the figure below is a parallelogram, find n and m

n=?
m=?

The area of the figure is 23.5 in².

Given is shape we need to find the area of the same,

For finding the same,

We will find the area of the rt. triangle with height 9 in and base 7 in.

Then we will subtract the area of the rectangle with dimension 2 x 4.

So,

The required area = (1/2 x 9 x 7) - (2 x 4) = 23.5 in²

Hence, the area of the figure is 23.5 in².

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The given example of rings A = Q and B = Q(ζ) demonstrates that B is integral over A, but not finite over A, as required by the problem.

To give an example of rings A⊂B such that B is integral over A, but not finite over A, we can use the hint provided.

Consider the following rings:
- A = Q (the field of rational numbers)
- B = Q(ζ) (the field obtained by adding all roots of unity to Q)

B is integral over A because every element in B can be expressed as a root of a monic polynomial with coefficients in A. Specifically, any root of unity ζ^n, where n is a positive integer, is a root of the monic polynomial x^n - 1 with coefficients in Q.

However, B is not finite over A because there are infinitely many roots of unity. Each root of unity generates a different extension field, and the union of all these fields is B. If B were finite over A, it would mean that there exists a finite set of elements {b_1, b_2, ..., b_n} in B such that every element in B can be written as a linear combination of these elements with coefficients from A. But, since there are infinitely many roots of unity, we can always find a new root that cannot be expressed as a linear combination of the others, which contradicts the finiteness assumption.

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A) The length MN of the given wooden block is: 12

B) The total surface area in square inches of the wooden blocks to be painted is, 80400 in²

1) The formula for volume of a cuboid is:

Volume = Length * Width * Height

Thus: We get;

427 = (MN x 7 x 3) + (5 x 5 x 7)

427 = 21MN + 175

21MN = 252

MN = 252/21

MN = 12

2) Surface area of entire object is:

TSA = 2(12 x 3) + 2(12 x 7) - (5 x 7) + 2(7 x 3) + 3(5 x 7) + 2(5 x 5)

TSA = 402 in²

Hence, For 200 blocks:

TSA = 200 x 402

TSA = 80400 in²

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The circumference of the circle is 26.38 inches and the area of the circle is 55.39 square inches, both rounded to the nearest hundredth.

The diameter of a circle is the distance across the circle passing through its center. In this problem, the diameter of the circle is given as 8.4 inches. We can use the formula for the circumference and the area of a circle in terms of its diameter to find the solutions.

First, we can find the radius of the circle by dividing the diameter by 2. So, the radius is 8.4/2 = 4.2 inches.

To find the circumference of the circle, we can use the formula:

C = πd

where d is the diameter. Substituting the value of d = 8.4 inches and π = 3.14, we get:

C = 3.14 x 8.4 = 26.376

Therefore, the circumference of the circle is 26.38 inches (rounded to the nearest hundredth).

To find the area of the circle, we can use the formula:

A = πr²

where r is the radius. Substituting the value of r = 4.2 inches and π = 3.14, we get:

A = 3.14 x (4.2)² = 55.3896

Therefore, the area of the circle is 55.39 square inches (rounded to the nearest hundredth).

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The cost per widget based on the given data is decreasing by $0.616 for every one-unit increase in volume, and the predicted cost when volume is zero is $36.94.

To determine the cost per widget based on the given data, we need to find the slope of the regression line. The slope of the regression line represents the change in cost for a one-unit change in volume.

We can use the formula for the slope of the regression line:

slope = r(Sy/Sx)

where r is the correlation coefficient, Sy is the standard deviation of Y (cost), and Sx is the standard deviation of X (volume).

From the given data, we can calculate the following:

r = -0.75 (negative correlation between cost and volume)

Sy = 4.5 (standard deviation of cost)

Sx = 5.5 (standard deviation of volume)

Substituting these values into the formula for slope, we get:

slope = -0.75(4.5/5.5) = -0.616

Therefore, the cost per widget is decreasing by $0.616 for every one-unit increase in volume.

To find the actual cost per widget, we need to look at the intercept of the regression line. The intercept represents the predicted cost when volume is zero.

