5. The surface area of a figure is 496 m². If the dimensions
are multiplied by 1/2, what will be
the surface area of the new figure?

A tape diagram can be used to represent Kennedy's purchases before tax.

Let's use a rectangle to represent the total cost before tax, and divide it into two parts: one for the popcorn and one for the juice bottles.

The cost of the popcorn is $3.30, so we can represent it with a segment of length 3.30 on the rectangle.

For the juice bottles, let's use a segment of length 5x to represent the total cost. If each bottle of juice costs x dollars, then the total cost of 5 bottles is 5x dollars.

The total cost before tax is $13.25, so we can represent it with a rectangle of length 13.25.

Putting it all together, the tape diagram would look like as shown in image.

This tape diagram represents the context if $x represents how much each bottle of juice costs.

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The answer to the fraction 6/7 - 4/5 is 2/35.

To subtract fractions with different denominators, we need to find a common denominator.

The common denominator for 7 and 5 is 35, hence:

6/7 - 4/5

= (6*5)/(7*5) - (4*7)/(5*7)

= 30/35 - 28/35

Now, we can subtract the numerators and keep the common denominator:

= (30 - 28)/35

= 2/35

Hence, the answer to 6/7 - 4/5 is 2/35.

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The warranty period should be 23 months (rounded down to the nearest whole number) to ensure that the manufacturer will not have more than 8% of the juicers returned.

To determine the warranty period, we need to find the time period that ensures that the manufacturer will not have more than 8% of the juicers returned. We can use the standard normal distribution to solve this problem.

First, we need to convert the mean and standard deviation to a standard normal distribution using the formula z = (x - mu) / sigma, where x is the warranty period, mu is the mean time before failure, sigma is the standard deviation, and z is the standard normal random variable.

Using this formula, we get z = (x - 30) / 4.

To find the warranty period that ensures that the manufacturer will not have more than 8% of the juicers returned, we need to find the z-score associated with the 8th percentile (since we want to find the value below which 8% of the juicers fail).

Using a standard normal table or a calculator, we find that the z-score associated with the 8th percentile is -1.41.

Substituting this value into the z formula, we get -1.41 = (x - 30) / 4. Solving for x, we get x = 23.16.

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Three standard deviations of the mean are set for the data which has t least 98. 77% of the data.

When dealing with normal distributions, the standard deviation serves as a valuable tool for measuring spread. The data is symmetrically distributed with no skew in the normal distributions. How spread out from the center of the distribution your data is on average is explained by the standard deviation.

According to statistical analysis, the empirical rule indicates that nearly all data collected from a normal distribution will fall within three standard deviations (represented by σ) of the mean or average (represented by µ). The empirical rule, or the 68-95-99.7 rule, tells you where your values lie:

Around 68% of scores are within 1 standard deviation of the mean,

Around 95% of scores are within 2 standard deviations of the mean,

Around 99.7% of scores are within 3 standard deviations of the mean.

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The mean and standard deviation obtained from simulations may differ from the true mean

standard deviation of a negative binomial distribution with parameters $r=0.6$ and $p=10$. However, with a large number of simulations, the mean and standard deviation from the simulations should approach the true mean and standard deviation of the distribution.

In general, the mean of a negative binomial distribution with parameters $r$ and $p$ is $r \cdot (1-p)/p$, and the standard deviation is $\sqrt{r \cdot (1-p)/p^2}$.

These formulas can be used to calculate the true mean and standard deviation of a $nb(0.6,\ 10)$ distribution.

Comparing the simulated mean and standard deviation to the true values can help assess the accuracy of the simulation results.

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The probability distribution for red ball is 1/16.

we have,

Red ball = 1

White ball= 3

Total ball = 4

Probability of getting a red ball both time

= 1/4 x 1/4

= 1/16

Thus, the required probability is 1/16.

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Answer:

27 cubic inches

Since each of the 6 faces of a cube have the same size, we know that each edge of the cube is √9 = 3 inches. Therefore the volume of the cube is 3 in x 3 in x 3 in = 27 cubic inches.on:

The drops per minute for the vancomycin infusion is 75 drops per minute (rounded to the nearest whole number).

To solve for drops per minute, we need to know the total volume of the infusion, the time it will take to infuse, and the drop factor of the tubing.

