a sample of n = 6 scores has a mean of m = 24. what is σx for this sample?

The ship’s horizontal distance from the lighthouse is  approximately 480.1 feet.

To solve it, we can make use of the tangent function.

Let x represent the horizontal separation between the boat and the lighthouse.

The lighthouse beacon is then at the top of the triangle, the boat is at the bottom, and the adjacent side is the horizontal distance x. 13° is the elevation angle, which is the angle perpendicular to x. The 126-foot height of the lighthouse beacon above the water is on the opposing side.

tan(13°) = [tex]\frac{126}{x}[/tex]

Multiplying both sides by x, we get:

x × tan(13°) = 126

Dividing both sides by tan(13°), we get:

x =  [tex]\frac{126}{tan(13)}[/tex]

Using a calculator, we find:

x ≈ 480.1 feet

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The probability that at least one of the 7 randomly chosen items will have a defect is approximately 52.17%

A manufacturing machine has a 9% defect rate. If 7 items are chosen at random, the probability that at least one will have a defect can be found using the complement probability.

First, find the probability of an item not having a defect, which is 91% (100% - 9%). Then, calculate the probability of all 7 items being defect-free: (0.91)7 ≈ 0.4783.

To find the probability that at least one item has a defect, subtract the probability of all items being defect-free from 1: 1 - 0.4783 ≈ 0.5217.

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.

Answer:

9

Step-by-step explanation:

Find the area of the rectangle. 5 x 3 = 15

Because the dilated area is 135, all you have to do it 135 divided by 15 which gives you 9!

The derivative of the function y = cosπx at x = 1 is 0.02sinπ(1) - 0.02sinπ(0.98).

Function is a block of code that performs a specific task. It is a self-contained unit of code that takes inputs, performs certain operations, and returns an output. Functions are often used to reduce code repetition and increase code readability. It is also used to make programs more efficient and easier to maintain.

Using the definition of the derivative, we can calculate dy by taking the limit as dx approaches 0.

dy = lim dx→0 (cosπ(1 + dx) - cosπ(1))/dx

= lim dx→0 (cosπ(1 - 0.02) - cosπ(1))/(-0.02)

= lim dx→0 (cosπ(0.98) - cosπ(1))/(-0.02)

= lim dx→0 (-(cosπ(1) - cosπ(0.98))/-0.02)

= lim dx→0 (0.04sinπ(1) - 0.04sinπ(0.98))/0.02

= lim dx→0 (0.04sinπ(1) - 0.04sinπ(0.98))/0.02

= (0.04sinπ(1) - 0.04sinπ(0.98))/0.02

= 0.02sinπ(1) - 0.02sinπ(0.98)

Therefore, dy = 0.02sinπ(1) - 0.02sinπ(0.98).

This calculation shows that the derivative of the function y = cosπx at x = 1 is equal to 0.02sinπ(1) - 0.02sinπ(0.98). This result is consistent with the definition of the derivative, which states that the derivative is the rate of change of a function with respect to its independent variable. In this case, the rate of change of the cosine function with respect to x is 0.02sinπ(1) - 0.02sinπ(0.98).

In conclusion, the derivative of the function y = cosπx at x = 1 is 0.02sinπ(1) - 0.02sinπ(0.98).

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The Polar cordinates is  ∫∫h(ρ, θ) = ∫(0 to 2√32)∫(0 to π/4) ρ dρ dθ.


To convert the given integral to polar coordinates, follow these steps:

1. Identify the Cartesian integral bounds: x ranges from 1/2√0 to 1 and y ranges from 1 - 2√32 to 32.

2. Determine the polar integral bounds: ρ ranges from 0 to 2√32, and θ ranges from 0 to π/4 (as the angle θ increases from 0 to π/4, the polar curve covers the region of interest).

3. Express the integrand in polar coordinates: The Jacobian of the polar coordinate transformation is ρ, so the integrand becomes ρ.

4. Write the integral in polar coordinates: ∫(0 to 2√32)∫(0 to π/4) ρ dρ dθ.

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The null hypothesis would be H0: p = 0.05. The alternative hypothesis would be Ha: p < 0.05.

