Suppose the number of business majors at liberal arts colleges are normally distributed and have a known population standard deviation of 21 students and an unknown population mean. A random sample of 35 liberal arts colleges is taken and gives a sample mean of 420 business majors. Find the margin of errorfor the confidence interval for the population mean with a 90% confidence level. Round the final answer to two decimal places.
z0.10z0.10 z0.05z0.05 z0.025 z 0.025 z0.01z0.01 z0.005 z 0.005 1.282 1.645 1.960 2.326 2.576
you may use a calculator or the common z values above. round the final answer to two decimal places. provide your answer below:

Looking at the graph, the best time to make a purchase is in month March 2013.

Exchange rate refers to the value ascribed to a particular currency in a foreign currency.

We have to find on which month the  American dollar was the strongest

Usually, currency exchange rates are not static but depend on many factors.

As such, it is always advisable to carry out trading activities when the exchange rate between currencies is favorable.

Looking at the graph, the best time to make a purchase is in March 2013.

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Answer:

[tex]\frac{3x^{2} }{10}[/tex]

Step-by-step explanation:

[tex]\frac{3x}{2}[/tex] x [tex]\frac{x}{5}[/tex] = [tex]\frac{3x^{2} }{10}[/tex]

So, the answer is  [tex]\frac{3x^{2} }{10}[/tex]

In hypothesis testing, converting a test statistic to a probability is called p-value. The p-value is the probability of obtaining a test statistic as extreme as the observed one or more extreme, assuming the null hypothesis is true.

If the p-value is less than the chosen level of significance, typically 0.05 or 0.01, the banker would reject the null hypothesis and conclude that there is evidence to support the alternative hypothesis, which is that the proportion of banking customers with a money market savings account has decreased. If the p-value is greater than the chosen level of significance, the banker would fail to reject the null hypothesis and conclude that there is not enough evidence to suggest that the proportion has decreased.

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So the order from left to right would be: Mode, Median, Mean.

In a positively skewed distribution, the mean is typically larger than the median, and the median is larger than the mode.

This can be illustrated in the following way:

Mean: The mean is affected by extreme values in the tail of the distribution, and will be pulled in the direction of the skew. Therefore, in a positively skewed distribution, the mean will be to the right of the median.

Median: The median is the value that separates the lower 50% of the data from the upper 50% of the data. In a positively skewed distribution, the tail of the distribution is on the right-hand side, which means that the median will be closer to the left-hand side than the mean.

Mode: The mode is the most frequent value in the distribution. In a positively skewed distribution, the mode will be the smallest value, located at the left-hand side of the distribution, while the mean and median will be to the right of it.

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The probability that the next car to drive by Pablo's house will be red or blue is 12 / 25.

For given data probabilities are,

color no. of cars probability

blue 70 0.28

green 30 0.12

red 50 0.2

white 80 0.32

yellow 20 0.08

total 250 1

Hence, the probability that the next car to drive by Pablo's house will be red or blue is,

= P(car drived will be red) + P(car drived will be blue)

= (50 / 250) + (70 / 250)

= 12/25

The probability is 12/25

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The given function is C(x) = 936 + 80x + 0.12x^2, where x represents the number of mountain bikes produced daily. The average cost function is also given by C(x).
To make the mountain bike as affordable as possible, the company should target a production level of 333.33 mountain bikes daily, where the average cost function is at its minimum. Rounded to 2 decimal places, the answer is

c = 333.33.

First, let's correct the given cost function: C(x) = 936x + 80x^2 + 0.12x^3. Now, we'll use the terms "function," "average," and "increases."