Total volume of infusion = 250 ml

Time to infuse = 2 hours = 120 minutes

Drip factor = 60 gtt/ml

To calculate the drops per minute, we can use the formula:

(drops/min) = (total volume in ml ÷ time in minutes) x drip factor

Substituting the values we have:

(drops/min) = (250 ÷ 120) x 60

(drops/min) = 1.25 x 60

(drops/min) = 75

This is the rate at which the infusion should be administered using the selected tubing to deliver 1 g of vancomycin over 2 hours every 12 hours. It is important to ensure that the drops per minute are monitored throughout the infusion to ensure that the rate is appropriate and to avoid potential complications.

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The coordinates of triangle A'B'C' are A(-14, -14), B(-14, -6), C(-4, -6)

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

The A'B'C' with vertices at is calculated as

A'B'C' = ABC * the scale factor

Substitute the known values in the above equation, so, we have the following representation

A'B'C = A(-7, -7), B(-7, -3), C(-2, -3) * 2

Evaluate

A(-14, -14), B(-14, -6), C(-4, -6)

Hence, the coordinates are A(-14, -14), B(-14, -6), C(-4, -6)

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It is FALSE that net pay minus deductions equal gross pay.

Net pay is the difference between gross pay and tax-allowed deductions.

The net pay is computed after deducting all deductibles from the gross pay.

The net pay of an individual represents the amount of the take-home pay.

Some of the deductions made from the gross pay before arriving at the net pay include withholding taxes, insurance premiums, social security, and Medicare.

Thus, we cannot agree that Net pay minus deductions equals gross pay.

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The conclusion of the Mean Value Theorem is satisfied for two values of c: [tex]c = \sqrt{(5/6)}[/tex] and [tex]c = -\sqrt{(5/6)}[/tex]. The limit of the given expression as x approaches infinity is 0.

1. To verify that the function [tex]g(x) = x^3 + x - 1[/tex] satisfies the hypotheses of the Mean Value Theorem on the interval [0, 2], we need to check two conditions: continuity and differentiability.

Firstly, g(x) is continuous on [0, 2] since it is a polynomial function. Secondly, g(x) is differentiable on (0, 2) since its derivative[tex]g'(x) = 3x^{2} + 1[/tex]is also a polynomial function and is defined for all x in the interval (0, 2).

Now, by the Mean Value Theorem, there exists a number c in (0, 2) such that [tex]g'(c) = [g(2) - g(0)]/(2 - 0)[/tex]. Therefore, we can find the value of c by solving the equation:

[tex]g'(c) = [g(2) - g(0)]/(2 - 0)[/tex]

3c² + 1 = (8 - 1)/(2)

3c² + 1 = 7/2

3c² = 5/2

c² = 5/6

[tex]c = \pm \sqrt{(5/6)}[/tex]

Hence, the conclusion of the Mean Value Theorem is satisfied for two values of c: [tex]c = \sqrt{(5/6)}[/tex] and [tex]c = -\sqrt{(5/6)}[/tex].

2. To evaluate [tex]\lim_{x \to \infty} (ln x)^3/x^2[/tex], we can use L'Hopital's Rule. Applying the rule once, we get:

[tex]\lim_{x \to \infty} (ln x)^3/x^2 = \lim_{x \to \infty} 3(ln x)^2/x[/tex]

[tex]= \lim_{x \to \infty} 6ln \;x/x[/tex]

[tex]= \lim_{x \to \infty} 6/x = 0[/tex]

Therefore, the limit of the given expression as x approaches infinity is 0.

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Before coming to a stop, the pendulum swings 192 feet in total.

The lengths of the arcs form a geometric sequence. Let's call the length of the first arc "a" and the common ratio "r". Then, we have:

First arc: a = 48

Third arc: ar² = 27

We can use the ratio of the third and first arcs to solve for the common ratio "r":

(ar²)/a = 27/48

r² = (27/48)

Now we can use the formula for the sum of an infinite geometric series to find the total distance traveled by the pendulum. The formula is:

S = a / (1 - r)

where S is the sum of the series, a is the first term, and r is the common ratio.

Substituting the values we have:

S = 48 / (1 - √(27/48))

Simplifying:

S = 48 / (1 - (3/4))

S = 48 / (1/4)

S = 192

Therefore, the pendulum travels a total distance of 192 feet before coming to a rest.

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To answer these questions, we can use the Empirical Rule, also known as the 68-95-99.7 rule, which applies to normally distributed data.