When forming hypotheses in this context, we typically state a null hypothesis (H0) and an alternative hypothesis (H1). Here's how you can fill in the blanks:

Null hypothesis (H0): The percentage of U.S. adults who suffer from a mental illness has not changed. H0: p = 0.05

Alternative hypothesis (H1): The percentage of U.S. adults who suffer from a mental illness has decreased. H1: p < 0.05

In this case, "p" represents the percentage of U.S. adults with a mental illness. The social worker will use statistical tests to analyze data and determine if there is enough evidence to reject the null hypothesis in favor of the alternative hypothesis.

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For this mass and spring system, the period of the simple harmonic motion is 1.42 seconds.

The period of simple harmonic motion can be calculated using the formula T = 2π√(m/k), where T is the period, m is the mass, and k is the spring constant.

In this case, the mass is 2 N, which is equivalent to 0.204 kg (using g = 9.8 m/s^2). The spring constant is 4 N/m.

So, plugging the values into the formula, we get:

T = 2π√(0.204 kg/4 N/m)
T = 2π√(0.051 m)
T = 2π(0.226 s)
T = 1.42 s

Therefore, the period of simple harmonic motion for this mass and spring system is 1.42 seconds.

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a. null hypothesis [tex]H_0[/tex]: PRmean=non-PRmean

b. the sample mean lies in the interval, so we fail to reject null hypothesis

c. critical value z(0.05)=1.96 is less than calculated z=3.56 so we fail to accept null hypothesis.

A null hypothesis states that there is no statistical significance to be discovered in the set of presented observations. The validity of a theory is assessed through hypothesis testing on sample data. Sometimes known as the "null," it is represented by the symbol  [tex]H_0[/tex].

(a)

null hypothesis  [tex]H_0[/tex]: PRmean=non-PRmean

(b).

i. [tex](1-\alpha)\times 100\%[/tex] confidence interval for sample

[tex]mean=mean \pm z(\frac{\alpha }{2} )*SE(mean)[/tex]

95% confidence interval for sample PRmean=PRmean±z(.05/2)*SE(mean)=69.5±1.96*1.9

=69.5±3.724=(65.776,73.224)

95% confidence interval for sample non-PRmean=non-PRmean±z(.05/2)*SE(mean)=61.2±1.96*1.7

=69.5±3.332=(57.868, 64.532)

ii. null hypothesis not be rejected

iii. since the sample mean lies in the interval, so we fail to reject null hypothesis

(c).

i. mean difference=69.5-61.5=8

ii. SE(difference)=[tex]\sqrt{SE(PR)^2+SE(non-PR)^2}[/tex]

[tex]=\sqrt{1.9\times 1.9+1.2\times 1.2}[/tex]

=2.2472

iii. we use z-test and z=(mean difference)/SE(difference)=8/2.2472=3.56

iv. here level of significance alpha is not mentioned,

let [tex]\alpha[/tex] =0.05

critical value z(0.05)=1.96 is less than calculated z=3.56 so we fail to accept null hypothesis.

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The mean weight of American adults in 2005 was 167 pounds, the tour operators should have been more cautious in evaluating the boat's weight capacity given this information.

To answer this question, we need to use the concept of the sampling distribution of the mean.

We know from the given information that the population mean weight of American adults in 2005 was 167 pounds with a standard deviation of 35 pounds.

However,

We are interested in the average weight of a sample of 47 passengers from the Ethan Allen boat.
Assuming that the weights of the passengers on the boat were normally distributed, we can calculate the standard error of the mean using the formula:
standard error of the mean = standard deviation / square root of sample size
Plugging in the given values, we get:
standard error of the mean = 35 / √47
standard error of the mean ≈ 5.09
Now, to find out how surprising it is for a sample of 47 passengers to have an average weight of at least 7500/47 = 159.57 pounds, we need to calculate the z-score:
z-score = (sample mean - population mean) / standard error of the mean
z-score = (159.57 - 167) / 5.09
z-score ≈ -1.45
Looking at the standard normal distribution table, we can see that the probability of getting a z-score of -1.45 or less is about 0.073.