We can use the formula for the intercept of the regression line:

intercept = y - slope(x)

where y is the mean of Y (cost), slope is the slope of the regression line, and x is the mean of X (volume).

From the given data, we can calculate the following:

y = $10.50 (mean of cost)

x = 40 (mean of volume)

Substituting these values into the formula for intercept, we get:

intercept = 10.50 - (-0.616)(40) = $36.94

Therefore, the cost per widget is approximately $36.94 when volume is zero.

In summary, the cost per widget based on the given data is decreasing by $0.616 for every one-unit increase in volume, and the predicted cost when volume is zero is $36.94.

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Mr. Vellman has a test bank with 75 multiple-choice questions on Lesson 4.7, and the test bank comes with a random generator that will select and arrange questions to make different versions of a test.

If Mr. Vellman wants to create a 10-question multiple-choice test on this lesson, there are a few different ways to approach the problem. One method is to use the combination formula, which calculates the number of ways to choose a certain number of items from a larger set without regard to order. In this case, we want to know how many different combinations of 10 questions can be selected from a pool of 75 questions. The formula for this is: nCr = n! / r! (n - r)! where n is the total number of items, r is the number of items being selected, and ! denotes the factorial function (i.e., n! = n x (n-1) x (n-2) x ... x 1).

Using this formula, we can calculate the number of different versions of a 10-question test that Mr. Vellman could make from his test bank: 75C10 = 75! / (10! (75-10)!) = 75! / (10! 65!) = 75 x 74 x 73 x ... x 66 / 10 x 9 x 8 x ... x 2 x 1 This simplifies to: 75C10 = 6,424,369,000 Therefore, Mr. Vellman could create over 6 billion different versions of a 10-question multiple-choice test on Lesson 4.7 using his test bank.

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The correct number line that can be used to find the distance between the given points (4, -1) and (8, -1) is a number line going from negative 2 to positive 8 in increments of 1, with the points at 4 and 8.Option (A)

The reason for this is that the two points have the same y-coordinate, which means they lie on a horizontal line. To find the distance between them, we simply need to measure the difference between their x-coordinates, which is 8 - 4 = 4. On the given number line, the distance between points 4 and 8 is also 4 units, so we can directly read off the distance as 4 units.

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The percent of area under a normal curve between the mean and −1.18 standard deviations is 38.10% and between z=−1.6 and z = 0.7 is 70.32% and the​ z-score that best satisfies the condition is z=−0.4.

To find the percent of area under a normal curve between the mean and −1.18 standard deviations from the mean, we need to use a standard normal distribution table or calculator.

The area to the left of −1.18 standard deviations is 0.1190, and the area to the left of the mean is 0.5000. To find the area between them, we subtract the smaller area from the larger area:

0.5000 - 0.1190 = 0.3810

Therefore, the percent of area under a normal curve between the mean and −1.18 standard deviations is 38.10%.

To find the percent of the total area under the standard normal curve between z=−1.6 and z = 0.7, we again need to use a standard normal distribution table or calculator.

The area to the left of −1.6 is 0.0548, and the area to the left of 0.7 is 0.7580. To find the area between them, we subtract the smaller area from the larger area:

0.7580 - 0.0548 = 0.7032

Therefore, the percent of the total area between z=−1.6 and z = 0.7 is 70.32%.

To find the​ z-score that best satisfies the condition that 36% of the total area is to the left of z, we need to use a standard normal distribution table or calculator.

We look for the z-score that corresponds to a cumulative probability of 0.36. This is approximately −0.4, which means that 36% of the total area under the standard normal curve is to the left of z=−0.4. Therefore, the​ z-score that best satisfies the condition is z=−0.4.

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The equation of the plane tangent to the surfacer=3u2i+(5u−v2)j+3v2kr=3u2i+(5u−v2)j+3v2kat the point P that is P(12,9,3).z(x,y)=z(x,y)= 90x + 1296y + 810z = 14218.

