Listen Without using a calculator, compute sin (72). Hint : use a sum fromula and the fact that + 5 = 12

The 95% confidence interval for the population mean annual earnings will be constructed as (2909.69, 3330.31)

To construct the confidence interval for the population mean, we can use the formula:

Confidence interval = sample mean +/- (critical value) x (standard error)

where the critical value is based on the desired confidence level (95% in this case), and the standard error is calculated as the population standard deviation divided by the square root of the sample size.

Plugging in the given values, we get:

Confidence interval = 3120 +/- (1.96) x (677/√(40))
Confidence interval = 3120 +/- 210.31

Therefore, the 95% confidence interval for the population mean annual earnings is (2909.69, 3330.31). This means we can be 95% confident that the true population mean falls within this range.

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The centroid of the region is (x, y) = (10, 1000/3).

(x, y) = (10, 1000/3)

1. Set up the equation for the centroid formula: x = (1/A)∫y dx and y = (1/A)∫x dy

2. Find the area of the region: A = ∫(y2 - y1) dx

3. Calculate the integral: ∫y dx = x4/4 + C and ∫x dy = xy + C

4. Substitute the boundaries into the integrals and solve for C: x4/4 + C = 30x and xy + C = 0

5. Substitute the solutions for C in the centroid formula: x = (1/A)∫y dx = (1/A)(30x - x4/4) and y = (1/A)∫x dy = (1/A)(xy - 0)

6. Substitute the boundaries into the area equation and solve for A: A = ∫(y2 - y1) dx = ∫(30x - x4/4 - 0) dx = 30x2/2 - x5/5 + C

7. Substitute the solutions for C in A: A = 30x2/2 - x5/5 + C = 30(30)2/2 - (30)5/5 + C = 27000/2 - 27000 + C = 13500 + C

8. Substitute the solutions for C in the centroid formula and solve for x and y: x = (1/13500 + C)(30x - x4/4) and y = (1/13500 + C)(xy - 0)

9. Substitute the boundaries into the centroid formula and solve for x and y: x = 10 and y = 1000/3

Therefore, the centroid of the region is (x, y) = (10, 1000/3).

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complete question:

Find the centroid of the region bounded by the given curves. y = x3, x + y = 30, y = 0 (x, y) = (10, 1000/3)

To assess the given fundamentally, we utilize the rules of integration.

When we evaluate∫(20x⁸ + 5x³ - 12/x⁵) dx ,we get the answer as

=(20/9)x + (5/4)x - 12ln|x| + C where, C is a self-assertive steady.

 The fundamental could be a numerical operation that finds the antiderivative of a work, which is the inverse of the subsidiary. The antiderivative of work can be found utilizing the control run of the show and the natural logarithm run of the show.

In this specific case, the necessity to assess are:

∫(20x⁸ + 5x³ - 12/x⁵) dx

Ready to apply the control run the show, which states that the antiderivative of xⁿ is (1/(n+1))x(n+1), where n may be consistent. Utilizing this run the show, we will discover the antiderivatives of each term within the integral:

∫(20x⁸) dx = (20/9)x + C1

∫(5x³) dx = (5/4)x + C2

∫(-12/x⁵) dx = -12ln|x| + C3

where C1, C2, and C3 are constants of integration.

To get the antiderivative of the whole necessarily, we include the antiderivatives of each term:

∫(20x⁸ + 5x³ - 12/x⁵) dx = (20/9)x + (5/4)x - 12ln|x| + C

where C is the consistency of integration.

Subsequently, the solution to the given fundamentally is:

∫(20x⁸ + 5x³ - 12/x⁵) dx = (20/9)x + (5/4)x - 12ln|x| + C

where C is a self-assertive steady. 

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The probability that the scooter came from Plant2 given that it is of standard quality is approximately 0.3861 or 38.61%

To find the probability that the scooter came from Plant2 given that it is of standard quality, we can use Bayes' theorem.

Let A be the event that the scooter comes from Plant2, and B be the event that the scooter is of standard quality. We want to find P(A|B), the probability that the scooter came from Plant2 given that it is of standard quality.