This means that if we took 100 random samples of 47 passengers from the Ethan Allen boat, we would expect to see a sample mean weight of 159.57 pounds or less in about 7.3 of those samples.
Therefore,

It is not very surprising to see a sample of 47 passengers from the Ethan Allen boat with an average weight of at least 159.57 pounds given the weight capacity of the boat.

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(a) A 90% confidence interval for the proportion of US adults favoring taxes on soda and junk food is (0.293, 0.347).

(b) The margin of error is 2.7%.

(c) To achieve a 1% margin of error with 90% confidence, a sample size of 6,811 is needed.


(a) To find the 90% confidence interval, use the formula CI = p ± Z * √(p(1-p)/n), where p is the proportion, Z is the Z-score for 90% confidence (1.645), and n is the sample size.
p = 0.32, n = 1000
CI = 0.32 ± 1.645 * √(0.32(1-0.32)/1000) = (0.293, 0.347)

(b) The margin of error is half the width of the confidence interval.
Margin of error = (0.347 - 0.293) / 2 = 0.027 or 2.7%.

(c) To find the needed sample size for a 1% margin of error, use the formula n = (Z²* p * (1-p)) / E², where E is the desired margin of error (0.01).
n = (1.645² * 0.32 * (1-0.32)) / 0.01² = 6810.8, rounding up to 6,811.

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Answer:

=715.92ft-2

Step-by-step explanation:

first find the area of the two circles by 2πr-2

then find the perimeter of one circle and use it as length and multiply it with 13ft and add the areas to get the answer

The equation of the transformed exponential function g(x) is g(x) = 2^-x - 1

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

Parent function: y = 2^x

The graph of the transformed exponential function g(x) passes through the points  (-2,3), (-1,1), (0,0), (1,-0.5) and (2, -0.75)

So, we have the following transformation steps:

1st Transformation:

Reflect y = 2^x across the y-axis

So, we have

y = 2^-x

2nd Transformation:

Translate y = 2^-x down by 1 unit

So, we have

y = 2^-x - 1

This means that

g(x) = 2^-x - 1

Hence, the equation of the function g(x) is g(x) = 2^-x - 1

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Each conditional probability is computed based on the two preceding words. For example, we can write: p(is|There) = p(is|There, _)

Assuming that we are working with a corpus of text and that the probabilities are based on the frequency of co-occurring words, we can use the chain rule to write the joint probability as:

p(There, is, only, one, person, who, is, not, ordinary) = p(There) × p(is|There) × p(only|There is) × p(one|is only) × p(person|only one) × p(who|one person) × p(is|person who) × p(not|who is) × p(ordinary|is not)

To compute this joint probability using the second-order Markov assumption, we would need to consider the probabilities of words given the two previous words. We can write this as:

p(There, is, only, one, person, who, is, not, ordinary) = p(There) × p(is|There) × p(only|There is) × p(one|is only) × p(person|only one) × p(who|one person) × p(is|person who) × p(not|who is) × p(ordinary|is not)

where each conditional probability is computed based on the two preceding words. For example, we can write: p(is|There) = p(is|There, _)

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On average, an individual waiting at the bus stop will wait 15 minutes to get on a bus.

Time in mathematics is a concept that is used to measure and record the passing of events. It is used to measure the duration between two events. Time is also used to measure the rate of change of a certain quantity over time. Time is expressed as a numerical quantity, such as seconds, minutes, hours, days, weeks, months, and years, and can be measured in increments such as fractions of a second, milliseconds, and nanoseconds. In mathematics, time is often represented using the Cartesian coordinate system, with the x-axis representing the passing of time and the y-axis representing the value of the quantity being measured.

The average wait time at the bus stop is 15 minutes. This is because Bus A and Bus B pass in a 30-minute cycle. Bus A passes 10 minutes after Bus B has passed, and Bus B passes 20 minutes after Bus A has passed. Therefore, an individual waiting at the bus stop will wait an average of 15 minutes to get on a bus.

