Quiz 11-1: Area of plane figures, sectors, and composite figures Unit 11 Volume and surface area

The null hypothesis and conclude that the average number of months looking for jobs after graduation is different for GMU and University of Alaska students with 95% confidence.

H0: The average number of months looking for jobs after graduation is the same for GMU and University of Alaska students. Ha: The average number of months looking for jobs after graduation is different for GMU and University of Alaska students.

alpha = 0.05

df = ngmu + nua - 2 = 198 (degrees of freedom)

t* = t(0.025, 198) = 1.972 (from t-distribution table)

SE = sqrt[(sgmu^2/ngmu) + (sua^2/nua)] = sqrt[(2.1^2/100) + (2.3^2/100)] = 0.324

tobt = (xgmu - xua) / SE = (3.6 - 2.7) / 0.324 = 2.77

Since tobt (2.77) > t* (1.972), we reject the null hypothesis and conclude that the average number of months looking for jobs after graduation is different for GMU and University of Alaska students with 95% confidence.

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The amount of paper used for the label on the can of tune is 12.57 in²

Here, the shape of the can of can is cylindrical.

The area of the cured surface of cylinder is given by formula,

A = 2πrh

where r is the radius of the cylinder

and h is the height of the cylinder

Here, r = 2 in and h = 1 in

so, the area of the lateral surface of cylinder would be,

A = 2 × π × r × h

A = 2 × π × 2 × 1

A = 4 × π

A = 12.57 sq. in.

Therefore, the required amount of paper = 12.57 in²

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Martina can run 4,920 more feet this year compared to last year.

Here, we have,

Martina can run 3 miles without stopping. Last year she could run 3,640 yards without stopping. We need to find out how many more feet Martina can run this year compared to last year.

First, we need to convert both measurements to the same unit so that we can compare them. We will convert both measurements to feet.

1 mile = 5,280 feet

1 yard = 3 feet

So, 3 miles = 3 x 5,280 feet = 15,840 feet

And, 3,640 yards = 3,640 x 3 feet = 10,920 feet

Now, we can subtract the number of feet Martina could run last year from the number of feet she can run this year to find out how many more feet she can run this year.

15,840 feet - 10,920 feet = 4,920 feet

Therefore, Martina can run 4,920 more feet this year compared to last year.

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complete question:

Martina can run 3 miles without stopping. Last year she could run 3,640 yards witho stopping. How many more feet can Martina

The Taylor series for f(x) centered at a = 5p is:

f(x) = f(a) + f'(a)(x-a) + f''(a)(x-a)^2/2! + f'''(a)(x-a)^3/3! + ...

To find the derivatives of f(x), we use the chain rule and the derivative of cos x:

f(x) = 4 cos x
f'(x) = -4 sin x
f''(x) = -4 cos x
f'''(x) = 4 sin x
f''''(x) = 4 cos x
...

Substituting a = 5p and evaluating the derivatives at a, we get:

f(5p) = 4 cos(5p) = 4
f'(5p) = -4 sin(5p) = 0
f''(5p) = -4 cos(5p) = -4
f'''(5p) = 4 sin(5p) = 0
f''''(5p) = 4 cos(5p) = 4
...

Therefore, the Taylor series for f(x) centered at a = 5p is:

f(x) = 4 - 4(x-5p)^2/2! + 4(x-5p)^4/4! - ...

Simplifying the series, we get:

f(x) = 4 - 2(x-5p)^2 + (x-5p)^4/3! - ...

Note that this is the Maclaurin series for cos x, with a = 0, multiplied by 4 and shifted to the right by 5p.

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After the battery is fully charged, Car B can go further than Car A.  Car B, as compared to Car A, had lower variability measurements. After the battery is completely charged, Car B can go further than Car A since Car A has a lower mean and median. Option D is Correct.

The median splits the data in half. A lower median indicates that Car A has less mileage than Car B.

Two measurements exist.

