Suppose that 45% of students in a college have a smart phone. If you select three students at random, what is the probability that all three have a smart phone? Give your answer as a decimal (to at least 3 places) or fraction

Answer:

He served as Assistant Secretary of the Navy under President William McKinley

hope i helped

-lvr

Answer:

please see the attached picture for full solution

Hope it helps

Good luck on your assignment

Answer:

39

Step-by-step explanation:

12+20+22+22+23=99

new mean=23

23*6=138

138-99=39

Answer:

Step-by-step explanation:

Area of the circular zone = [tex]\pi[/tex]r^2

= 3.14 × 40^2 = 3.14 × 1600 = 5024 m^2

Area of the basketball court = l × b

= 30 × 15 = 450 m^2

Area of the trapezium shaped park =  ( 6 + 4 ) 3.5 / 2

= 35/2 = 17.5 m^2

∴ Area left in the circular zone = Area of the circular zone - ( Area of the basketball court + Area of the trapezium shaped park )

= 5024 - ( 450 + 17.5 )

= 5024 - 467.5

= 4556.5 m^2

hope this helps

plz mark it as brainliest!!!!!!!

Answer:

2 total roots

x = -1/3, 3/4

Step-by-step explanation:

We can use the discriminant b² - 4ac to find how many roots a polynomial has.

Answer:

Step-by-step explanation:

Edginuity 2021

Answer: Undefined

Step-by-step explanation:

For this problem, we know that 3ˣ=-9. All we have to do is figure out what x is.

We know that any integer raised to the power cannot be negative. The closest answer we can get is x=2 because 3²=9. Unfortunately, we are looking for -9. Therefore, this x is undefined.

Answer:

Nothing can be further done to this equation. It has been simplified all the way.

Answer:

20 x 20 grid = 1066.67 cm wire

Step-by-step explanation:

Using unitary method

9 grid = 24 cm wire

1 grid = [tex]\frac{24}{9}[/tex] cm wire

Multiplying both sides by 400 (20 x 20)

400 grid = [tex]\frac{24}{9} * 400[/tex] cm

20 x 20 grid = 1066.67 cm wire

Answer:

the correct answer is

Step-by-step explanation:

So, the probability is:P(greater than 4)=26=13. This is a theoretical probability, which is the observed number of favorable outcomes out of a certain number of trials. For instance, suppose you rolled the six-sided die five times, and got the following results:2,6,4,5,6

hope this help you!!!!!

Answer:

1/5 chance.

Step-by-step explanation:

There is only one number, 5, that is greater than 4 and there are 5 total numbers so there is a 1/5 chance selecting that number.

Step-by-step explanation:

I will do 12 and 14 as examples.

12) Angles of a triangle add up to 180°.

m∠P + m∠Q + m∠R = 180

5x − 14 + x − 5 + 2x − 9 = 180

8x − 28 = 180

8x = 208

x = 26

m∠P = 5x − 14 = 116

m∠Q = x − 5 = 21

m∠R = 2x − 9 = 43

14) If two sides of a triangle are equal, then the angles opposite those sides are also equal.

(Conversely, if two angles are equal, then the sides opposite those angles are also equal.  Such a triangle is called an isosceles triangle.)

BC ≅ BD, so m∠C = m∠D.

5x − 19 = 2x + 14

3x = 33

x = 11

m∠B = 13x − 35 = 108

m∠C = 5x − 19 = 36

m∠D = 2x + 14 = 36

Answer:

The sample correlation coefficient is, r = 0.8722.

The equation of the least-squares line is:

[tex]y= -0.161+0.154x[/tex]

Step-by-step explanation:

(a)

The scatter diagram displaying the data for X : total number of jobs in a given neighborhood and Y : number of entry-level jobs in the same neighborhood is shown below.

(b)

The table attached below verifies the values of [tex]\sum X,\ \sum Y,\ \sum X^{2},\ \sum Y^{2}\ \text{and}\ \sum XY[/tex].