To calculate this average wait time, we can use the following formula:

AverageWaitTime = (TimeBusAPasses + TimeBusBPasses) / 2

Using the given information, we can plug in the values for each bus:

AverageWaitTime = (10 minutes + 20 minutes) / 2
AverageWaitTime = 15 minutes

Therefore, on average, an individual waiting at the bus stop will wait 15 minutes to get on a bus.

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The Laplace transform of f(t) can be computed using the integral formula and the exponential integral, and is given by [tex]-Ei(-(s+2))[/tex] for [tex]Re(s) > -2[/tex].

To compute the Laplace transform of a function, we first need to define the function and then apply the Laplace transform integral formula. In this case, we have:

f(t) = { 0 if [tex]t < 0, e^(-2t)[/tex] if [tex]t >= 0[/tex]}

The Laplace transform of this function can be computed using the integral formula:

F(s) = L{f(t)} = ∫[0, ∞)[tex]e^(-st) f(t) dt[/tex]

where s is a complex variable.

Using the definition of f(t) and splitting the integral into two parts, we can write:

F(s) = ∫[0, ∞) [tex]e^(-st) e^(-2t) dt[/tex]

To evaluate this integral, we can use integration by substitution, letting u = (s+2)t. Then, du/dt = s+2 and dt = du/(s+2). Substituting in the integral, we get:

F(s) = ∫[0, ∞) [tex]e^(-u) du/(s+2)[/tex]

Using the definition of the exponential integral, Ei(x) = - ∫[-x, ∞) [tex]e^(-t)/t dt[/tex], we can write:

F(s) = -Ei(-(s+2))

Therefore, the Laplace transform of f(t) is given by:

F(s) = { -Ei(-(s+2)) if Re(s) > -2, ∞ if Re(s) <= -2 }

where Re(s) denotes the real part of s.

In summary, the Laplace transform of f(t) can be computed using the integral formula and the exponential integral, and is given by -Ei(-(s+2)) for Re(s) > -2.

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The setting of the machine should be no more than 6.135 milliliters per can of paint to ensure that no more than 2.5% of the cans of paint will be unacceptable.

A continuous probability distribution known as the normal distribution is frequently used to simulate symmetric and bell-shaped real-world phenomena. The mean and the standard deviation are the two factors that define it. Because of its numerous characteristics and uses, the normal distribution is significant in statistics and data analysis. The assumption that the data are normally distributed or may be approximated by a normal distribution is made by many statistical tests and confidence ranges, for instance.

Let us suppose the amount of dye discharged = X.

Thus, X ~ N(μ, σ).

Now, for μ such that no more than 2.5%:

P(X > 6.4) ≤ 0.025

Using the z-score we have:

Z = (X - μ) / σ

P(X > 6.4) = P((X - μ) / σ > (6.4 - μ) / σ) = P(Z > (6.4 - μ) / σ)

(6.4 - μ) / 0.1342 > 1.96

μ < 6.4 - 1.96(0.1342) = 6.135

Hence, the setting of the machine should be no more than 6.135 milliliters per can of paint to ensure that no more than 2.5% of the cans of paint will be unacceptable.

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Events A and B are mutually exclusive.

Prime numbers are numbers that are greater than 1 and have only two distinct positive divisors, which are 1 and the number itself. In this case, the prime numbers among the digits 0 through 9 are 2, 3, 5, and 7, as they are not divisible by any other number within the given range.

Odd numbers are numbers that are not divisible by 2, meaning they have a remainder of 1 when divided by 2. In this case, the odd numbers among the digits 0 through 9 are 1, 3, 5, 7, and 9.

Upon comparing the prime numbers (2, 3, 5, 7) and odd numbers (1, 3, 5, 7, 9) within the range of 0 through 9, it is evident that the numbers 3 and 5 are common to both events A and B, as they are both prime and odd.

Mutually exclusive events refer to events that cannot occur simultaneously. If one event occurs, the other cannot occur at the same time. In this case, event A (obtaining a prime number) and event B (obtaining an odd number) are mutually exclusive, as the numbers 3 and 5 are the only numbers that satisfy both events, and only one outcome can occur.

Therefore, events A and B are mutually exclusive, as they cannot occur simultaneously.

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Therefore, the variance of the lognormal distribution for this company is approximately 322196.29 (dB/hour)^2.