To find the equation of the plane tangent to the surface at point P(12, 9, 3), we first need to find the partial derivatives of the surface with respect to u and v:

∂r/∂u = 6ui + 5j

∂r/∂v = -2vj + 6vk

Next, we can evaluate these partial derivatives at the point P(12, 9, 3) to get:

∂r/∂u = 6(12)i + 5j = 72i + 5j

∂r/∂v = -2(9)j + 6(3)k = -18j + 18k

Using these partial derivatives, we can find the normal vector to the tangent plane at point P by taking their cross product:

n = (∂r/∂u) x (∂r/∂v) = (72i + 5j) x (-18j + 18k)

= -90i - 1296j - 90k

Since the tangent plane passes through point P, its equation can be written in the form:

-90(x - 12) - 1296(y - 9) - 90(z - 3) = 0

Simplifying this equation gives:

-90x + 12960 - 1296y - 810z + 1458 = 0

or

90x + 1296y + 810z = 14218

Therefore, the equation of the plane tangent to the surface at point P is 90x + 1296y + 810z = 14218.

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40%

Step-by-step explanation:

For every one Polo shirt sold, the store sells approximately 0.93 Sunglasses. This value is a ratio, not the actual quantity of items sold.

The chart shows that the percentage of Polo Shirts sold is 20.6%, while the sunglasses sold are 19.2%. To determine the ratio of Polo shirts to Sunglasses sold, we divide the percentage of Sunglasses by the percentage of Polo shirts.

So, 19.2 divided by 20.6 equals approximately 0.93. This means for every one Polo shirt sold, approximately 0.93 Sunglasses are sold. It's important to note that this number is a ratio, not the actual number of items sold. It's also rounded to two decimal places as instructed.

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The larger can price is proportional to the price of

smaller can in relation to its volume.

A cylinder is a three-dimensional shape consisting of two parallel circular bases, joined by a curved surface.

The volume of a cylinder is expressed as;

V = πr²h

Volume of the small cylinder = πr²h

= 3.14 × 2² × 3

= 3.14 × 4 × 3

= 37.68 in²

The volume of big cylinder

= πR²h

= 3.14 × 6² × 9

= 3.14 × 36 × 9

= 1017.36 in³.

price of the big can = 2 × price of small

Therefore the volume of the big can is thrice the volume of the small cylinder and the price of the

big can is twice of the price of the small can.

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Yes because the digital scale only reports integers, making the measurement of weight a discrete variable.

However, the accuracy of the scale can also affect whether the weight measurement is truly discrete or has some degree of variability. If the scale has a high level of accuracy, the weight measurement may still be considered continuous even though it is reported in integers.

When using a digital scale that only reads in integers, your weight is considered a discrete variable, as it can only take on specific, separate values (whole numbers) rather than continuous values (including decimals). However, it's important to note that weight is inherently a continuous variable, but the limitations of the scale make it discrete in this specific scenario.

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Answer:

A legal question an interviewer may ask an application at a job interview is does the applicant has a criminal history.,

In the given triangle, the measure of side c is approximately 39 m

From the question, we are to calculate the measure of side c in the given triangle.

To determine the measure of side c, we will use SOH CAH TOA

sin (angle) = Opposite / Hypotenuse

cos (angle) = Adjacent / Hypotenuse

tan (angle) = Opposite / Adjacent

In the given diagram,

Angle = 29°

Opposite = 19 m

Hypotenuse = c

Thus

sin (29°) = 19 / c

0.4848 = 19 / c

c = 19 / 0.4848

c = 39.1914

c ≈ 39 m

Hence,

The measure of c is 39 m

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We used mathematical induction to prove that 5 divides n⁵ - n for any positive integer n. We proved it for k+1 by showing that (k+1)⁵ - (k+1) is divisible by 5 if k⁵ - k is divisible by 5. Therefore, the statement holds for all positive integers, n≥1.

We can prove this by induction.

Mathematical induction is a proof technique used to prove statements about all positive integers. The proof is divided into two steps: the base step and the inductive step.

Base Step: Prove the statement is true for the smallest integer n.

Inductive Step: Assume the statement is true for an arbitrary positive integer k, and use this assumption to prove the statement is true for the next integer k+1.