To find the average cost function, we need to divide the total cost function, C(x), by the number of mountain bikes produced daily, x. Let A(x) represent the average cost function:

A(x) = C(x) / x

Now, let's substitute C(x) into this equation:

A(x) = (936x + 80x^2 + 0.12x^3) / x

Simplify by canceling out an x term:

A(x) = 936 + 80x + 0.12x^2

To find the production level c where the average cost function decreases and then increases, we need to find the minimum point on the A(x) curve. To do this, we'll differentiate A(x) with respect to x to obtain the first derivative:

A'(x) = 80 + 0.24x

Now, set the first derivative equal to zero and solve for x:

80 + 0.24x = 0

0.24x = -80

x = c = -80 / 0.24

Round to 2 decimal places:

c ≈ 333.33

So, to make the mountain bike as affordable as possible, the company should target a production level of approximately 333.33 mountain bikes daily.

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We say that there are n-1 degrees of freedom in this case.

The number of values free to vary after certain restrictions have been placed on the data is the definition of degrees of freedom (df). Degrees of freedom are a key concept in inferential statistics and are often used in hypothesis testing and the calculation of confidence intervals. In essence, degrees of freedom represent the number of values in a data set that are free to vary after the mean has been calculated.

For example, if we have a sample of n observations and we know the mean of the sample, then we can calculate the sum of the n observations. However, we cannot set the value of the last observation, as it is determined by the values of the first n-1 observations and the mean. Therefore, we say that there are n-1 degrees of freedom in this case.

Degrees of freedom are also important in the calculation of standard errors, t-tests, and F-tests. In these cases, the degrees of freedom reflect the amount of information in the sample and are used to calculate the probability of observing a particular test statistic under the null hypothesis.

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Answer:

Step-by-step explanation:

First get y byitself to oneside

[tex]2x-y\leq 5[/tex]

Subtract -2x to bothside

[tex]-y\leq 5-2x[/tex]

Divide -1 to make y positive. Dividing or Multiplying changes direction.

[tex]y\geq 2x-5[/tex]

y >= any value above the positive of the line.

There are 64 boards in the stack.

To find the number of boards in the stack, we need to divide the total height of the stack by the thickness of each board.

Since each board is 3/8 of an inch thick, we can write:

Number of boards = Total height of stack ÷ Thickness of each board

Number of boards = 24 inches ÷ (3/8) inches

Number of boards = 24 inches × (8/3)

Number of boards = 64

Therefore, there are 64 boards in the stack.

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Answer:

woman,man,woman,man,woman,man,woman,man,woman,man,man,man,man

Step-by-step explanation:

too easy

Answer:

53.93 cm

Step-by-step explanation:

The given arc is 38.95 and the angle is 260 degrees.

A full angle would be 360 degrees, so we can use a ratio to find what the full circle would be:  

260/360 = 38.95/x

This equation is saying that 38.95 is equal to 260 degrees of the circle, while x is equal to 360 degrees.

Solving for x:

260x = 14022

x = 53.9306792

Round and it is:

53.93 cm

Answer: 10

Step-by-step explanation:

| –10 | = 10

Because that's the number of spaces it's from 0. :-)

The error between the exponential function e^x and its third degree Taylor polynomial P3(x) is given by e^x - P3(x).

Let's compute this error for various values of x:

For x = 0, we have e^0 - P3(0) = 1 - 1 = 0.

For x = 1, we have e^1 - P3(1) = e - (1 + 1 + 1/2 + 1/6) = e - 2.16667 ≈ -0.0803.

For x = -1, we have e^-1 - P3(-1) = 1/e - (1 - 1 + 1/2 - 1/6) = 0.581976 ≈ 0.582.

For x = 2, we have e^2 - P3(2) = e^2 - (1 + 2 + 4/2 + 8/6) = e^2 - 5.33333 ≈ 2.995.

For x = -2, we have e^-2 - P3(-2) = 1/e^2 - (1 - 2 + 4/2 - 8/6) = 0.133151 ≈ 0.133.

Overall, we can see that the error between the exponential function and its third degree Taylor polynomial decreases as x gets closer to 0. This is because the Taylor polynomial is centered at x = 0 and becomes a better approximation as x gets closer to the center. However, for larger values of x, the error can become quite significant.

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Answer:

290 degrees

Step-by-step explanation:

To find the length of the major arc subtracts 360-70.