The sample correlation coefficient is:

[tex]\begin{aligned}r~&=~\frac{n\cdot\sum{XY} - \sum{X}\cdot\sum{Y}} {\sqrt{\left[n \sum{X^2}-\left(\sum{X}\right)^2\right] \cdot \left[n \sum{Y^2}-\left(\sum{Y}\right)^2\right]}} \\r~&=~\frac{ 6 \cdot 1163 - 201 \cdot 30 } {\sqrt{\left[ 6 \cdot 7759 - 201^2 \right] \cdot \left[ 6 \cdot 182 - 30^2 \right] }} \approx 0.8722\end{aligned}[/tex]

Thus, the sample correlation coefficient is, r = 0.8722.

(c)

The slope and intercept are:

[tex]\begin{aligned} a &= \frac{\sum{Y} \cdot \sum{X^2} - \sum{X} \cdot \sum{XY} }{n \cdot \sum{X^2} - \left(\sum{X}\right)^2} = \frac{ 30 \cdot 7759 - 201 \cdot 1163}{ 6 \cdot 7759 - 201^2} \approx -0.161 \\ \\b &= \frac{ n \cdot \sum{XY} - \sum{X} \cdot \sum{Y}}{n \cdot \sum{X^2} - \left(\sum{X}\right)^2} = \frac{ 6 \cdot 1163 - 201 \cdot 30 }{ 6 \cdot 7759 - \left( 201 \right)^2} \approx 0.154\end{aligned}[/tex]

The equation of the least-squares line is:

[tex]y= -0.161+0.154x[/tex]

(d)

The least-squares line is graphed in the diagram below.

Answer: The distance of the shortest route of return is 400

Step-by-step explanation:

The direction of travel of the plane forms a right angle triangle ABC as shown in the attached photo. C represents the starting point of the plane. To determine the distance of the shortest by which the plane can return to its starting point, BC, we would apply the Pythagorean theorem which is expressed as

Hypotenuse² = opposite side² + adjacent side²

BC² = 320² + 240²

BC² = 160000

BC = √160000

BC = 400

Answer:

44.43% probability that among 40 adults (ages 70 and older) chosen at random more than 22 percent will have been told by their doctor that they have cancer

Step-by-step explanation:

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

Normal probability distribution

When the distribution is normal, we use the z-score formula.

In a set with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the zscore of a measure X is given by:

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

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 pvalue, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

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

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

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean [tex]\mu = p[/tex] and standard deviation [tex]s = \sqrt{\frac{p(1-p)}{n}}[/tex]

In this question, we have that:

[tex]p = 0.211, n = 40[/tex]

So

[tex]\mu = 0.211, s = \sqrt{\frac{0.211*0.789}{40}} = 0.0645[/tex]

What is the probability that among 40 adults (ages 70 and older) chosen at random more than 22 percent will have been told by their doctor that they have cancer

This is 1 subtracted by the pvalue of Z when X = 22. So

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

By the Central Limit Theorem

[tex]Z = \frac{X - \mu}{s}[/tex]

[tex]Z = \frac{0.22 - 0.211}{0.0645}[/tex]

[tex]Z = 0.14[/tex]

[tex]Z = 0.14[/tex] has a pvalue of 0.5557

1 - 0.5557 = 0.4443

44.43% probability that among 40 adults (ages 70 and older) chosen at random more than 22 percent will have been told by their doctor that they have cancer

Answer:

The calculated  value Z = 3.775 > 1.96 at 0.05 level of significance

Null hypothesis is rejected

The Two Population proportion are not equal

Step-by-step explanation:

Given first sample size n₁ = 677

First sample proportion

                             [tex]p^{-} _{1} = \frac{x_{1} }{n_{1} } = \frac{172}{677} = 0.254[/tex]

Given second sample size n₂ = 3377

second sample proportion

                             [tex]p^{-} _{2} = \frac{x_{2} }{n_{2} } = \frac{654}{3377} = 0.1936[/tex]

Null Hypothesis : H₀ :  p₁ = p₂.

Alternative Hypothesis : H₁ :  p₁ ≠ p₂.

