remains largely true for most of the periods examined. Hence it is more pragmatic to expect a dip in unemployment whenever there is a spike in the CPI.

Cheers

6 0
3 years ago
A random sample of 300 circuits generated 13 defectives. Use the data to test the hypothesis Upper H Subscript 0 Baseline colon
____ [38]

Complete Question

A random sample of 300 circuits generated 13 defectives. a. Use the data to test

                            H_o : p = 0.05

Versus

 

                          H_1 : p \ne 0.05

Use α = 0.05. Find the P-value for the test

   

Answer:

The  p-value is  p-value =  0.5949        

Step-by-step explanation:

From the question we are told that

  The sample size is  n = 300

    The number of defective circuits is  k = 13

Generally the sample proportion of defective circuits is mathematically represented as

        \^ p = \frac{k}{n}

=>     \^ p = \frac{13}{300}

=>     \^ p = 0.0433

Generally the standard Error is mathematically represented as

       SE  = \sqrt{\frac{p(1- p)}{n} }

=>     SE  = \sqrt{\frac{0.05(1- 0.05)}{300} }

=>     SE  = 0.0126

Generally the test statistics is mathematically represented as

       z =  \frac{\^ p - p }{SE}

=>     z =  \frac{0.0433 - 0.05 }{0.0126}

=>     z =  -0.5317

From the z table  the area under the normal curve to the left  corresponding to  -0.5317  is

         (P < -0.5317 ) = 0.29747

Generally the p-value is mathematically represented as

       p-value =  2 * P(Z <  -0.5317 )

=>     p-value =  2 * 0.29747

=>     p-value =  0.5949        

     

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