According to the Empirical Rule:

1. Approximately 68% of the data falls within one standard deviation of the mean.

2. Approximately 95% of the data falls within two standard deviations of the mean.

3. Approximately 99.7% of the data falls within three standard deviations of the mean.

Given that the average speed is 48 mph and the standard deviation is 12 mph, we can use this information to estimate the percentage of vehicle speeds within certain ranges.

1. The range between 36 and 60 mph corresponds to one standard deviation below the mean (36 mph) to one standard deviation above the mean (60 mph). Since one standard deviation covers approximately 68% of the data, we can estimate that approximately 68% of the vehicle speeds were between 36 and 60 mph.

2. To estimate the percentage of vehicle speeds that exceeded 60 mph, we can consider

the range beyond one standard deviation above the mean (60 mph). Since the Empirical Rule states that approximately 68% of the data falls within one standard deviation of the mean, this means that approximately (100% - 68%) = 32% of the data lies beyond one standard deviation above the mean.

However, to calculate the percentage exceeding 60 mph, we need to consider speeds above two standard deviations from the mean since the range of interest is above 60 mph. Therefore, we estimate that approximately (32% / 2) = 16% of the vehicle speeds exceeded 60 mph.

So, the answers are:

1. Approximately 68% of the vehicle speeds were between 36 and 60 mph.

2. Approximately 16% of the vehicle speeds exceeded 60 mph.

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a. The probability if individual bottle contains less than 2.03 liters is 0.2119.

b. If a sample of 4 bottles is selected,  the probability that the sample mean amount contained is less than 2.03 liters is 0.0548.

c. The probability that the sample mean amount contained is less than 2.03 liters if a sample of 25 bottles is selected, t is  0

d. The difference in the results in (a) and (c) is due to the sample size.

e. The difference in the results in (b) and (c) is also due to the sample size.

a. To determine the probability that a single bottle contains less than 2.03 liters, we must normalize the number using the z-score formula: z = (x - mu) / sigma, where x is the desired value, mu is the mean, and sigma is the standard deviation. Thus:

z = (2.03 - 2.05) / 0.025 = -0.8

We calculate the probability of a z-score less than -0.8 using a standard normal distribution table or calculator. As a result, the probability that a single bottle contains less than 2.03 liters is 0.2119.

b. To calculate the probability that the sample mean amount contained is less than 2.03 liters, use the standard error of the mean formula: SE = sigma / sqrt(n), where n is the sample size. Thus:

SE = 0.025 / sqrt(4) = 0.0125

The sample mean must then be standardized using the z-score formula:

z = (xbar - mu) / SE = (2.03 - 2.05) / 0.0125 = -1.6

We calculate the probability of a z-score less than -1.6 using a conventional normal distribution table or calculator. As a result, the chance that the sample mean quantity contains less than 2.03 liters is 0.0548.

c. Using the same formula for the standard error of the mean, but with a sample size of 25:

SE = 0.025 / sqrt(25) = 0.005

Standardizing the sample mean:

z = (2.03 - 2.05) / 0.005 = -4

Using a standard normal distribution table or calculator, we find that the probability of a z-score less than -4 is very close to 0. As a result, the likelihood that the sample mean amount contained is less than 2.03 liters is essentially zero.

d. The difference in the results in (a) and (c) is due to the sample size. When we're looking at an individual bottle, the distribution is normal with mean 2.05 and standard deviation 0.025.

However, when we take a sample of 25 bottles, the sample mean is much more tightly distributed around the true mean of 2.05, with standard error of the mean 0.005. This means that it's very unlikely to get a sample mean less than 2.03 liters, because the sample mean is very close to the true mean.

e. The difference in the results in (b) and (c) is also due to the sample size. As the sample size increases, the standard error of the mean decreases, which means that the sample mean is more tightly distributed around the true mean.

This makes it less likely to get a sample mean that is far from the true mean, and thus the probability of getting a sample mean less than 2.03 liters decreases as the sample size increases.

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The unknown angles of the cyclic quadrilateral is as follows:

m∠C = 88 degrees

A cyclic quadrilateral is a quadrilateral which has all its four vertices lying on a circle.

The sum of angles in a cyclic quadrilateral is 360 degrees.