      Test statistic

                [tex]Z = \frac{p_{1} ^{-}-p^{-} _{2} }{\sqrt{P Q(\frac{1}{n_{1} } +\frac{1}{n_{2} }) } }[/tex]

where

        [tex]P = \frac{n_{1} p_{1} + n_{2} p_{2} }{n_{1}+n_{2} } = \frac{677 X 0.254+3377 X 0.1936}{677+3377}[/tex]

       P =  0.2036

      Q = 1 - P = 1 - 0.2036 = 0.7964

         [tex]Z = \frac{0.254- 0.1936 }{\sqrt{0.2036 X 0.7964(\frac{1}{677 } +\frac{1}{3377 }) } }[/tex]

        Z =  3.775

Critical value ∝=0.05

Z- value = 1.96

The calculated  value Z = 3.775 > 1.96 at 0.05 level of significance

Null hypothesis is rejected

The Two Population proportion are not equal

Answer:

Yes, the sample has a bias

Step-by-step explanation:

Bias is the term used in statistics to describe a systematic distortion in the samples obtained for the parameter being estimated. It is evident by obtaining values higher or lower than that of the average population for the parameter being measured. As such the data is a misrepresentation of the population and cannot be trusted to give a good indices of things.

This sample has a bias because the concerned citizen opted to use a convenience sampling instead of using random sampling. In random sampling, every individual has an equal chance of being chosen which is unlike the convenience sampling when only a specific group of individuals can be chosen. In this case, the bias was introduced when the citizen went to stand outside the courthouse with his petition, the citizen should have taken samples across diverse geographical locations and professional institutions. The implication of this sampling is that a significant percentage of the population has been sidelined (considering they would not be in or around the courthouse) from the sampling and the sampling has been restricted to only those who have business around the courthouse. The result is that whatever samples he/she obtains will not be an accurate representation of the parameter being measure from the population.

As such, the sampling technique is biased

Answer:

a.) 8x + 6y

b.) 4x + 2y

Step-by-step explanation:

Simply add like terms together (x with x and y with y).

Answer:

9

Step-by-step explanation:

f(x) = (x + 1)^2

Let x=2

f(2) = (2 + 1)^2

     = 3^2

     = 9

Answer:

9x-11

Step-by-step explanation:

-5+2(x-3)+7x

Distribute

-5 +2x -6 +7x

-11 +9x

9x-11

Answer:

[tex]= 9x - 11 \\ [/tex]

Step-by-step explanation:

[tex] - 5 + 2(x - 3) + 7x \\ - 5 + 2x - 6 + 7x \\ - 5 - 6 + 2x + 7x \\ - 11 + 9x \\ = 9x - 11[/tex]

Answer:

US

World

Step-by-step explanation:

It depends on where you are. A "trapezium" outside the US is the same as a "trapezoid" in the US, and vice versa.

A trapezium (World; trapezoid in the US) is characterized by exactly one pair of parallel lines. One of the lines that are not parallel may be perpendicular to the parallel lines, but that will only be true for the specific case of a "right" trapezium.

__

A trapezium (US; trapezoid in the World) is characterized by no parallel lines. It may have one angle or opposite angles that are right angles (one or two sets of perpendicular lines), but neither diagonal may bisect the other.

In the US, "trapezium" is rarely used. The term "quadrilateral" is generally applied to a 4-sided figure with no sides parallel.

Answer:

[tex]71.35-2.093\frac{22.48}{\sqrt{20}}=60.83[/tex]    

[tex]71.35+2.093\frac{22.48}{\sqrt{20}}=81.87[/tex]    

Step-by-step explanation:

Information given

90 34 41 106 84 53 55 48 41 75 49 97 92 73 74 80 94 102 56 83

In order to calculate the mean and the sample deviation we can use the following formulas:  

[tex]\bar X= \sum_{i=1}^n \frac{x_i}{n}[/tex] (2)  

[tex]s=\sqrt{\frac{\sum_{i=1}^n (x_i-\bar X)}{n-1}}[/tex] (3)  

[tex]\bar X=71.35[/tex] represent the sample mean for the sample  

[tex]\mu[/tex] population mean (variable of interest)

s=22.48 represent the sample standard deviation

n=20 represent the sample size  

Confidence interval

The confidence interval for the mean is given by the following formula:

[tex]\bar X \pm t_{\alpha/2}\frac{s}{\sqrt{n}}[/tex]   (1)

The degrees of freedom are given by:

[tex]df=n-1=20-1=19[/tex]

Since the Confidence is 0.95 or 95%, the significance is [tex]\alpha=0.05[/tex] and [tex]\alpha/2 =0.025[/tex], and the critical value would be [tex]t_{\alpha/2}=2.093[/tex]