To find the mean power usage (average dB per hour) for a lognormal distribution with parameters 4 and ơ-2, we use the formula:

[tex]Mean = e^{u+ o^{2/2}}\\=e^{u+o}[/tex]

where μ is the mean of the logarithm of the data (in this case, μ = 4) and σ is the standard deviation of the logarithm of the data (in this case, σ = -2).

Substituting the values, we get:

Mean = [tex]e^{(4 + (-2)^{2/2}}  

 = e^{(4 + 2)}

   = e^6[/tex]
    ≈ 403.43 dB/hour

Therefore, the mean power usage for this company is approximately 403.43 dB per hour.

To find the variance of the lognormal distribution, we use the formula:
[tex]Variance = (e^{o^2} - 1) * e^{2u + o^2}[/tex]

Substituting the values, we get:

[tex]Variance = (e^(-2) - 1) * e^(2*4 + (-2)^2)\\         = (1/e^2 - 1) * e^(8 + 4)\\         = (1/7.389 - 1) * e^{1/2}\\         = 322196.29[/tex]
Therefore, the variance of the lognormal distribution for this company is approximately 322196.29 (dB/hour)^2.

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The possible values of a and b that satisfy the criteria are (4, -49) and (-4, 103).

We need to use the properties of the Chi-Square Distribution.

Given: X is a random variable from a Chi-Square Distribution with 19 degrees of freedom. We have Y = aX + b, where E(Y) = 27 and V(Y) = 608.

Step 1: Compute E(X) and V(X) for a Chi-Square Distribution with 19 degrees of freedom.
E(X) = ν, where ν is the degrees of freedom.
E(X) = 19

V(X) = 2ν
V(X) = 2(19) = 38

Step 2: Use the properties of expected value and variance to find the expressions for E(Y) and V(Y) in terms of a and b.
E(Y) = E(aX + b) = aE(X) + b
V(Y) = V(aX + b) = a² × V(X)

Step 3: Plug in the given values for E(Y) and V(Y) and solve for a and b.
27 = a(19) + b (1)
608 = a² × 38

Step 4: Solve for a.
a² = 608/38
a² = 16
a = ±4

Step 5: Solve for b using the value of a.
For a = 4:
27 = 4(19) + b
27 = 76 + b
b = -49

For a = -4:
27 = -4(19) + b
27 = -76 + b
b = 103

Step 6: Write the answer as ordered pairs.
The possible values of a and b that satisfy the criteria are (4, -49) and (-4, 103).

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You have a project completion time of 60 days, and a non-critical path with 5 days of slack was delayed by 10 days. The correct answer is option ii. 65. The new project completion time after the delay of the non-critical task is 65 days.

To determine the new project completion time, follow these steps:

1. Determine the impact of the delay on the project completion time:

Since the non-critical path has 5 days of slack, it means that it can be delayed by up to 5 days without affecting the project completion time. However, the task was delayed by 10 days, which is 5 days more than its slack.

2. Calculate the new project completion time:

To find the new project completion time, add the extra delay (5 days) to the original project completion time (60 days).

New project completion time = Original project completion time + Extra delay
New project completion time = 60 days + 5 days
New project completion time = 65 days

So, the new project completion time is 65 days.

Based on the given options:
i. 60 - Incorrect, as the delay affects the project completion time.
ii. 65 - Correct, as calculated above.
iii. 70 - Incorrect, as the delay is not long enough to push the project completion time to 70 days.
iv. 55 - Incorrect, as the delay increases the project completion time, not decreases it.

Therefore, the correct answer is option ii. 65. The new project completion time after the delay of the non-critical path is 65 days.

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Answer:

Step-by-step explanation:

We can use trigonometry to solve this problem. Let's call the height of the antenna h and the length of the wire connecting the top of the antenna to the ground d.From the problem statement, we know that d = 7 feet and the angle of elevation θ is 75 degrees. The angle of elevation is the angle between the horizontal and the line of sight to the top of the antenna.We can use the tangent function to find h:tan(θ) = opposite / adjacentIn this case, the opposite side is the height of the antenna h, and the adjacent side is the length of the wire d + 0. This is because the wire touches the ground at a point 7 feet away from the base of the antenna, so the total length of the wire is d + 0.Substituting the values we have:tan(75 degrees) = h / (7 feet + 0)Simplifying:h = (7 feet) × tan(75 degrees)Using a calculator:h ≈ 24.16 feetTherefore, the height of the antenna is approximately 24.16 feet.