The measure of centre reveals how closely or widely the data are dispersed around the centre.

The measurements of centre are mean, median, and mode.

Car A travelled less since it had a lower mean and median.

We can find out how data changes with a single value using the measure of variability. The data is denser at the mean when the MAD is less. The MAD in Car B is lower. Data that is closer to the centre of the data set has a smaller IQR.

IQR is lower in Car B.

Consequently, automobile B travelled steadily since its IQR and MAD were lower. Option D is Correct.

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Correct Question:

Annabel is comparing the distances that two electric cars can travel after the battery is fully charged. Car A (miles) Car B (miles) Mean 145 200 Median 142 196 IQR 8 4 MAD 6 2 Part A Use the measures of center to make an inference about the data. Use the drop-down menus to complete your answer. Car A can travel further than Car B after the battery is fully charged. Part B Based on the data, which car performs most consistently? Explain. A. Car A because the measures of center are smaller for Car A than for Car B. B. Car B because the measures of center are smaller for Car B than for Car A. C. Car A because the measures of variability are smaller for Car A than for Car B. D. Car B because the measures of variability are smaller for Car B than for Car A.

The probability density function of Z is fZ(z) = (1/√(2π(4 + 2e^(-5)))) * e^(-z^2/(2(4 + 2e^(-5))))

Given that X(t) is a stationary Gaussian random process with mX(t) = 0 and RX(τ) = 2e^(-5|τ|).

We are interested in finding the probability density function (PDF) of Z = X(2) + X(3).

First, we need to find the mean and variance of Z:

E[Z] = E[X(2) + X(3)] = E[X(2)] + E[X(3)] = 0 + 0 = 0

Var(Z) = Var(X(2) + X(3)) = Var(X(2)) + Var(X(3)) + 2Cov(X(2), X(3))

Since X(t) is a stationary process, we have:

Var(X(2)) = Var(X(3)) = RX(0) = 2

Cov(X(2), X(3)) = RX(1) = 2e^(-5)

Therefore, Var(Z) = 2 + 2 + 2e^(-5) = 4 + 2e^(-5)

Now we can use the properties of Gaussian random variables to find the PDF of Z. Since Z is a linear combination of Gaussian random variables, it is also Gaussian with mean 0 and variance 4 + 2e^(-5).

Thus, fZ(z) = (1/√(2π(4 + 2e^(-5)))) * e^(-z^2/(2(4 + 2e^(-5)))).

Therefore, the probability density function of Z is fZ(z) = (1/√(2π(4 + 2e^(-5)))) * e^(-z^2/(2(4 + 2e^(-5))))

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The value of the variable is 3

Proportion can be defined as a method of comparing numbers in mathematics such that one is made equal to another.

Note that a fraction is described as the part of a whole

From the information given, we have that;

×:8 = 9:24​

To determine the fraction, we divide the numerator by the denominator, we have;

x/8= 9/24

Now, cross multiply the values

24(x) =9(8)

multiply the values, we have;

24x = 72

Now, make 'x' the subject

Divide both sides by the coefficient

x = 3

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To find the average number of bits required to encode this source using a Huffman code, we need to first construct the Huffman code for the given probabilities. The Huffman code assigns shorter codes to more probable values and longer codes to less probable values. We can start by listing the probabilities in descending order:

0.2, 0.15, 0.15, 0.15, 0.15, 0.1, 0.1

Next, we group the two least probable values and assign them a code of 0. We then repeat this process, grouping the next two least probable values and assigning them a code of 10. We continue until we have assigned codes to all values:

7: 0
1: 1000
2: 1001
3: 1010
4: 1011
5: 110
6: 111

We can see that the average number of bits required to encode this source using the Huffman code is:

(0.2 x 1) + (0.1 x 4) + (0.1 x 4) + (0.15 x 4) + (0.15 x 4) + (0.15 x 3) + (0.2 x 3) = 2.771 bits

Therefore, the correct answer is b) 2.771 bits.
To find the average number of bits required to encode this source using a Huffman code, follow these steps:

1. Arrange the probabilities in descending order: 0.2, 0.15, 0.15, 0.15, 0.15, 0.1, 0.1.

2. Build the Huffman tree:
- Combine the two smallest probabilities (0.1 and 0.1) into a single node with a probability of 0.2.
- Combine the next two smallest probabilities (0.15 and 0.15) into a single node with a probability of 0.3.
- Combine the next smallest probability (0.2) with the previously created 0.2 nodes to create a node with a probability of 0.4.
- Combine the remaining 0.3 and 0.4 nodes to create the root node with a probability of 0.7.

3. Assign binary codes to each value based on the Huffman tree:
- Value 1: 111
- Value 2: 110
- Value 3: 101
- Value 4: 100
- Value 5: 011
- Value 6: 010
- Value 7: 00

4. Calculate the average number of bits required to encode the source using the assigned binary codes and their probabilities:
- (3 * 0.1) + (3 * 0.1) + (3 * 0.15) + (3 * 0.15) + (3 * 0.15) + (3 * 0.15) + (2 * 0.2) = 0.9 + 0.9 + 1.35 + 1.35 + 0.4 = 2.771 bits

So, the average number of bits required to encode this source using a Huffman code is 2.771 bits, which corresponds to option (b).

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1.The first statement "Let S = {a, v, c, x, y}. Then {v, x} ∈ S." is false.
This is because {v, x} is a subset of S, not an element, so it should be {v, x} ⊆ S, not {v, x} ∈ S.

2. The statement "Let |B| = 6, then the number of all subsets of B is 36." is false.
This is because the number of subsets of a set with |B| elements is 2^|B|. So, in this case, there are 2^6 = 64 subsets, not 36.

3. If the set B = {1, 2, a, b, c}, then the cardinality |B| is :
|B| = 5
This is because the cardinality of a set is the number of elements in the set. B has 5 elements: {1, 2, a, b, c}.

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The volume of cone is 2 cubic units.

In this image, we have :

The cylinder has a volume of 18 cubic units and a height of 3.

The cone has a congruent base and the same height.

We have to find the volume of the cone.

We know that:

Volume of the cylinder is :

Volume of cylinder = [tex]\pi r^{2} h[/tex]__(A)

18 = [tex]\pi r^2(3)[/tex]

[tex]\pi r^2= 6[/tex]

Now, Volume of cone = [tex](1/3)\pi r^{2} h[/tex]___(B)

and, The cone has a congruent base and the same height.

substitute equation A in equation B

Volume of cone = (1/3)volume of cylinder

Volume of cone = (1/3) × 6

Volume of cone = 2 units.

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Answer:

54

Step-by-step explanation:

Multiply each number by 3

The probability of tossing 3 coins of uniform texture at the same time, and two of them happen to be heads up is [tex]\frac{3}{8}[/tex] or 0.375.

The probability of tossing 3 coins of uniform texture at the same time, and two of them happen to be heads up is as follows:

1. Each coin has 2 possible outcomes: heads (H) or tails (T).
2. Since there are 3 coins, there are [tex]2^3 = 8[/tex] total possible outcomes (HHH, HHT, HTH, THH, HTT, THT, TTH, TTT).
3. We're interested in the outcomes where 2 coins are heads up: HHT, HTH, THH.
4. There are 3 favorable outcomes out of 8 total outcomes.

So, the probability of tossing 3 coins of uniform texture at the same time, and two of them happen to be heads up is 3/8 or 0.375.

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When two fair dice are rolled,

(a) P(F) = 1/9

(b) P(F|E) = 1/5

a. To compute P(F), we need to find the probability that the total of two dice is five. There are four ways to obtain a total of five: (1,4), (2,3), (3,2), and (4,1). Since each die has six possible outcomes, there are 6x6=36 possible outcomes when two dice are rolled. Therefore, P(F) = 4/36 = 1/9.

b. To compute P(F|E), we need to find the probability that the total of two dice is five given that the total is odd. Since the sum of two odd numbers is always even, we know that if an odd total shows on the dice, then the sum must be either 3, 5, 7, 9, or 11. Out of these possibilities, only one yields a total of 5, which is (2,3). Therefore, P(F|E) = 1/5.