Here is the prove

Base case: For n=1, we have 1⁵ - 1 = 0 which is divisible by 5.

Inductive step: Assume that for some positive integer k≥1, 5 divides k⁵ - k. We want to show that 5 divides (k+1)⁵ - (k+1).

Expanding (k+1)⁵ - (k+1), we get

(k+1)₅ - (k+1) = k⁵ + 5k⁴ + 10k³ + 10k² + 5k + 1 - (k+1)

= k⁵ - k + 5k⁴ + 10k³ + 10k² + 5k

By the inductive hypothesis, k₅ - k is divisible by 5. Also, every other term in the expression is clearly divisible by 5. Therefore, (k+1)⁵ - (k+1) is divisible by 5 as well.

By mathematical induction, we have proved that 5 divides n⁵ - n for any positive integer n≥1.

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Given a significance level (alpha) of 0.05, we can conclude that the P-value of 0.097 is greater than the alpha. Therefore, we fail to reject the null hypothesis and conclude that zip code and diet are independent of one another.

Since the P-value (0.094) is greater than the significance level of 0.05, we fail to reject the null hypothesis that zip code and diet are independent of one another. Therefore, the conclusion is that Zip code and diet are independent of one another.
We need to first calculate the degrees of freedom for the chi-square test statistic. For a contingency table with R rows and C columns, the degrees of freedom (df) is calculated as follows:
The degree of freedom of the x statistic is calculated as (number of rows - 1) times (number of columns - 1), which in this case is (4-1) times (3-1) = 6.
df = (R - 1) * (C - 1)
In this case, the table has 4 rows (zip codes) and 3 columns (diets), so:
df = (4 - 1) * (3 - 1) = 3 * 2 = 6
The test statistic (x^2) is 10.78, and the degrees of freedom is 6. To find the P-value, we need to refer to a chi-square distribution table or use statistical software. For this example, we'll round the P-value to 3 decimals.
P-value ≈ 0.097
Therefore, we need to use a chi-square distribution table with 6 degrees of freedom. Looking up the value of 10.78 in the table, we find that the P-value is approximately 0.094.
Given a significance level (alpha) of 0.05, we can conclude that the P-value of 0.097 is greater than the alpha. Therefore, we fail to reject the null hypothesis and conclude that zip code and diet are independent of one another.

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Jorge's score on Exam 1 in his statistics class was at the 64th percentile, which means his score falls (c) between the median and the third quartile. This is because the median represents the 50th percentile and the third quartile represents the 75th percentile, and his score falls within that range.

Based on the information given, we know that Jorge's score is at the 64th percentile of all the scores. This means that 64% of the scores are below his score and 36% of the scores are above his score.

Option (c) between the median and the third quartile is the correct answer. The median represents the 50th percentile, and the third quartile represents the 75th percentile. Since Jorge's score is at the 64th percentile, it falls between these two values.

Options (a), (b), (d), and (e) can be eliminated because they do not fall within the range of the 64th percentile.

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The probability of randomly selecting a park that neither allows camping nor has a playground is 31/77.

We have,

We know that there are 59 parks that allow camping, 76 parks that have playgrounds, and a total of 154 parks.

Number of parks that allow camping only = 59 - 14 = 45

Number of parks that have playgrounds only = 76 - 14 = 62

Number of parks that have both camping and playgrounds = 14

The number of parks that neither allow camping nor have a playground.

= Total number of parks - (number of parks that allow camping only + number of parks that have playgrounds only - number of parks that have both camping and playgrounds)

= 154 - (45 + 62 - 14)

= 61

Now,

The probability of randomly selecting a park that neither allows camping nor has a playground.

= 61/154

= 31/77

Thus,

The probability of randomly selecting a park that neither allows camping nor has a playground is 31/77.

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The missing side is 37.8, option B is correct in the triangle.

In the given triangle we have to find the value of x

We know than tan function is a ratio of opposite side and adjacent side

tan 71 = x/13

2.90 = x/13

Multiply both sides by 13

13×2.9=x

37.8=x

Hence, the missing side is 37.8, option B is correct in the triangle.