Using the formula for Bayes' theorem, we have:

P(A|B) = P(B|A) * P(A) / P(B)

where P(B|A) is the probability that a scooter from Plant2 is of standard quality, P(A) is the probability that a randomly chosen scooter came from Plant2, and P(B) is the probability that a randomly chosen scooter is of standard quality.

From the given information, we have:

P(B|A) = 0.96 (the probability that a scooter from Plant2 is of standard quality)
P(A) = 0.38 (the proportion of scooters manufactured by Plant2)
P(B) = P(B|A) * P(A) + P(B|not A) * P(not A)
    = 0.96 * 0.38 + 0.92 * 0.62 (using the law of total probability)
    = 0.9416

Substituting these values into Bayes' theorem, we get:

P(A|B) = 0.96 * 0.38 / 0.9416
      = 0.3861

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.

The next two terms of the sequence are 6 and -3.

A list of numbers or objects that adhere to a pattern or rule is referred to as a sequence in mathematics. The name for each number or item in the sequence is.

Sequences can take many various forms, but some of the most popular ones are as follows:

Arithmetic sequence: In an arithmetic sequence, each term is produced by multiplying the previous term by a constant amount (referred to as the common difference). For instance, the arithmetic sequence 2, 5, 8, 11, 14,... has a common difference of 3.

Sequence that is geometric: In a sequence that is geometric, each term is produced by multiplying the previous term by a constant (known as the common ratio). For instance, the geometric series 1, 2, 4, 8, 16,... has a common ratio of 2.

For the given sequence we observe that the next term is negative half of the previous term thus,

-12/-2 = 6

6/- 2 = -3

Hence, the next two terms of the sequence are 6 and -3.

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The only functions g such that the first difference of g is the zero function are constant functions.

The first part of the problem asks us to consider a constant function f. A constant function is a function that takes the same value for every input. For example, f(x) = 3 is a constant function, since it takes the value 3 for every input value of x. We are asked to show that the first difference of a constant function is the zero function. To see why this is the case, consider the formula for the first difference:

Of(x) = f(x+1) - f(x)

For a constant function, we have f(x+1) = f(x), since the function takes the same value for every input. Substituting this into the formula above, we get:

Of(x) = f(x+1) - f(x) = f(x) - f(x) = 0

This shows that the first difference of a constant function is indeed the zero function.

The second part of the problem asks whether there are any other functions g such that the first difference of g is also the zero function. In other words, we are looking for functions g such that g(x+1) - g(x) = 0 for all positive integer values of x.

To answer this question, we can use the fact that if the first difference of a function is the zero function, then the function must be a constant function.

To see why this is the case, suppose g(x+1) - g(x) = 0 for all x. Then we have g(x+1) = g(x) for all x, which means that the value of the function at any input value x+1 is the same as the value of the function at the input value x. In other words, the function takes the same value for every input value, which means that it is a constant function.

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An orthonormal basis for the column space of the matrix is

[ -1/√18, -1/√18, -4/√18 ]

[  2/√405,  7/√405, 16/√405 ]

To find an orthonormal basis for the column space of the given matrix, we first need to compute its reduced row echelon form (RREF) using Gaussian elimination:

-1 -1 -4 20 2

R1 <- R1 + R2

-1 0 -8 20 2

R1 <- -R1

1 0 8 -20 -2

R3 <- R3 - 8R2

1 0 0 -180 -18

So the RREF of the matrix is:

[ 1 0 0 -180 -18 ]

[ 0 0 1 -5/9 -1/9 ]

[ 0 0 0  0    0   ]

[ 0 0 0  0    0   ]

Therefore, the column space of the matrix is spanned by the first two columns of the original matrix, which are:

-1  20

-1   2

-4

We now need to orthogonalize these vectors using the Gram-Schmidt process. Let's call the first vector v1 and the second vector v2. We start by normalizing v1 to obtain a unit vector u1:

v1 = [-1, -1, -4]

u1 = v1 / ||v1|| = [-1/√18, -1/√18, -4/√18]

We then project v2 onto u1 and subtract the projection from v2 to obtain a vector w2 that is orthogonal to u1:

[tex]proj_{u1}(v2) = (v2 . u1) \times u1 = (20/\sqrt{18}) \times [-1/\sqrt{18} , -1/\sqrt{18}, -4/\sqrt{18}] = [-10/9, -10/9, -40/9][/tex]

[tex]w2 = v2 - proj_{u1}(v2) = [ 2/9, 7/9, 16/9 ][/tex]

Finally, we normalize w2 to obtain a unit vector u2 that is orthogonal to u1:

u2 = w2 / ||w2|| = [ 2/√405, 7/√405, 16/√405 ]

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The solution to the inequality X-8>-3 is X > 5.