And replacing we got:

[tex]71.35-2.093\frac{22.48}{\sqrt{20}}=60.83[/tex]    

[tex]71.35+2.093\frac{22.48}{\sqrt{20}}=81.87[/tex]    

Answer:

Step-by-step explanation:

Hi,

the function is defined for all reals so the domain is [tex]]-\infty;+\infty[[/tex]

for x real

|x| >= 0

so f(x) >= 4

so the range is [tex][4;+\infty[[/tex]

do not hesitate if you need any further explanation

hope this helps

Answer:

Domain: (-∞,∞) Range: (4,∞)

Answer:

(a) The probability that at least one individual with a reservation cannot be accommodated on the trip is 0.4202.

(b) The expected number of available places when the limousine departs is 0.338.

Step-by-step explanation:

Let the random variable Y represent the number of passenger reserving the trip shows up.

The probability of the random variable Y is, p = 0.70.

The success in this case an be defined as the number of passengers who show up for the trip.

The random variable Y follows a Binomial distribution with probability of success as 0.70.

(a)

It is provided that n = 6 reservations are made.

Compute the probability that at least one individual with a reservation cannot be accommodated on the trip as follows:

P (At least one individual cannot be accommodated) = P (X = 5) + P (X = 6)

[tex]={6 \choose 5}\ (0.70)^{5}\ (1-0.70)^{6-5}+{6 \choose 6}\ (0.70)^{6}\ (1-0.70)^{6-6}\\\\=0.302526+0.117649\\\\=0.420175\\\\\approx 0.4202[/tex]

Thus, the probability that at least one individual with a reservation cannot be accommodated on the trip is 0.4202.

(b)

The formula to compute the expected value is:

[tex]E(Y) = \sum X\cdot P(X)[/tex]

[tex]P (X=0)={6 \choose 0}\ (0.70)^{0}\ (1-0.70)^{6-0}=0.000729\\\\P (X=1)={6 \choose 1}\ (0.70)^{1}\ (1-0.70)^{6-1}=0.010206\\\\P (X=2)={6 \choose 2}\ (0.70)^{2}\ (1-0.70)^{6-2}=0.059535\\\\P (X=3)={6 \choose 3}\ (0.70)^{3}\ (1-0.70)^{6-3}=0.18522\\\\P (X=4)={6 \choose 4}\ (0.70)^{4}\ (1-0.70)^{6-4}=0.324135[/tex]

Compute the expected number of available places when the limousine departs as follows:

[tex]E(Y) = \sum X\cdot P(X)[/tex]

         [tex]=(4\cdot 0.000729)+(3\cdot 0.010206)+(2\cdot 0.059535)+(1\cdot 0.18522)\\+(0\cdot 0.324135)\\\\=0.002916+0.030618+0.11907+0.18522+0\\\\=0.337824\\\\\approx 0.338[/tex]

Thus, the expected number of available places when the limousine departs is 0.338.

Answer:

[tex]y = -\frac{7x}{3} - 24[/tex]

Step-by-step explanation:

We can model this function using the equation of a line:

[tex]y = ax + b[/tex]

Where a is the slope of the line and b is the y-intercept.

To find the values of a and b, we can use the two points given:

(-9, -3):

[tex]-3 = a * (-9) + b[/tex]

[tex]-9a + b = -3[/tex]

(-12, 4):

[tex]4 = a * (-12) + b[/tex]

[tex]-12a + b = 4[/tex]

If we subtract the second equation from the first one, we have:

[tex]-12a + b - (-9a + b) = 4 - (-3)[/tex]

[tex]-12a + 9a = 4 + 3[/tex]

[tex]-3a = 7[/tex]

[tex]a = -7/3[/tex]

Then, finding the value of b, we have:

[tex]-12a + b = 4[/tex]

[tex]28 + b = 4[/tex]

[tex]b = -24[/tex]

So the equation is:

[tex]y = -\frac{7x}{3} - 24[/tex]

Answer:

The future value of the annuity due to the nearest cent is $2956.

Step-by-step explanation:

Consider the provided information:

It is provided that monthly payment is $175, interest is 7% and time is 11 years.

The formula for the future value of the annuity due is:

Now, substitute P = 175, r = 0.07 and t = 11 in above formula.