We would expect the probability of F to change when we condition on E because the occurrence of E affects the sample space. When we know that an odd total shows on the dice, we can eliminate some of the possible outcomes and reduce the sample space. This makes it more likely that the remaining outcomes will satisfy the condition for F, which increases the probability of F. Therefore, P(F|E) is greater than P(F) because E provides additional information that makes F more likely.

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31.25 g on the 5th day

no it will never by empty because even when it gets down to one singular piece of sugar you would technically just cut it in half, then that in half, yes it would get impossible, that's why you wouldn't actually do it, but if you typed it into a calculator it would just keep getting a smaller and smaller decimal.

In this case, since the curve is not a cylindrical helix, there is no well-defined axis.

A cylindrical helix is a curve in 3D space that follows the path of a cylinder as it is unwrapped along a line. The curve is parameterized by a vector function α(t) = (x(t), y(t), z(t)), where x(t) = r cos(t), y(t) = r sin(t), and z(t) = ht, with r and h being the radius and height of the cylinder, respectively.

In this case, the parameterization of the curve is given by α(t) = (at, bt^2, t^3). To determine if it is a cylindrical helix, we need to check if it follows the path of a cylinder as it is unwrapped along a line.

First, let's look at the z-coordinate, which corresponds to the height of the curve. We see that it is a cubic function of t, which means that the curve is not a horizontal line and it does not lie in a plane. This suggests that the curve may be a helix.

Next, let's look at the x and y-coordinates. The x-coordinate is a linear function of t, which means that it varies uniformly along the curve. The y-coordinate, on the other hand, is a quadratic function of t, which means that it changes faster than the x-coordinate.

This indicates that the curve may be a spiral, which is a type of helix that has an additional circular motion in the x-y plane as it moves along the z-axis. To confirm that the curve is a spiral, we need to check that the radius of the circle traced out by the curve in the x-y plane is constant.

To find the radius, we can take the derivative of the x and y-coordinates with respect to t:

dx/dt = a

dy/dt = 2bt

The radius of the circle is given by:

r = sqrt(x^2 + y^2) = sqrt(a^2 + 4b^2t^2)

We can take the derivative of r with respect to t to see if it is constant:

dr/dt = 4bt/sqrt(a^2 + 4b^2t^2)

We see that dr/dt is not constant, which means that the radius of the circle traced out by the curve is changing as it moves along the z-axis. Therefore, the curve is not a spiral.

In summary, the necessary and sufficient conditions for the curve to be a cylindrical helix are:

The z-coordinate of the curve is a linear function of t, i.e., z(t) = ht.

The radius of the circle traced out by the curve in the x-y plane is constant.

In this case, the curve does not satisfy condition 2, which means that it is not a cylindrical helix.

The axis of the curve is the line along which the cylinder is unwrapped. In this case, since the curve is not a cylindrical helix, there is no well-defined axis.

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The mean life of the 25 items will be less than 5.9 years (rounded to one decimal place) 8% of the time.

We'll use the concepts of normal distribution, mean, standard deviation, and the z-score.

Step 1: Calculate the standard error of the mean. Standard error = (Standard deviation) / sqrt(Number of items) Standard error = 1.6 / sqrt(25) = 1.6 / 5 = 0.32 years

Step 2: Find the z-score corresponding to the 8% probability. We look for the z-score in a standard normal distribution table, which tells us that 8% of the time (0.08 probability), the z-score is approximately -1.4.