The inequality given to us is X-8>-3. This means that X-8 is greater than -3. To solve for X, we need to isolate X on one side of the inequality sign, while keeping the inequality true.

First, we can add 8 to both sides of the inequality to get X by itself:

X - 8 + 8 > -3 + 8

This simplifies to:

X > 5

So we have found that the solution to the inequality X-8>-3 is all values of X that are greater than 5.

In other words, X can take on any value greater than 5, but it cannot be equal to 5. If X is equal to 5, then the inequality becomes 5-8>-3, which is not true.

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The rewritten expression of 8x + 20 using the distributive property is 4(2x + 5)

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

8x+ 20 distributive property

This means that

8x + 20

Factor out 4 from the equation

So, we have

8x + 20 = 4(2x + 5)

The above equation has been rewritten using the distributive property.

Hence, the rewritten expression using the distributive property is 4(2x + 5)

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To find the approximate standard deviation of the maximum likelihood estimate (MLE) using the bootstrap method, we need to generate multiple samples by resampling from the original data with replacement. For each sample, we calculate the MLE and store the value. We repeat this process for a large number of times (e.g., 1000) to get a distribution of MLE values. Then, we can calculate the standard deviation of this distribution as an approximation of the standard deviation of the MLE.

In R, we can implement this as follows:
1. Store the original data:
counts <- c(1997, 906, 904, 32)
2. Define a function to calculate the MLE:mle <- function(p) {
 return(sum(counts * log(c(0.25 * (2 + p), 0.25 * (1 - p), 0.25 * (1 - p), 0.25))))
}3. Generate multiple samples using the bootstrap method:n <- 1000
samples <- replicate(n, sample(counts, replace=TRUE))4. Calculate the MLE for each sample:
mle_values <- apply(samples, 2, mle)
5. Calculate the standard deviation of the MLE values:
sd_mle <- sd(mle_values)
To draw a histogram of the MLE values, we can use the hist() function in R:
hist(mle_values, breaks=20, main="Histogram of MLE Values", xlab="MLE", col="lightblue")
the bootstrap method can be used to estimate the standard deviation of the MLE for a given set of data. By resampling from the original data with replacement and calculating the MLE for each sample, we can get a distribution of MLE values. The standard deviation of this distribution can be used as an approximation of the standard deviation of the MLE. In this case, we used the bootstrap method to find the approximate standard deviation of the MLE for the counts of starchy and sugary progeny with green and white base leaves. We then drew a histogram of the MLE values using R.

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The proportion of the population between 24 and 32 is approximately 0.159, or 15.9%.

To find the proportion of a normal population between 24 and 32 with a mean (μ) of 40 and a standard deviation (σ) of 11, follow these steps:

1. Calculate the z-scores for 24 and 32 using the z-score formula: z = (X - μ) / σ
  For 24: z1 = (24 - 40) / 11 = -16 / 11 ≈ -1.45
  For 32: z2 = (32 - 40) / 11 = -8 / 11 ≈ -0.73

2. Use a z-table or calculator to find the proportion of the population corresponding to these z-scores.
  For z1 = -1.45:

p(z1) ≈ 0.074
  For z2 = -0.73:

p(z2) ≈ 0.233

3. Find the proportion of the population between z1 and z2 by subtracting p(z1) from p(z2).
  p(z2 - z1) = p(z2) - p(z1) = 0.233 - 0.074 = 0.159

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The displacement will only vary with time due to the sinusoidal function of the angular frequency w.