The  corners of the frame are 90°

You should recall that a right triangle is an orthogonal triangle in which one angle is 90°. The sides of a right triangle are commonly referred to with the variables a, b, and c, where c is the hypotenuse and a and b are the lengths of the shorter sides. Their angles are also typically referred to using the capitalized letter corresponding to the side length.

Let the corners of the canvas frame be right angle triangles

the AB² = aC² + BC²

THE AB = AC = √18²+24²

⇒ AC =√324 + 576

This means that Ac = √900

AC = 30

Therefore fore when the ruler measure 30 inches feet on the diagonal, the angle of the frame is a right angle

If the sides of a right angle  are A,B and the hypothenuse is C

The A² + B² = C²

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The function f(x,y) has a line of discontinuity along the x-axis (i.e., y=0) and the y-axis (i.e., x=0).

What is function?

In mathematics, a function is a relationship between two sets of elements, called the domain and the range, such that each element in the domain is associated with a unique element in the range. In simpler terms, a function is a set of rules that takes an input value and produces a corresponding output value.

The function f(x,y) = ln|xy| is discontinuous along the lines x=0 and y=0.

To see this, consider approaching the origin along different paths. For example, if we approach the origin along the x-axis (i.e., y=0), then we have f(x,0) = ln|0|, which is undefined. Similarly, if we approach the origin along the y-axis (i.e., x=0), then we have f(0,y) = ln|0|, which is also undefined.

Therefore, the function f(x,y) has a line of discontinuity along the x-axis (i.e., y=0) and the y-axis (i.e., x=0).

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The function f(x,y) has a line of discontinuity along the x-axis (i.e., y=0) and the y-axis (i.e., x=0).

What is function?

In mathematics, a function is a relationship between two sets of elements, called the domain and the range, such that each element in the domain is associated with a unique element in the range. In simpler terms, a function is a set of rules that takes an input value and produces a corresponding output value.

The function f(x,y) = ln|xy| is discontinuous along the lines x=0 and y=0.

To see this, consider approaching the origin along different paths. For example, if we approach the origin along the x-axis (i.e., y=0), then we have f(x,0) = ln|0|, which is undefined. Similarly, if we approach the origin along the y-axis (i.e., x=0), then we have f(0,y) = ln|0|, which is also undefined.

Therefore, the function f(x,y) has a line of discontinuity along the x-axis (i.e., y=0) and the y-axis (i.e., x=0).

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when you add all the answers up and divide by 2 is your answer

Answer:

P=17/30

Step-by-step explanation:

The amount of wire does she have remaining after the first day is,

⇒ 27.558 meters

We have to given that;

An electrician has 42.3 meters of wire to use on a job on the first day she uses 14.742 meters of the wire.

Now, We can formulate;

The amount of wire does she have remaining after the first day is,

⇒ 42.3 - 14.742

⇒ 27.558 meters

Thus, The amount of wire does she have remaining after the first day is,

⇒ 27.558 meters

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The value of the integral is approximately 106.438.

To evaluate the integral, we can make the substitution u = x² and v = y². Then, we have the Jacobian of the transformation as J = 2xy.

Next, we need to find the new limits of integration for u and v.

When x-y=0, we have u - v = 0, so u = v. When x-y=2, we have u - v = 2, so u = v + 2. When xy=0, either u or v must be 0. When xy=3, we have u × v = 3.