Hence, the future value of the annuity due to the nearest cent is $2956.

Step-by-step explanation:

Answer:

25/88

Step-by-step explanation:

25 red marbles, 27 blue marbles, and 36 yellow marbles. = 88 marbles

P(red) = number of red/total

          = 25/88

Answer:

Dear user,

Answer to your query is provided below

Probability of choosing a red marble is 0.28 or (25/88)

Step-by-step explanation:

Total number of marbles = 88

Number of red marbles = 25

Probability = 25/88

Answer:

(a) S = {GH, GT, BH, BT, RH and RT}

(b) The value of P (A) is 0.15.

(c) A and B mutually exclusive.

(d) A and C are not mutually exclusive.

Step-by-step explanation:

There are 10 cards in a special deck of cards: 4 are green (G), 3 are blue (B), and 3 are red (R).

Also when a card is picked, its color of it is recorded. An experiment consists of first picking a card and then tossing a coin.

(a)

The sample space is:

S = {GH, GT, BH, BT, RH and RT}

(b)

A = a blue card is picked first, followed by landing a head on the coin toss

Compute the probability of event A as follows:

[tex]P(A)=P(B)\times P(H)[/tex]

         [tex]=\frac{3}{10}\times\frac{1}{2}\\\\=\frac{3}{20}\\\\=0.15[/tex]

Thus, the value of P (A) is 0.15.

(c)

B = a red or green is picked, followed by landing a head on the coin toss.

The result of the coin toss is same for both events A and B.

So, consider the events,

A as a blue card is picked first

B as a red or green is picked

There is no intersection point for the two events.

Thus, events A and B mutually exclusive.

(d)

C = a red or blue is picked, followed by landing a head on the coin toss.

The result of the coin toss is same for both events A and C.

So, consider the events,

A as a blue card is picked first

C as a red or blue is picked

There is an intersection point for the two events.

Thus, events A and C are not mutually exclusive.

Part(a): The sample space can be written as shown below:

[tex]S=\{GH,GT,BH,BT,RH,RT\}[/tex]

Part(b): The required probability is [tex]P(A)=0.15[/tex]

Part(c): The events A and B are mutually exclusive because of [tex]P( A\ AND\ B ) = 0[/tex] are equal to zero.

Part(d): The events A and C are not mutually exclusive because [tex]P( A\ AND\ C ) = 0[/tex] are not equal to zero.

A sample space is a collection of a set of possible outcomes of a random experiment. The sample space is represented using the symbol, “S”.

Part(a):

A special deck contains ten cards with colors red, green, and blue when the card is picked its color gets recorded, and after that coin will get tossed.

Then the sample space can be written as shown below:

[tex]S=\{GH,GT,BH,BT,RH,RT\}[/tex]

Part(b):

If A is the event that a blue card is picked first followed by landing ahead on the coin toss then the outcome it contains is 3 blue cards and 1 head.

Therefore the [tex]P(A)[/tex] is calculated below:

[tex]P(A):P(B)\timesP(H)\\=\frac{3}{10}\times\frac{1}{2}\\ =0.15[/tex]

Part(c):

Mutually exclusive events contain a probability [tex]P( A\ AND\ B ) = 0[/tex] that means there is no common outcome between them.

Here, it can be noticed that events A and B cannot happen at the same time. That means, the researcher cannot pick the same cards together. Either it could be red or green.

Hence, events A and B are mutually exclusive because of [tex]P( A\ AND\ B ) = 0[/tex] are equal to zero.

Part(d):

Mutually exclusive events contain a probability [tex]P( A\ AND\ C ) = 0[/tex]  which means there is no common outcome between them.

Here, it can be noticed that events A and C can happen at the same time because event C can contain all outcomes of event A.

Hence, events A and C are not mutually exclusive because [tex]P( A\ AND\ C ) = 0[/tex] are not equal to zero.

Learn more about the topic samples space:

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The result will be the probability that 17 or fewer out of the 50 sampled students are bilingual.