At time t=0,

the displacement of the string y (x,0) can be expressed as

y(x,0) = Acos(kx)sin(0)

since the angular frequency w is equal to zero at time t=0.

The sine of 0 is equal to 0, which means that the entire expression for y(x,0) is equal to 0.

Therefore, the displacement of the string at time t=0 is 0,

which is expected since the standing wave is at its equilibrium position at this point in time. It is important to note that the max transverse displacement (amplitude)

A and wave number k will still play a role in the shape and behavior of the standing wave, but they do not affect the displacement of the string at time t=0.

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to maximize the revenue, the musical theater group should charge approximately $6.04 per ticket.

Given terms:
1. Price of the ticket: $6
2. Theater capacity: 1400 seats
3. For every additional dollar charged, the number of people attending decreases

Let's use 'x' as the additional dollar charged on top of the initial $6 per ticket. Since the number of attendees decreases for every additional dollar charged, we can represent the number of people attending the theater as (1400 - 140x).

The total revenue earned by the theater group can be represented as the product of the price per ticket and the number of people attending: R = (6 + x)(1400 - 140x).

Now, to maximize the revenue, we need to find the maximum value of R with respect to 'x'. To do this, we'll differentiate R with respect to 'x' and set the derivative equal to zero.

Step 1: Differentiate R with respect to 'x'
[tex]dR/dx = -140^2x + 140(6 - x)[/tex]

Step 2: Set the derivative equal to zero to find the critical points
[tex]0 = -140^2x + 140(6 - x)[/tex]

Step 3: Solve for 'x'
0 = -19600x + 840 - 140x
19600x = 840 - 140x
19740x = 840
x ≈ 0.0426

Since 'x' represents the additional dollar charged, we need to add this value to the initial $6 per ticket price:

Optimal price per ticket ≈ $6 + $0.0426 ≈ $6.04

So, to maximize the revenue, the musical theater group should charge approximately $6.04 per ticket.

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The rate of change of the linear function is -2

A linear function can be described as two different but still related notions.

It is also described as a function whose graph is seen as a straight line, that is, having a polynomial function with its highest degrees as one or zero.

Note that the rate of change of a linear function is its slope.

From the information given, we have that;

Rate = 40 - 50/2 - 0

subtract the values

Rate = -10/2

Divide the values

Rate = -2

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The normal approximation to the binomial, the probability of getting X = 5 successes is approximately 0.0052.

To find the probability using the normal approximation to the binomial, you will need to convert the binomial distribution to a normal distribution by finding the mean (μ) and standard deviation (σ). Then, you'll use the z-score formula to find the probability for the specific value of X.

Given: n = 30, p = 0.4, and X = 5

1. Find the mean (μ) and standard deviation (σ):
μ = n * p = 30 * 0.4 = 12
σ = √(n * p * (1 - p)) = √(30 * 0.4 * 0.6) ≈ 2.74

2. Calculate the z-score for X = 5:
z = (X - μ) / σ = (5 - 12) / 2.74 ≈ -2.56

3. Use the z-score table or a calculator to find the probability for the z-score:
The probability for z = -2.56 is approximately 0.0052.

So, using the normal approximation to the binomial, the probability of getting X = 5 successes is approximately 0.0052.

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There exists a number c in the open interval (-1, 1) such that

f'(c) = 0. There are no numbers satisfying the theorem's conclusion in this case.

To apply Rolle's Theorem to f(x), we need to verify the following two

conditions:

f(x) is continuous on the closed interval [-1, 1].

f(x) is differentiable on the open interval (-1, 1).

Both of these conditions are satisfied by[tex]f(x) = x^4 - 2x^2 + 1[/tex]on the

interval [-1, 1],

since it is a polynomial function and therefore is continuous and

differentiable everywhere.

Now, Rolle's Theorem states that if f(x) satisfies the above conditions and

f(-1) = f(1),

then there exists at least one number c in the open interval (-1, 1) such

that f'(c) = 0.

First, let's find f(-1) and f(1):

[tex]f(-1) = (-1)^4 - 2(-1)^2 + 1 = 4\\f(1) = 1^4 - 2(1)^2 + 1 = 0[/tex]

Since f(-1) does not equal f(1), we cannot apply Rolle's Theorem to

conclude that there exists a number c in the open interval (-1, 1) such that

f'(c) = 0.