You do this because angle LKM is a central angle, so the arc of LKM will be the same as the angle which is 70. If LKM was an inscribed angle the arc angles would be twice the degrees as the inscribed angle. And because arc LNM is a major arc and because a circle is 360 degrees all you have to do is subtract 70 from 360.

The image below shows an inscribed angle and a central angle.

Based on the definition of vertical angles, the value of x is calculated as: x = 16.

When two lines that are straight intersect each other at a point, they form two pairs of opposite angles which are referred to as vertical angles. These angles called vertical angles are congruent to each other.

We are given:

m∠A = (7x − 24)°

m∠B = (5x + 8)°

Given that angle A and angle B are vertical angles, therefore:

7x - 24 = 5x + 8

Combine like terms:

7x - 5x = 24 + 8

2x = 32

x = 16

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Approximately 187.97 Joules of energy is required to raise the temperature of 12.2 grams of gaseous nitrogen from 24.5 °C to 39.3 °C.

To calculate the energy required to raise the temperature of 12.2 grams of gaseous nitrogen from 24.5°C to 39.3°C, we need to use the following formula:

Q = m x c x ΔT

Where Q is the energy required (in joules), m is the mass of the substance (in grams), c is the specific heat capacity of the substance (in J/g°C), and ΔT is the change in temperature (in °C).

The specific heat capacity of nitrogen gas at constant pressure is approximately 1.04 J/g°C. Therefore, we can calculate the energy required as follows:

Q = 12.2 g x 1.04 J/g°C x (39.3°C - 24.5°C)
Q = 163.52 J

Therefore, it would require 163.52 joules of energy to raise the temperature of 12.2 grams of gaseous nitrogen from 24.5°C to 39.3°C.

To calculate the energy required to raise the temperature of 12.2 grams of gaseous nitrogen from 24.5 °C to 39.3 °C, you can use the formula:

q = mcΔT

where:
- q is the energy required (in Joules)
- m is the mass of the substance (in grams)
- c is the specific heat capacity of the substance (in J/g°C)
- ΔT is the change in temperature (in °C)

For gaseous nitrogen, the specific heat capacity (c) is approximately 1.04 J/g°C.

Now, let's calculate the energy required:

1. Calculate the mass (m): 12.2 grams
2. Calculate the change in temperature (ΔT): 39.3°C - 24.5°C = 14.8°C
3. Use the formula q = mcΔT:
  q = (12.2 g) * (1.04 J/g°C) * (14.8 °C)
  q ≈ 187.97 Joules

So, approximately 187.97 Joules of energy is required to raise the temperature of 12.2 grams of gaseous nitrogen from 24.5 °C to 39.3 °C.

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Using a t-distribution with 14 degrees of freedom (n-1) and a 98% confidence level (α = 0.02/2 = 0.01 for each tail), we have:

sample mean (x) = (2051+2061+2162+2167+2169+2171+2180+2183+2186+2195+2196+2198+2205+2210+2211)/15 = 2180.6

sample standard deviation (s) = 39

standard error of the mean (SEM) = s/√n = 39/√15 ≈ 10.077

t-score for a 98% confidence level and 14 degrees of freedom (from t-distribution table or calculator) = 2.977

Margin of error (ME) = t-score × SEM = 2.977 × 10.077 ≈ 30.05

Therefore, the 98% confidence interval for the mean hours worked per year in this state is:

(x- ME, x+ ME) = (2180.6 - 30.05, 2180.6 + 30.05) = (2150, 2211)

Rounding to the nearest integer and putting the limits in ascending order, we get:

(2150, 2211)

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A marginal distribution refers to the distribution of one variable in a dataset without taking into account the other variables. It is the probability distribution of a single random variable. On the other hand, a conditional distribution refers to the distribution of one variable in a dataset given that another variable has a specific value. It is the probability distribution of a random variable, given that another random variable has a specific value. Marginal distributions are often used to calculate overall probabilities, while conditional distributions are used to calculate probabilities under specific conditions. Marginal and conditional distributions are important concepts in statistics and are used to analyze data and make predictions. In general, marginal distributions are useful when considering the overall distribution of a dataset, while conditional distributions are useful when considering the distribution of a dataset under specific conditions or circumstances.
Hi! A "marginal distribution" is meant to describe the probability distribution of a single variable in a multivariate setting, without considering the relationships with other variables. To find the marginal distribution, you sum or integrate the joint distribution over all possible values of the other variables.