Converting these limits of integration to u and v, we have:

0 <= v <= 3/u
v <= u <= v+2

Using the Jacobian and the change of variables, the original integral becomes:

double integral (x y)8e^x² y²da = double integral (uv)8e^(u+v) × 2√(uv) dudv

Integrating with respect to u first, we get:

integral from v to v+2 of [16√(v) × e^(u+v)] du

Using integration by parts, we can evaluate this integral to get:

16sqrt(v) × (e^(2v) - e^v)

Then, integrating with respect to v, we get:

integral from 0 to 3/u of [16sqrt(v) × (e^(2v) - e^v)] dv

This integral can be evaluated using integration by parts again, and we get:

32/3 × (u^(3/2) - 1/e × u^(3/2))

Finally, substituting back in for u and v, we have:

integral from 0 to 3 of [32/3 × (x^3/2 - 1/e × x^3/2)] dx

This can be evaluated using basic calculus, and the final answer is:

(32/3) × (27/2 - 2/e)

Therefore, the value of the integral is approximately 106.438.

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A negative z-score implies that the value is less than the mean. This suggests that the data point is more diminutive than the common amount of data set.

While a z-score of zero reveals that the data point sits at exactly the mean of the data set. Which means, the data point is normal, neither bigger nor smaller than the mean.

Substituting the given values and solving for x, we get:

1.80 = (x - 75) / 10

x - 75 = 18

x = 93

Therefore, Brittany's score was 93.

Substituting the given values and solving for μ, we get:

1.25 = (80 - μ) / 4

80 - μ = 5

μ = 75

Therefore, the mean was 75.

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Step-by-step explanation:

Angles R and D are the same just as RSW is to ESD

Answer:

  (x -10)²/64 +(y +8)²/100 = 1

Step-by-step explanation:

You want the equation of the ellipse with center (10,-8), a focus at (10, -14), and a vertex at (10, -18).

The length of the semi-major axis is the distance between the center and the give vertex: a = -8 -(-18) = 10 units.

The distance from the center to the focus is -8 -(-14) = 6.

The distance from the center to the covertex is the other leg of the right triangle with these distances as the hypotenuse and one leg.

  b = √(10² -6²) = √64 = 8 . . . . units

The equation for the ellipse with semi-axes 'a' and 'b' with center (h, k) is ...

  (x -h)²/b² +(y -k)²/a² = 1

  (x -10)²/64 +(y +8)²/100 = 1

__

Additional comment

The center, focus, and given vertex are all on the vertical line x=10, This means the major axis is in the vertical direction, and the denominator of the y-term will be the larger of the two denominators.

You will notice the center-focus-covertex triangle is a 3-4-5 right triangle with a scale factor of 2.

If X has a density function given by a function called as f(x), then density function E[X] = ∞.

Since the integral diverges and density function as x approaches infinity, the expected value of X does not exist. This can also be seen by noting that f(x) is a right-skewed distribution with a long tail, and so it does not have a finite mean.

Here E[X], we can use the formula:

E[X] = ∫ x f(x) dx,

Here f(x) is the probability density function of X.

For this problem, we have:

0 otherwise.

So, we can write:

E[X] = [tex]x (1/4 x e^{(x/2)}) dx\\= (1/4) x^2 e^{(x/2)} dx[/tex]

We can use integration by parts with u = [tex]x^2[/tex]and dv/dx = (x/2):

[tex]E[X] = (1/4) [x^2 e^{(x/2)} - 2x e^{(x/2)} dx]\\= (1/4) [x^2 e^{(x/2)} - 4x e^{(x/2)} + 8 e^{(x/2)}] + C[/tex]

HereC is the constant of integration. Since f(x) is a probability density function, it must integrate to 1 over its support (which in this case is (0, ∞)):

∫ f(x) dx = ∫ 1/4 x [tex]e^{(x/2)[/tex] dx = 1

So we can solve for C:

C = -1/2

Therefore, the expected value of X is:

E[X] = [tex](1/4) [x^2 e^{(x/2)} - 4x e^{(x/2)} + 8 e^{(x/2)]} - 1/2[/tex]

To evaluate this expression, we can use the limits of integration (0, ∞):

E[X] = [tex](1/4) [(\alpha )^2 e^(\alpha /2) - 4(\alpha ) e^(\alpha /2) + 8 e^(\alpha /2)] - 1/2[/tex]

= ∞

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Correct Question:

Compute E[X] if X has a density function given by f(x) = {1/4 xe^x/2 if x > 0

or 0 if x < 0