To determine the probability that 17 or fewer out of 50 sampled students are bilingual, we can use the binomial probability formula. Let's calculate it step by step:

First, we need to determine the probability of an individual student being bilingual. We can do this by dividing the number of bilingual students by the total number of students:

P(bilingual) = 466 / 1320

Next, we'll use this probability to calculate the probability of having 17 or fewer bilingual students out of a sample of 50. We'll sum up the probabilities for having 0, 1, 2, ..., 17 bilingual students using the binomial probability formula:

P(X ≤ 17) = P(X = 0) + P(X = 1) + P(X = 2) + ... + P(X = 17)

Where:

P(X = k) = (nCk) * (P(bilingual))^k * (1 - P(bilingual))^(n - k)

n = Sample size = 50

k = Number of bilingual students (0, 1, 2, ..., 17)

Now, let's use a calculator to compute these probabilities. Assuming you have access to a scientific calculator, you can follow these steps:

Convert the probability of an individual being bilingual to decimal form: P(bilingual) = 466 / 1320 = 0.353

Calculate the cumulative probabilities for having 0 to 17 bilingual students:

P(X ≤ 17) = P(X = 0) + P(X = 1) + P(X = 2) + ... + P(X = 17)

Using the binomial probability formula, we'll substitute the values:

P(X ≤ 17) = (50C0) * (0.353)^0 * (1 - 0.353)^(50 - 0) + (50C1) * (0.353)^1 * (1 - 0.353)^(50 - 1) + ... + (50C17) * (0.353)^17 * (1 - 0.353)^(50 - 17)

Evaluate this expression using your calculator to get the final probability. Make sure to use the combination (nCr) function on your calculator to calculate the binomial coefficients.

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Using the central limit theorem, the probability that 17 or fewer of them are bilingual.

The following information is given in the question:

Population size N = 1320

Number of bilingual students = 466

Sample size n = 50

number of bilingual students in the sample = 17

Population proportion:

[tex]P =\frac{466}{1320}[/tex]

P =0.3530

Q= 1-3530

Q = 0.647

Sample proportion:

[tex]p = \frac{17}{50}[/tex]

p = 0.34

q = 1-0.34

q = 0.66

Since,

[tex]X \sim B(n, p)[/tex]

E(x) = np and var(x) = npq

Here, the sample size (50) is large and the probability p is small.

So we can use the central limit theorem, which says that for large n and small p :

[tex]X \sim (nP, nPQ)[/tex]

Where, P =0.3530

nP = 50 x 0.3530 = 17.65

and nPQ = 50x0.3530x0.647 = 11.41

Now, we want to calculate P(X≤17)

[tex]P(X\leq 17) = P(\frac{x-nP}{\sqrt{nPQ}}\leq \frac{17-17.65}{\sqrt{11.41}})[/tex]

[tex]P(X\leq 17) = P(z}\leq \frac{-0.65}{3.78}})[/tex]

[tex]P(X\leq 17) = P(z}\leq -0.172)[/tex]

[tex]P(X\leq 17) = P(z}\geq 0.172)[/tex]

[tex]P(X\leq 17) =1- P(z}\leq 0.172)[/tex]

[tex]P(X\leq 17) =1-0.56[/tex]

[tex]P(X\leq 17) =0.44[/tex]

Hence, the probability that 17 or fewer of the students are bilingual is 0.44.

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Answer:

P(33) = 0.0826

Step-by-step explanation:

The binomial distribution in this case has parameters n=55 and p=0.55.

The probability that k successes happen with these parameters can be calculated as:

[tex]P(x=k) = \dbinom{n}{k} p^{k}(1-p)^{n-k}\\\\\\P(x=k) = \dbinom{55}{k} 0.55^{k} 0.45^{55-k}\\\\\\[/tex]

We have to calculate the probability fo X=33 succesess.

This can be calculated using the formula above as:

[tex]P(x=33) = \dbinom{55}{33} p^{33}(1-p)^{22}\\\\\\P(x=33) =1300853625660220*0.0000000027*0.0000000235\\\\\\P(x=33) =0.0826\\\\\\[/tex]

Answer:

72√3

Step-by-step explanation:

30 60 90 triangles are what you start out with.

Step 1: 30-60-90

x = 12

WZ = 12√3

Step 2: Area formula

A = 1/2(12)(12√3)

*Since the 2 30-60-90 triangles are congruent, both segments of the base are 12

Plug it into the calc and you should get A = 72√3 as your final answer!