A "conditional distribution," on the other hand, is meant to describe the probability distribution of a variable given the values of one or more other variables. In this case, you focus on a specific subset of the data where the given condition(s) hold true, and then calculate the probability distribution for the variable of interest within that subset.

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The critical value for this problem would be 1.729, as this corresponds to a 5% error level and a two-tailed test.
To explain further, we can use hypothesis testing to determine whether the claim made by the local professor is supported by the sample data.

H0: The true mean salary for college graduates in the program is equal to or less than $53,500.

And our alternative hypothesis as:

Ha: The true mean salary for college graduates in the program is greater than $53,500.

We can then use the sample mean and standard deviation to calculate the test statistic:

t = (sample mean - hypothesized mean) / (standard deviation / sqrt(sample size))
t = (50994 - 53500) / (521 / sqrt(20))
t = -2.01

Using a t-distribution table with 19 degrees of freedom (sample size minus 1), and a significance level of 0.05 (corresponding to a 5% error), we can find the critical value for a two-tailed test:

t_critical = +/- 2.093

Since our calculated test statistic falls outside of the critical value range, we can reject the null hypothesis and conclude that there is evidence to suggest that the true mean salary for college graduates in the program is less than $53,500. Therefore, the rival university's faculty may have a valid point in disputing the local professor's claim.
To find the critical value for this problem, we will use a one-tailed t-test since we want to test if the actual value is less than $53,500.

Given:
- Sample size (n) = 20 graduates
- Significance level (α) = 5% or 0.05
- Degrees of freedom (df) = n - 1 = 20 - 1 = 19

Now, let's find the critical value (t) using the t-distribution table. For a one-tailed test at a 5% significance level and 19 degrees of freedom, the critical value is -1.729.

So, the critical value for this problem is -1.729.

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Other than translation, the other transformation used to create this frieze pattern is:

A 180-degree rotation is a transformation wherein an object or shape obtains a spin of half a full circle, indulging in the metamorphosis of facing the total opposite direction.

To demonstrate this more accurately, each point on the object must transition to a placement that is precisely polar to its primary site; centered by a fixed spot recognized as the axis of revolution.

A close examination of the pattern shows that it is not a reflection, hence making all the options of reflection unsuitable

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The zeros of the function h(x) = 6x² + x − 1 are x = 1/3 and x = -1/2.

Given the function in the question:

h(x) = 6x² + x − 1

To determine the zeros of the function, we need to solve for x when h(x) equals zero.

Plug in h(x) = 0

0 = 6x² + x − 1

6x² + x − 1 = 0

We can use the quadratic formula to solve for x:

x = [-b ± √(b² - 4ac)] / 2a

where a, b, and c are the coefficients of the quadratic equation.

In the function, a = 6, b = 1, and c = -1.

Plug these values into the above formula

x = [-1 ± √(1² - 4(6)(-1))] / 2(6)

x = [-1 ± √(1 + 24)] / 12

x = [-1 ± √(25)] / 12

x = [-1 ± 5] / 12

Hence, the zeros of the function are:

x = (-1 + 5) / 12 = 4/12 = 1/3

and

x = (-1 - 5) / 12 = -6/12 = -1/2

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Answer:

14/13

Step-by-step explanation:

40/3

The given expression, (sec A x sin C - tan A x tan C)/sin B, simplifies to (x/40) x AB, where AB is the length of the side opposite the right angle in triangle ABC.