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The standard deviation of the data set is approximately 11.1, rounded to one decimal place.

To calculate the standard deviation of a set of data, we need to follow a few steps. First, we need to find the mean (average) of the data set. Then, we need to subtract the mean from each data point and square the result. We add up all of the squared differences, divide by the number of data points minus one, and take the square root of the result.

So, for the data set 4, 25, 11, 26, 30:

- The mean is (4+25+11+26+30)/5 = 19.2

- The differences between each data point and the mean are:

   - 4-19.2 = -15.2

   - 25-19.2 = 5.8

   - 11-19.2 = -8.2

   - 26-19.2 = 6.8

   - 30-19.2 = 10.8

- Squaring these differences gives:

   - (-15.2)^2 = 231.04

   - 5.8^2 = 33.64

   - (-8.2)^2 = 67.24

   - 6.8^2 = 46.24

   - 10.8^2 = 116.64

- Adding up these squared differences gives 495.96

- Dividing by 4 (the number of data points minus one) gives 123.99

- Taking the square root of 123.99 gives approximately 11.1

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The angle formed by the radius of a circle and a tangent line to the circle is always equal to 90°

From the question, we have the following parameters that can be used in our computation:

The statement

In the statement, we have

As a general rule, the pojnt of intersection between the Radius of a circle and a Tangent line is right angles

This means that the angle is 90 degrees

Hence, the angle formed by the radius of a circle and a tangent line to the circle is always equal to 90°

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The trapezoid has only one line of reflectional symmetry.

When we divide the image, the mirror image of one side of the image to the other is known as reflectional symmetry. We can say that one half of the image is the reflection of the other half. Reflection symmetry is also known as mirror symmetry.

In an isosceles trapezoid, the length of the sides is the same which means that the left and the right sides are equal. But, the bases of an isosceles trapezoid are not the same. When a vertical line is drawn in the middle of the isosceles trapezoid, the left side of the image becomes the reflection of the right side. So there is only one line of reflection symmetry.

Therefore, there is only one line of reflectional symmetry in this figure of an isosceles trapezoid.

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The complete question is "The figure is an isosceles trapezoid. How many lines of reflectional symmetry does the trapezoid have? The image is given below"

Compared to small samples, large samples have less variability and thus will have a smaller error from the population parameters. Variability refers to the degree to which the data points in a sample differ from one another.

A small sample size may not accurately represent the population it was taken from, as it is subject to random variation. This random variation may lead to a large degree of variability in the sample, which in turn leads to a larger error from the population parameters.
On the other hand, large samples tend to have a more representative selection of individuals from the population. As a result, they tend to have less variability and a smaller error from the population parameters. This means that the estimates made from a large sample are likely to be more accurate than those made from a small sample. However, it is important to note that even with a large sample size, there may still be some degree of error due to other factors such as sampling bias or measurement error. Therefore, it is important to carefully consider the sample size and other factors when making statistical inferences about a population.
Compared to small samples, large samples have lower variability and thus will have a smaller error from the population parameters.

To explain further, a "sample" is a subset of a larger group, called the "population." When conducting research or analyzing data, researchers use samples to make inferences about the overall population. The characteristics of the population, such as the mean and standard deviation, are called "parameters."

When a sample is small, it is more susceptible to variability, which is the degree to which the data points in the sample differ from one another. High variability can lead to unreliable conclusions about the population parameters. A small sample may not be representative of the entire population, so the error, or difference between the sample estimate and the actual population parameter, can be larger.
On the other hand, large samples tend to have lower variability because they include more data points from the population, making them more representative of the overall group. This increased representation leads to a smaller error between the sample estimate and the actual population parameter.

In summary, using large samples is generally more advantageous because they provide lower variability and smaller errors, leading to more accurate estimates of population parameters.

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The returns when 30 tickets were sold would be $ 70 .

To calculate the total earnings from 30 sold tickets using the formula a ( n ) = 3 n - 20 , we must input n as 30 and assess the outcome .