Step 3: Use the z-score formula to find the mean life (x) that corresponds to this probability. Z = (x - Mean) / Standard error -1.4 = (x - 6.3) / 0.32

Step 4: Solve for x. x - 6.3 = -1.4 * 0.32 x = 6.3 - (1.4 * 0.32) x ≈ 5.852

The mean life of the 25 items will be less than 5.9 years (rounded to one decimal place) 8% of the time.

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The difference between the two possibilities is based on theory and mathematics. The experimental probability is based  on the results of several tests or experiments, but the theortical result is  calculated by comparing the positive results with all the results.

Theoretical probability of an event  occurring based on theory and reasoning. It is determined by dividing  number of favourable results by total  result. On the other hand, the experimental depend on the results of  various trials or tests.

The difference between theoretical probability and testing probability is that theory is based on knowledge and mathematics. Theoretical probability is what it should be. The test will appear as a result. For example, if I flip a coin, 50 times, the theoretical number of heads of the coin is 25. Coin flip probability = 0.5

Number of flips = 50

Theoretical number of heads = 0.5 × 50

= 25

If I actually flip a coin 50 times, 25 heads may or may not come up. If we have 21 heads, the test probability is 21 out of 50 heads, or 0.42. So the theoretical probability of getting heads in this example = 0.5

The experimental probability of landing heads = 0.42. Hence, both probabilities are not the same.

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So, there are 20 possible outfits.

An outfit like t-shirts is a group of garments that have been specifically chosen or created to be worn together. A firm, organisation, or group that collaborates closely is referred to as an outfit. It may be used as a verb to signify to supply with the right tools.

The term outfit can be used to refer to coordinated clothing, such as a shirt and trousers that you usually wear to job interviews. From out- + fit (v.), "act of fitting out (a ship, etc.) for an expedition," 1769. The broader sense of "articles and equipment required for an expedition" is documented in American English from 1787.

To calculate the number of outfits possible, we need to multiply the number of options for each item.

Number of options for jeans = 2 pairs = 2

Number of options for t-shirts = 5

Number of options for shoes = 2 pairs = 2

Therefore, the total number of possible outfits is:

2 x 5 x 2 = 20

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There are infinitely many even integers that are divisible by 5.

By considering how any even integer can be represented as 2m, where m is an integer, it becomes evident that if 2m happens to be divisible by 5, then m will also have this quality because 5, which is a prime number, cannot divide into 2.

As a result, all even integers that aredivisible by 5 can be expressed in the format of 10n, with any n being acceptable. Examples of such numbers include:

0 (from 10 x 0 = 0)

10 (from 10 x 1 = 10)

-10 (through 10 x -1 = -10)

20 (by evaluating 10 x 2 = 20)

And similarly when exploring negative values:  

-20 (since 10 x -2 = -20), and so on.

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The standard deviation of the random variable B(400, 0.9) is 6 (option E).

To determine the standard deviation of the random variable B(400, 0.9), we need to use the formula for the standard deviation of a binomial distribution:

Standard deviation (σ) = √(n * p * (1 - p))

Here, n is the number of trials (400) and p is the probability of success (0.9). Now, let's calculate the standard deviation step by step:

1. Calculate the probability of failure (1 - p): 1 - 0.9 = 0.1
2. Multiply n, p, and the probability of failure: 400 * 0.9 * 0.1 = 36
3. Calculate the square root of the result: √36 = 6

So, the standard deviation of the random variable B(400, 0.9) is 6 (option E).

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Answer:

2a - 1/a^2 +5

The first three terms of the sequence a_n = 2n-1/n²+5 are 1/6, 1/3, and 5/14.

In mathematics, a sequence is an enumerated collection of objects in which repetitions are allowed and order matters. Like a set, it contains members. The number of elements is called the length of the sequence.

A sequence is an ordered list of numbers. The three dots mean to continue forward in the pattern established. Each number in the sequence is called a term.