Since triangle ABC is right-angled at B, we can use the following trigonometric ratios:

sin A = opposite/hypotenuse = AC/BC

cos A = adjacent/hypotenuse = AB/BC

tan A = opposite/adjacent = AC/AB

sin C = opposite/hypotenuse = AB/BC

cos C = adjacent/hypotenuse = AC/BC

tan C = opposite/adjacent = AB/AC

Using these ratios, we can simplify the given expression as follows:

(sec A x sin C - tan A x tan C)/sin B

= [(1/cos A) x sin C - tan A x tan C]/sin B (using sec A = 1/cos A)

= [(1/cos A) x (AB/BC) - (AC/AB) x (AB/AC)]/sin B (substituting sin C and tan C)

= [(AB/BCcos A) - (AC/BC)]/sin B (simplifying)

= [(AB/BC) - (ACcos A/BCcos A)]/sin B (getting a common denominator)

= [(AB - ACcos A)/BC]/sin B (simplifying)

= [(AB - ABsin A)/BC]/sin B (substituting)

Since triangle ABC is right-angled at B, we can use the following trigonometric ratios:

sin A = opposite/hypotenuse = AC/BC

cos A = adjacent/hypotenuse = AB/BC

tan A = opposite/adjacent = AC/AB

sin C = opposite/hypotenuse = AB/BC

cos C = adjacent/hypotenuse = AC/BC

tan C = opposite/adjacent = AB/AC

Using these ratios, we can simplify the given expression as follows:

(sec A x sin C - tan A x tan C)/sin B

= [(1/cos A) x sin C - tan A x tan C]/sin B (using sec A = 1/cos A)

= [(1/cos A) x (AB/BC) - (AC/AB) x (AB/AC)]/sin B (substituting sin C and tan C)

= [(AB/BCcos A) - (AC/BC)]/sin B (simplifying)

= [(AB/BC) - (ACcos A/BCcos A)]/sin B (getting a common denominator)

= [(AB - ACcos A)/BC]/sin B (simplifying)

= [(AB - ABsin A)/BC]/sin B (substituting sin A = AC/BC)

= [AB(1 - sin A)/BC]/sin B (factoring out AB)

= [(AB/BC) x (cos A/sin A)]/sin B (using sin A = opposite/hypotenuse and cos A = adjacent/hypotenuse)

= [cot A x (AB/BC)]/sin B (using cot A = cos A/sin A)

= (AB/BC) x (cos A/sin A) x (1/sin B) (multiplying fractions)

= (AB/BC) x (cos A/sin A) x csc B (using csc B = 1/sin B)

= (AB/BC) x cot A x csc B (using cot A = cos A/sin A)

= (BC/AB) x tan A x sin B (taking the reciprocal of both sides)

= (2BC/2AB) x (sin B/cos B) x (sin A/cos A) (multiplying and dividing by cos B and cos A)

= (BC/AB) x (2sin Bcos A)/(2sin A cos B) (simplifying)

= (BC/AB) x (sin (B + A)/sin (A + B)) (using sum and difference formulae)

= (BC/AB) x (sin C/sin 90) (since A + B + C = 90 degrees in a right-angled triangle)

= (BC/AB) x sin C

Substituting the given values, we get:

= [(2x + 20)/80] x AB

= (x/40) x AB

Therefore, the final answer is (x/40) x AB.

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There were 20 mens that classified as supertasters.

We will use the unitary method which is a method for solving a problem by the first value of a single unit and then finding the value by multiplying the single value.

we have been told that the number of women was 3.25 times the number of men. Therefore,

Number of women = 3.25 m

Since there are 65 women, the number of men will be:

3.25 m = 65

Men = 65/ 3.25

Men = 20

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Type I Error: Concluding that the percentage of adults with jobs is greater than 88% when it is actually equal to 88%, Type II Error: Concluding that the percentage of adults with jobs is equal to 88% when it is actually greater than 88%

In a hypothesis test, a Type I error occurs when we reject a true null hypothesis. In the case of the indicated claim, this would mean rejecting the hypothesis that the percentage of adults who have a job is not greater than 88%, when in fact it is true. This would be a serious mistake as we would be making a false claim.

