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Ray Of Light [21]

2 years ago

12

Felicia worked at the library for three months. She earned $4,500 and must pay a total of 15% in taxes. How much money will Feli

cia have to pay in income taxes?

2 answers:

valentina_108 [34]2 years ago

7 0

Answer:

150

Step-by-step explanation:

MakcuM [25]2 years ago

7 0

Answer: 675, I believe.

Explanation: 15% of 4500 is 675. Correct me if I'm wrong, since I haven't had to do math in awhile lol

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Here's what we know, numbers are rounded. 1.It takes 8 minutes for light to reach Earth from the sun. 2. The distance from the s

VMariaS [17]

<span>forth to the sun is 1 light-year</span>

6 0

3 years ago

The angles of elevation froma point X to the top of flagpoles A and B are 35* and 45* respectively. If X lies in the middle of t

BartSMP [9]

Let AB = t. And since X lies in the middle, so AX=BX = t/2 .

Let the height of the smaller flagpole is AO and of larger flagpole is BP .

Using tangent ratio rule in each triangle, we will get

$tan 35 =\frac{AO}{t/2} , tan 45= \frac{BP}{t/2} // AO = \frac{t*tan35}{2}, BP=\frac{t*tan45}{2}$

And there ratio is

$\frac{AO}{BP}= \frac{tan 35}{tan 45}=\frac{0.7}{1}$

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3 years ago

Which angles equal 91°? angles T and V angles S and U angles U and V angles S and T.

Ahat [919]

Answer:

Angles T and V

Step-by-step explanation:

5 0

2 years ago

The random variable X is exponentially distributed, where X represents the waiting time to be seated at a restaurant during the

erastova [34]

Answer:

The probability that the wait time is greater than 14 minutes is 0.4786.

Step-by-step explanation:

The random variable <em>X</em> is defined as the waiting time to be seated at a restaurant during the evening.

The average waiting time is, <em>β</em> = 19 minutes.

The random variable <em>X</em> follows an Exponential distribution with parameter $\lambda=\frac{1}{\beta}=\frac{1}{19}$ .

The probability distribution function of <em>X</em> is:

$f(x)=\lambda e^{-\lambda x};\ x=0,1,2,3...$

Compute the value of the event (<em>X</em> > 14) as follows:

$P(X>14)=\int\limits^{\infty}_{14} {\lambda e^{-\lambda x}} \, dx=\lambda \int\limits^{\infty}_{14} {e^{-\lambda x}} \, dx\\=\lambda |\frac{e^{-\lambda x}}{-\lambda}|^{\infty}_{14}=e^{-\frac{1}{19} \times14}-0\\=0.4786$

Thus, the probability that the wait time is greater than 14 minutes is 0.4786.

7 0

3 years ago

If you have never seen 2 pretty best-friends, how many best-friends are ugly?

Natalka [10]

Answer:

1

Step-by-step explanation:

one gotta be ugly

6 0

3 years ago

Read 2 more answers