The first three terms of the sequence a_n = 2n-1/n²+5 are:

1. For n=1, a_1 = (2(1)-1)/(1²+5) = 1/6
2. For n=2, a_2 = (2(2)-1)/(2²+5) = 3/9 = 1/3
3. For n=3, a_3 = (2(3)-1)/(3²+5) = 5/14

So, the first three terms of the sequence are 1/6, 1/3, and 5/14.

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Answer:

The probability of selecting a pen from the first box is 3/4, and the probability of selecting a crayon from the second box is 5/10 or 1/2.

To find the probability of both events occurring together, we multiply the probabilities:

(3/4) × (1/2) = 3/8

Therefore, the probability of selecting a pen from the first box and a crayon from the second box is 3/8.

Step-by-step explanation:

Answer:

There are 4 items in the first box and 10 items in the second box, so there are 4 x 10 = 40 possible combinations of one item from each box.

The probability of selecting a pen from the first box is 3/4, since 3 of the 4 items in the first box are pens. The probability of selecting a crayon from the second box is 5/10 or 1/2, since there are 5 crayons in the second box out of 10 total items.

To find the probability of selecting a pen from the first box and a crayon from the second box, we need to multiply the probabilities of the two events:

P(pen from first box and crayon from second box) = P(pen from first box) * P(crayon from second box)

P(pen from first box and crayon from second box) = (3/4) * (1/2)

P(pen from first box and crayon from second box) = 3/8

Therefore, the probability that a pen from the first box and a crayon from the second box are selected is 3/8.

Answer:

Step-by-step explanation:

Let's start with the wording of the question. Since the sphere is tangential to the faces of the cube, if we draw our radius perpendicular (forming a right angle with the face), we can see it makes a direct connection to the cube face. This means that the diameter of the sphere is equal to the length of the cube.

Next, the question is asking for the volume outside the sphere and inside the cube. To find this, we need to take the volume of the sphere and subtract it from the volume of the cube.

The volume of a sphere is given as: 4/3*pi*(r)^3

The volume of a cube (or any rectangle) is given as: l*w*h

Now all that's left is to plug in the radius and sides of the cube (which we know is double the radius) and subtract.

(6)*(6)*(6)  -  4/3*pi*(3)^3

216 - 113.1 = 102.9

The question asks for standard units, but we aren't given any units so I'm a bit unclear about this. Either way, volumes are measured in cubics (m^3, ft^3, etc.) so it would be the unit of the radius cubed.

Hope I could help!

The volume contained outside the sphere and inside the cube is 216 - 36π cubic units, which is approximately 99.425 cubic units when rounded to three decimal places.

To find the volume contained outside the sphere and inside the cube, we need to calculate the volume of the cube and subtract the volume of the sphere.

The cube's side length is equal to twice the radius of the inscribed sphere. Therefore, the cube's side length is 2 * 3 = 6 units.

The volume of a cube is calculated by raising the side length to the power of 3. So, the volume of the cube is [tex]6^3 = 216[/tex] cubic units.

The volume of a sphere is given by the formula where r is the radius. Substituting the value, we have [tex](4/3) * π * 3^3 = (4/3) * π * 27[/tex]= 36π cubic units.

Now, to find the volume contained outside the sphere and inside the cube, we subtract the volume of the sphere from the  [tex](4/3) * π * r^3[/tex],volume of the cube: 216 - 36π.

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Is due to the fact that the standard error of the sample mean decreases with increasing sample size, leading to a more accurate estimation of the population mean.

To determine whether it is more likely to randomly select one woman with a height less than 64.4 inches or a sample of 21 women with a mean height less than 64.4 inches, we need to calculate the probability in each case.

Case 1: Randomly selecting 1 woman with height less than 64.4 inches

Since the height is normally distributed with a mean of 63.7 inches and a standard deviation of 2.5 inches, we can use the z-score formula to calculate the probability of selecting a woman with height less than 64.4 inches:

z = (64.4 - 63.7) / 2.5 = 0.28

From the standard normal distribution table, we can find that the probability of selecting a woman with a z-score of 0.28 or less is approximately 0.6103. Therefore, the probability of randomly selecting one woman with a height less than 64.4 inches is 0.6103.