On the other hand, a Type II error occurs when we fail to reject a false null hypothesis. In this case, it would mean failing to reject the hypothesis that the percentage of adults who have a job is not greater than 88%, when in fact it is false. This error would lead us to miss the true claim that the percentage of adults who have a job is greater than 88%, which could have important implications for policy and decision-making.

Therefore, in the hypothesis test of the indicated claim, the Type I error would be to falsely claim that the percentage of adults who have a job is greater than 88%, while the Type II error would be to miss the true claim that it is indeed greater than 88%.

First, let's set up our null hypothesis (H0) and alternative hypothesis (H1):
- Null hypothesis (H0): The percentage of adults who have a job is equal to 88% (P = 0.88)
- Alternative hypothesis (H1): The percentage of adults who have a job is greater than 88% (P > 0.88)

Now, let's identify the Type I and Type II errors for this hypothesis test:

1. Type I Error: This occurs when we reject the null hypothesis (H0) when it is actually true. In this context, a Type I error would be concluding that the percentage of adults who have a job is greater than 88% (P > 0.88) when, in reality, it is equal to 88% (P = 0.88).

2. Type II Error: This occurs when we fail to reject the null hypothesis (H0) when it is actually false. In this context, a Type II error would be concluding that the percentage of adults who have a job is equal to 88% (P = 0.88) when, in reality, it is greater than 88% (P > 0.88).

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Therefore, we would use a chi-squared distribution with 12 degrees of freedom to conduct the hypothesis test of the sample.

The degrees of freedom for a chi-squared test of independence with a contingency table with r rows and c columns can be calculated as (r-1)(c-1). In this case, we have a contingency table with 3 rows and 7 columns, so the degrees of freedom would be (3-1)(7-1) = 12. A chi-squared test of independence is a statistical test used to determine if there is a relationship between two categorical variables. It is commonly used to analyze contingency tables, which are tables that display the frequency distribution of two or more categorical variables.

The degrees of freedom (df) for a chi-squared test of independence with a contingency table are calculated using the formula (r-1)(c-1), where r is the number of rows in the table and c is the number of columns.

In this case, we have a contingency table with 3 rows and 7 columns. Therefore, r = 3 and c = 7.

Substituting these values into the formula, we get:

df = (r-1)(c-1)

= (3-1)(7-1)

= 2 x 6

= 12

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The answer is: one pair of opposite parallel sides, congruent diagonals, and congruent base angles.

An isosceles trapezoid has the following properties:

- One pair of opposite parallel sides

- Diagonals are congruent

- Congruent base angles

As a result, the right options are:

- One set of opposite parallel sides

- Congruent diagonals

- Congruent base angles

Hence, answer is: one pair of opposite parallel sides, congruent diagonals, and congruent base angles.

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Therefore, it is approximately 0.8911, or 89.11% (rounded to four decimal places), that a household watches television for between 4 and 12 hours per day.

z = (x - μ) / σ

For part (a), we want to find the probability that a household views television between 4 and 12 hours a day. We can translate this into finding the probability that a random variable X with mean μ = 8.35 and standard deviation σ = 2.5 falls between 4 and 12:

P(4 ≤ X ≤ 12)

To find this probability, we first standardize the values 4 and 12:

z1 = (4 - 8.35) / 2.5

= -1.74

z2 = (12 - 8.35) / 2.5 = 1.46

Now that we have the area under the curve between these two z-scores, we can use a normal distribution table or calculator to determine it:

P(-1.74 ≤ Z ≤ 1.46) ≈ 0.8911

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According to the information the volume of this figure would be 16cm³ and the surface area of this figure would be 24cm²

To calculate the surface area and volume of this figure we must perform the following procedure:

Volume:

Multiply height, width and length

2cm * 2cm *2cm = 16cm³

Surface area:

Multiply height by width and multiply the result by the number of faces the figure has.

2cm * 2cm = 4cm²

4cm² * 6 = 24cm²

According to the above, the volume of this figure is 16cm³ and the surface area is 24cm².

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