The opposite angles of a cyclic quadrilateral are supplementary which means that the sum of either pair of opposite angles is equal to 180 degrees.

Therefore, let's find m∠C as follows:

m∠C = 180 - 92

m∠C = 88 degrees

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In the situation, if you took another sample of 157 students and asked them for measurements of thumb and height, it is unlikely that you would get the exact same F ratio.

The F ratio is a statistical value that compares the variance between groups to the variance within groups. Here's why it might be different:

1. Sampling variability: Since you are taking another sample of 157 students, there is a chance that the measurements will be slightly different from the original sample. The new sample might have students with different thumb lengths and heights, which could lead to different variances and thus a different F ratio.

2. Measurement errors: Even if the actual relationship between thumb length and height remains constant, the process of measuring these variables can introduce errors. Errors in measurement can cause discrepancies in the data, leading to a different F ratio.

3. Population diversity: If the new sample is drawn from a different population, there could be differences in the relationship between thumb length and height in that population. This would also result in a different F ratio.

To summarize, while it is possible to get a similar F ratio in a new sample, it is unlikely that the F ratio would be exactly the same due to sampling variability, measurement errors, and potential population differences.

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The Nyquist-Shannon sampling theorem, also known as the sampling theorem, states that if the sampling rate is greater than or equal to twice the maximum frequency of the signal being sampled, then the original signal can be perfectly reconstructed from its samples.

The maximum frequency of the signal is also referred to as the Nyquist frequency, which is half of the sampling rate. The theorem is often used in digital signal processing, data compression, and other applications where analog signals are converted into digital signals.

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The kilometers the bus travels between these two stops is 5.8 km

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

Speed = 23 km/h

Time = 13 : 40 - 13 : 25 = 15 minutes = 1/4 hr

The kilometers the bus travels between these two stops is calculated as

Distance = Speed * Time

Substitute the known values in the above equation, so, we have the following representation

Distance = 23 * 1/4

Evaluate

Distance = 5.8 km

Hence, the distance is 5.8 km

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a) The probability function of Y1 + Y2 is a Poisson distribution with mean λ1 + λ2.

b) The conditional probability function of Y1, given that Y1 + Y2 = m, is a binomial distribution with parameters m and

p = λ1 / (λ1 + λ2).

a. To find the probability function of Y1 + Y2, we can use the fact that the sum of independent Poisson random variables follows a Poisson distribution with the mean equal to the sum of their individual means. Therefore, Y1 + Y2 follows a Poisson distribution with mean λ1 + λ2.

b. To find the conditional probability function of Y1 given that Y1 + Y2 = m, we use the fact that the conditional distribution of a Poisson random variable, given the sum of two independent Poisson random variables, is a binomial distribution.

The parameters of this binomial distribution are m (the total number of events) and p (the probability of an event occurring in Y1), where p = λ1 / (λ1 + λ2).

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The volume of a square pyramid is given by the formula: V = (1/3) * b^2 * h

where b is the base length and h is the height.

In this case, the base is a square with sides of length 2.75 inches, so the base area is:

b^2 = 2.75^2 = 7.5625 square inches

The height of the pyramid is also 2.75 inches.

Therefore, the volume of the ornament is:

V = (1/3) * 7.5625 * 2.75 = 6.5391 cubic inches

Rounding to the nearest hundredth, the approximate volume of the ornament is:

V ≈ 6.54 cubic inches

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The value of Area of triangle is,

A = 38 units²

Given that;

Coordinates of STU are,

S = (2, 6)

T = (5, 2)

U = (- 7, - 7)

Hence, Midpoint of S and T is, X

X = (2 + 5) /2 , (6 + 2)/2

X = (3.5, 4)

We know that;

The distance between two points (x₁ , y₁) and (x₂, y₂) is,

⇒ d = √ (x₂ - x₁)² + (y₂ - y₁)²

Hence, Distance between S and T is,

d = √(5 - 2)² + (2 - 6)²

d = √9 + 16

d = √25

d = 5

And, Distance between U and X is,

d = √(3.5 - (-7))² + (4 - (-7))²

d = √110.25 + 121

d = √231.25

d = 15.2

Thus, Area of triangle is,

A = 1/2 × ST × UX

A = 1/2 × 5 × 15.2

A = 38 units²

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The last two digits of x must be either 34, 54, 64, 84, or 94.