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The print you specifically described is entitled "No se puede saber por qué" (translated as "One cannot know why") in Spanish.

Goya mocks the many superstitions and illogical ideas that were pervasive in Spanish culture at the time in this print. A crowd is gathered around a fortune teller who is looking into a crystal ball in the picture. The people are portrayed in a variety of excited and anxious states, indicating their readiness to accept the fortune teller's predictions in the face of a lack of proof or logic.

Even in modern times, the topic of irrational beliefs and superstitions persists, albeit it may take many forms depending on the culture or civilization. For instance, despite the fact that there is little scientific proof to back up their claims, some people continue to turn to astrology, psychics, or alternative medicine. Similar to this, false information and conspiracy theories are still proliferating quickly in the social media age, feeding irrational views and mistrust of authorities and organizations.

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The first derivative of f(x) is [tex]f'(x) = (x^2 - 6x + 7) / (x - 3)^2[/tex], and the second

derivative is[tex]f''(x) = 4 / (x - 3)^3[/tex].

To find the first derivative of the given function, we will use the quotient rule:

[tex]f(x) = (x^2 - 3x + 2) / (x - 3)\\f'(x) = [ (x - 3)(2x - 3) - (x^2 - 3x + 2)(1) ] / (x - 3)^2\\f'(x) = [ 2x^2 - 9x + 9 - x^2 + 3x - 2 ] / (x - 3)^2\\f'(x) = [ x^2 - 6x + 7 ] / (x - 3)^2[/tex]

To find the second derivative, we will use the quotient rule again:

[tex]f''(x) = [ (x - 3)^2(2x - 6) - (x^2 - 6x + 7)(2(x - 3)) ] / (x - 3)^4\\f''(x) = [ 2x^2 - 12x + 18 - 2x^2 + 12x - 14 ] / (x - 3)^3\\f''(x) = [ 4 ] / (x - 3)^3[/tex]

Now let's find the asymptotes. The function has a vertical asymptote at x = 3, since the denominator becomes zero at that point. To find the horizontal asymptote, we will divide the numerator by the denominator using long division:

   x + 1

___________

[tex]x - 3 | x^2 - 3x + 2\\x^2 - 3x[/tex]

-------

2x + 2

2x - 6

------

8

The quotient is x + 1 with a remainder of 8/(x - 3). As x approaches infinity or negative infinity, the remainder term becomes negligible, and the function approaches the line y = x + 1. Therefore, the horizontal asymptote is y = x + 1.

To find the y-intercept, we set x = 0:

[tex]f(0) = (0^2 - 3(0) + 2) / (0 - 3) = -2/3[/tex]

So the y-intercept is (0, -2/3).

To find the x-intercept, we set y = 0 and solve for x:

[tex]0 = (x^2 - 3x + 2) / (x - 3)\\0 = x^2 - 3x + 2[/tex]

Using the quadratic formula, we get:

x = (3 ± sqrt(9 - 8)) / 2

x = (3 ± 1) / 2

x = 2 or x = 1

So the x-intercepts are (2, 0) and (1, 0).

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The value of second order differentiation, that is d²y/dx² at x = 1 is 132 for function y= f(x) such that f(1) = 2 and dy/dx=y³+3 .

Hence option c is the correct answer.

The given function of x is, y = f(x)

y = f(x) is twice differentiable.

dy/dx = f'(x) = y³ + 3

Differentiation dy/ dx with respect to x, that is differentiating y = f(x) second time with respect to x, we get,

f''(x) = d²y / dx² = [d(dy/dx)] / dx

= d (y³ + 3) / dx

Thus by chain rule of differentiation we get,

f''(x) = d²y / dx² = 3y² (dy/dx)

= 3y² ( y³ +3)

= 3[tex]y^{5}[/tex] + 9y²

Since, f(1) = 2, it implies when x=1 , then y = 2 as y = f(x)

Therefore, d²y/dx² at x = 1  or f''(1) is,

f''(1) = 3[[tex](2)^{5}[/tex]] + [9(2²)]

= 96 + 36 = 132

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The vertical asymptote is x=-2. There is no horizontal asymptote.