Therefore, the returns raised when there were 30 tickets sold would be :
= 3 n - 20

= 3 ( 30 ) - 20

= 3 x 30 - 20

= 90 - 20

= 90 - 20

= $ 70

Therefore, with 30 tickets sold, the amount of money raised is $70.

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Question is:

How much was raised when 30 tickets were sold?

a)the probability that a single student randomly chosen from all those taking the test scores 558 or higher is approximately 0.4251.

b) the mean of the sampling distribution for x¯ is 552.9, and the standard deviation of the sampling distribution for x is approximately 4.507.

c)the probability that the mean score x¯ of these 35 students is 558 or higher is approximately 0.0943.

(a) Using the given mean and standard deviation, we can standardize the score of 558 as:

z = (558 - 552.9) / 26.7 = 0.1925

Using a standard normal table or calculator, we can find the probability of getting a z-score of 0.1925 or higher:

P(Z ≥ 0.1925) ≈ 0.4251

Therefore, the probability that a single student randomly chosen from all those taking the test scores 558 or higher is approximately 0.4251.

(b) The mean of the sample mean score x is the same as the population mean μ, which is 552.9. The standard deviation of the sample mean score x¯, also known as the standard error, is given by:

σ / sqrt(n) = 26.7 / sqrt(35) ≈ 4.507

Therefore, the mean of the sampling distribution for x¯ is 552.9, and the standard deviation of the sampling distribution for x is approximately 4.507.

(c) To find the z-score corresponding to the mean score x¯ of 558, we can standardize using the standard error:

z = (558 - 552.9) / (26.7 / sqrt(35)) ≈ 1.315

(d) Using the z-score of 1.315 and a standard normal table or calculator, we can find the probability of getting a sample mean score of 558 or higher:

P(Z ≥ 1.315) ≈ 0.0943

Therefore, the probability that the mean score x¯ of these 35 students is 558 or higher is approximately 0.0943.

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You need to assign a 3-digit identifier to each person to randomly select 900 students from a population of 5 million using a random number table.

To randomly select 900 students from a population of 5 million using a random number table, you need to assign a unique identifier to each person. This identifier should be a sequence of digits that allows you to distinguish between individuals and assign a random number to each.

To determine the number of digits required for this identifier, you can use the formula:

n = log10(N)

where N is the population size and n is the number of digits required. In this case:

N = 5,000,000

n = log10(5,000,000) = 6.7

This means that you need 7 digits to assign a unique identifier to each individual. However, since you are only selecting 900 students, you can truncate the identifier to 3 digits, which will still be sufficient to identify each individual in the sample. Therefore, you need to assign a 3-digit identifier to each person to randomly select 900 students from a population of 5 million using a random number table.

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Answer:

16/22, 24/33, and 40/55

or

72.7272...% = Percentage form

0.7272... = Decimal form

Hope this helps :)

Pls brainliest...

Answer: 70% decrease

Step-by-step explanation:

The total row and column provide the overall proportions of "Yes" and "No" responses in the survey, as well as the total number of responses.

We can make the two-way table with conditional relative frequencies based on the row totals by dividing each count in a row by the total number of responses in that row. Rounded to the nearest thousandth, the table looks like this:

Yes No Total

Students (n=54) 0.407 0.593 1.000

Teachers (n=23) 0.696 0.304 1.000

Total 0.481 0.519 1.000

In the first row, the conditional relative frequency for "Yes" is found by dividing the number of "Yes" responses among students (22) by the total number of student responses (54), which gives 22/54 ≈ 0.407. Similarly, the conditional relative frequency for "No" is found by dividing the number of "No" responses among students (32) by the total number of student responses, which gives 32/54 ≈ 0.593.

In the second row, the conditional relative frequency for "Yes" is found by dividing the number of "Yes" responses among teachers (16) by the total number of teacher responses (23), which gives 16/23 ≈ 0.696. Similarly, the conditional relative frequency for "No" is found by dividing the number of "No" responses among teachers (7) by the total number of teacher responses, which gives 7/23 ≈ 0.304.

The total row and column provide the overall proportions of "Yes" and "No" responses in the survey, as well as the total number of responses.

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