To determine the last two digits of x, we need to analyze the last two digits of 63x.
Firstly, we can break down 63x into (60x + 3x).
We know that the last two digits of 60x will always be 0, as any multiple of 60 has a 0 in the tens place.
Therefore, we only need to focus on the last two digits of 3x.
We also know that the last two digits of 3x must be even, as the last digit of 63x is 6 (an even number) and the second to last digit is 0 (an even number).

Thus, the last digit of 3x must be even, which means that x must end in either 4, 6, or 8.
Additionally, the second to last digit of 3x must be 1 or 5, so that when we multiply it by 3, it will add either 3 or 5 to the last digit (which is even).
Therefore, the possible values for x are 34, 54, 64, 84, 94, and so on.

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The correct answer to your question is simple random sampling. This type of sampling involves randomly selecting items from a population, where each item has an equal chance of being selected.

This process helps ensure that the sample is representative of the population, as each item in the population has an equal chance of being included in the sample. Simple random sampling is often used in research studies, where a subset of the population is selected for study. By using simple random sampling, researchers can minimize bias and ensure that the results of their study are applicable to the larger population. It is important to note that simple random sampling is not the only type of sampling method available, and researchers must carefully consider which method is most appropriate for their research question and population of interest.

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Answer:

If 5 + 6i is a root of the polynomial function f(x), then its complex conjugate 5 - 6i must also be a root of f(x). This is because complex roots of polynomial functions always come in conjugate pairs.

To see why this is true, consider a polynomial function with real coefficients. If a complex number z = a + bi is a root of the polynomial, then we have:

f(z) = 0

Substituting z = a + bi into the polynomial function, we get:

f(a + bi) = 0

Now we can take the complex conjugate of both sides:

f(a - bi) = (f(a + bi))^*

Since the coefficients of the polynomial are real, we have:

(f(a + bi))^* = f(a - bi)

Therefore, if a + bi is a root of the polynomial, then so is its conjugate a - bi.

In this case, since 5 + 6i is a root of f(x), we know that 5 - 6i must also be a root of f(x). Therefore, the answer is the complex number 5 - 6i.

Based on the given information, the researcher conducted a one-sample t-test to determine whether training supervisors on giving appropriate feedback will reduce the number of negative statements they make to their employees.

The null hypothesis (H0) is that there is no significant difference in the number of negative statements made by supervisors before and after training, while the alternative hypothesis (Ha) is that there is a significant reduction in the number of negative statements made after training.

The results of the one-sample t-test showed that the mean number of negative statements made by supervisors after training was 8.6667, with a standard deviation of 2.16025 and a standard error of 0.88192. The test value was calculated to be -1.917, with a p-value of 0.109.

Since the p-value (0.109) is greater than the alpha level of 0.05, we fail to reject the null hypothesis. Therefore, we cannot conclude that there is a significant reduction in the number of negative statements made by supervisors after training. However, it is important to note that the sample size (n=6) is small, and further research with a larger sample size may be needed to draw more definitive conclusions.
Hi! Based on the provided data, the researcher conducted a one-sample t-test to determine if the training on giving appropriate feedback significantly reduced the number of negative statements made by supervisors. With an alpha level of .05, we compare the obtained t-value to the critical t-value to draw a conclusion.

The data shows:
- Sample size (n) = 6
- Mean number of negative statements = 8.6667
- Standard deviation (std. deviation) = 2.16025
- Standard error of the mean (std. error mean) = .88192

However, the t-value and degrees of freedom are not provided. To conclude the study, we would need to compute the t-value and compare it with the critical t-value (obtained from a t-distribution table using the alpha level and degrees of freedom). If the computed t-value is greater than the critical t-value, we would reject the null hypothesis and conclude that the training significantly reduced the number of negative statements made by supervisors. If not, we would fail to reject the null hypothesis and conclude that the training did not have a significant effect.

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The Maclaurin series for f(x) = ln(1 - 9x^2) is: f(x) = -9x^2 + (81/2)x^4 - (243/3)x^6 + ... And the radius of convergence is R = 1/3. The correct answer is D) R = 1/3.