Case 2: Selecting a sample of 21 women with mean height less than 64.4 inches

Since we are dealing with a sample mean, we need to use the central limit theorem, which tells us that the distribution of sample means will be approximately normal, with a mean of the population mean (63.7 inches) and a standard deviation of the population standard deviation divided by the square root of the sample size (2.5 / sqrt(21) = 0.545).

Using the same formula as before, we can calculate the z-score for a sample mean of less than 64.4 inches:

z = (64.4 - 63.7) / (2.5 / sqrt(21)) = 1.252

From the standard normal distribution table, we can find that the probability of selecting a sample mean with a z-score of 1.252 or less is approximately 0.8944. Therefore, the probability of selecting a sample of 21 women with mean height less than 64.4 inches is 0.8944.

Conclusion:

Based on the calculated probabilities, we can conclude that it is more likely to select a sample of 21 women with mean height less than 64.4 inches, as the probability of this event is higher than the probability of randomly selecting one woman with height less than 64.4 inches. This is due to the fact that the standard error of the sample mean decreases with increasing sample size, leading to a more accurate estimation of the population mean.

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According to the figure of a circle, x is equal to 17

The total arc length in a circle is equal to 360 degrees

hence arc QR + arc RS + arc QS = 360 degrees

Where

arc QR = 120

arc RS = 2 * 67 = 134

arc QS = 5x + 20

plugging in the values

120 + 134 + 5x + 21 = 360

5x = 360 - 120 - 134 - 21

5x = 85

x = 17

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(a) According to Chebyshev's theorem, at least 36% of the measurements lie between 122.7 mmHg and 145.5 mmHg. (b) According to Chebyshev's theorem, at least 56% measurements lie between 122.7 mmHg and 147.2. So, the correct option is 56%.

(a) Using Chebyshev's theorem to find how much data falls within a certain number of standard deviations from the mean.

Using k = 2,  to capture at least 75% of the data (which is 1 - 1/2^2 = 0.75).

Using k = 2, we can say that at least 75% of the data falls within the range of 134.1 - 2(5.7) = 122.7 mmHg and 134.1 + 2(5.7) = 145.5 mmHg.

The percentage of data that falls outside of this range is (1 - 0.75)/2 = 0.125, or 12.5%.

Therefore, at least 12.5% of the data falls in each, below 122.7 mmHg and above 145.5 mmHg. This means that at least 36% of the data falls within the range of 122.7 mmHg and 145.5 mmHg.

(b) We can use Chebyshev's theorem again, this time with k = 2.5, since we want to capture at least 56% of the data (which is 1 - 1/2.5^2 = 0.64).

Using the same calculations as in part (a), we find that at least 64% of the data falls within the range of 121.0 mmHg and 147.2 mmHg.

Therefore, we can say that at least 56% of the data falls within this range, since 56% is less than 64%.

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The measure of the missing angle which is named ∠PQR = 84°

The first step to solving the problem is to identify the nature of the triangle.

Note that the information states that:

Side PQ and QR are equal,
This means that it is an isosceles triangle because only isosceles triangles have two equal sides.

Another property of isosceles triangles that will help determine the m∠PQR is that the angles at the base of those equal sides are always equal.

Since that is true, then,

∠PQR = 180 - (QPR x 2 )

We know ∠QPR is 48°, so


∠PQR = 180 - (48x 2 )

∠PQR = 180 - 96

Thus,

∠PQR = 84°

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Full Question:

Although part of your question is missing, you might be referring to this full question:

See attached image.

The probability, provided that the windshield is a rectangle with the dimensions 28 inches by 54 inches and his line of site through the windshield is a rectangle with the dimensions 30 inches by 24 inches is 0.476

Continuous Probability is used for this information. Probability = Area of line of sight / total area of windshield

Probability = (30*24)/(28*54)

Probability = 0.476

The probability will be 0.476.

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