To find the Maclaurin series for f(x) = ln(1 – 9x^2)^2, we can start by finding the derivative of f(x) and evaluating it at x=0 to find the coefficients of the series: f(x) = ln(1 – 9x^2)^2
f'(x) = 2(ln(1 – 9x^2))(1 – 9x^2)'
      = 2(ln(1 – 9x^2))(-18x)
f''(x) = 2[(ln(1 – 9x^2))'(-18x) + (ln(1 – 9x^2))(-18)]
        = 2[(-18x/(1 – 9x^2))(-18x) - 18(ln(1 – 9x^2))]
        = 324x^2/(1 – 9x^2)^2 - 36(ln(1 – 9x^2))
We can see a pattern emerging with these derivatives, where the nth derivative of f(x) can be expressed as:
f^(n)(x) = (-1)^(n-1)2^(n-1)(n-1)! 324x^(2n-2) / (1 – 9x^2)^n - (-1)^n 2^(n-1)(n-1)! 36(ln(1 – 9x^2))
Now we can write out the Maclaurin series for f(x) by summing up these derivatives multiplied by the appropriate power of x:
f(x) = Σ(-1)^(n-1)2^(n-1)(n-1)! 324x^(2n-2) / (1 – 9x^2)^n - Σ(-1)^n 2^(n-1)(n-1)! 36(ln(1 – 9x^2))
The radius of convergence R of this series can be found using the ratio test:
lim |a_(n+1)/a_n| = lim [(n/(n+1))(1/3)]|(1 – 9x^2)/(1 – 9(x/2)^2)|
                  = lim (n/(n+1))^(1/2) |(1 – 9x^2)/(1 – 81x^2)|
                  = 1/3
So the series converges for |x| < 1/3, and therefore the radius of convergence is R = 1/3. Therefore, the answer is D) R = 1/3.

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Answer:

π(17^2 - 12^2) = (289 - 144)π

= 145π square inches

= 455.5 square inches

Since we need to use 3.14 for π:

145(3.14) = 455.3 square inches

Answer:

455.3 square inches

Step-by-step explanation:

An initial value problem for the mass of the substance is [tex]m'(t) = 0.005m(t) - 40, m(0) = 0[/tex]  and the solution to the initial value problem is [tex]m(t) = 160000e^{(0.005t)} - 160000[/tex].

a. The correct answer is [tex]m'(t) = 0.005m(t) - 40, m(0) = 0[/tex]. This is because the rate of change of the mass of substance b is proportional to the amount of substance present, and is also affected by the inflow and outflow rates.

b. To solve the initial value problem, we use separation of variables:

[tex]m'(t) = 0.005m(t) - 40[/tex]

[tex]m'(t) + 40 = 0.005m(t)[/tex]

[tex](1/0.005)m'(t) + 8000 = m(t)[/tex]

We can then solve for m(t):

[tex](1/0.005)m'(t) + 8000 = m(t)[/tex]

[tex](1/0.005)(m'(t) + 160000) = m(t)[/tex]

[tex]m(t) = Ce^{(0.005t)} - 160000[/tex]

Using the initial condition m(0) = 0, we get:

[tex]0 = Ce^0 - 160000[/tex]

C = 160000

Therefore, the solution to the initial value problem is: [tex]m(t) = 160000e^{(0.005t)} - 160000[/tex]

In summary, the initial value problem for the mass of substance b is [tex]m'(t) = 0.005m(t) - 40, m(0) = 0[/tex] . We solved the initial value problem using separation of variables and obtained the solution [tex]m(t) = 160000e^{(0.005t)} - 160000.[/tex]

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Complete Question:

For the following stirred tank reaction, carry out the following analysis.

a. Write an initial value problem for the mass of the substance

b. Solve the initial value problem

A 400-L tank is initially filled with pure water: A copper sulfate solution with a concentration of 20 g / L flows into the tank at a rate of 2 LJ min: The thoroughly mixed solution is drained from the tank at a rate of 2 L min.

a. Write an initial value problem for the mass of the substance. Choose the correct answer below:

m'(t) = 0.1 m(t) + 20, m(0) = 20

m'(t) = 0.005m(t) - 40, m(0) = 0

m'(t) = -0.1 m(t) - 20, m(0) = 20

m'(t) = 0.1 m(t) - 20, m(0) =20

m'(t) = 0.005m(t) + 40, m(0) = 0

m'(t) = 0.1m(t) + 20,m(O) = 20

m' (t) = - 0.0O5m(t) + 40, m(0) = 0

m'(t) = 0.005m(t) - 40,m(0) = 0

b. Solve the initial value problem: m(t)