To find the horizontal asymptote of f(x), we need to examine the behavior of f(x) as x approaches positive or negative infinity. Since the highest degree term in the function is 4x⁶, the function grows much faster than x+2. Therefore, as x approaches positive or negative infinity, the x+2 term becomes negligible compared to the 4x⁶ term, and f(x) approaches infinity. Therefore, there is no horizontal asymptote.

To find the vertical asymptotes, we need to look for values of x that make the denominator of the fraction (x+2) equal to zero. Since the denominator is x+2, the only value of x that makes it equal to zero is x=-2.

Therefore, the vertical asymptote is x=-2.

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The graph of [tex]y = -x^2[/tex] is the mirror image of [tex]y = x^2[/tex] with regard to the x-axis.

To reflect a function's graph across the x-axis, negate the y-coordinates of all the points on the original graph. In the case of [tex]y = x^2[/tex], this entails altering the sign of [tex]x^2[/tex] to produce the reflected function.

Beginning with the initial function [tex]y = x^2[/tex], multiply [tex]x^2[/tex] by (-1) to reflect it across the x-axis, yielding the equation:

[tex]y = -x^2[/tex]

This new equation reflects the reflection of the original function [tex]y = x^2[/tex]  across the x-axis, where the graph of [tex]y = -x^2[/tex] is the mirror image of [tex]y = x^2[/tex] with regard to the x-axis.

The graph of orignal function, [tex]y = x^2[/tex] (red) and transformed function(blue),    [tex]y = -x^2[/tex] can be found in the image attached.

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Answer: It's A) [tex]y=-x^2[/tex]

Step-by-step explanation:

Just took the test and it's 100% correct, just trust me ✔️

The rolls are not independent of each other, which is a requirement for using a Bernoulli trial model.

The reason is that a Bernoulli trial is a random experiment with only two possible outcomes, such as success or failure, heads or tails, etc. In this game, there are more than two possible outcomes on each roll of the dice. Specifically, the player can roll any number from 1 to 6, and the outcome of each roll can affect the outcome of the subsequent rolls.

Furthermore, the probability of getting at least three 2's in seven rolls of a fair dice is not constant for each roll, as it depends on the previous outcomes. Therefore, the rolls are not independent of each other, which is a requirement for using a Bernoulli trial model.

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Given the data set of the number of miles that Monica walked each day, the summary is :

First sort the numbers into ascending order:

3. 2, 3. 8, 4. 1, 4. 2, 4. 7, 5, 5. 8

Min is smallest value in the data set.

Min = 3.2

Max is the largest value in the data set.

Max = 5.8

The median is the middle number which we can see to be 4. 2 .

The Q1 is the first quartile which would be:

lower half is 3.2, 3.8, and 4.1 = 3 . 8

The Q3 is the third quartile and would be the upper half is 4.7, 5, and 5.8. Q3 = 5

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If Bill took 2 hours to bike around a lake, then it would take Bill 5 hours to walk-around the lake at a speed of 4 miles per hour.

The "Speed" is defined as a "scalar-quantity" that refers to the rate at which an object changes its position with respect to time.

Let the distance around lake be = "d" miles.

We know that,

⇒ Time-taken to bike around lake is = 2 hours,

⇒ Speed while biking = 10 mph,

We use formula ⇒ Distance = (Speed) × (Time),

Substituting the values,

We get,

⇒ d = 10 × 2,

⇒ d = 20 miles,

Now, Speed while walking = 4 miles per hour,

So, Time taken to walk around the lake = (Distance)/(Speed),

⇒ Time taken to walk around lake = 20/4,

⇒ Time taken to walk around lake = 5 hours,

Therefore, the required time is 5 hours.

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The probability that X has a value less than 2.1 is 0.2 or 20%.

The probability that the random variable X has a value less than 2.1 can be found by calculating the area under the probability density function (PDF) of X from 0.1 to 2.1. Since X is a uniform random variable over the interval [0.1, 5], its PDF is a straight line with a slope of 1/(5-0.1) = 0.2 and a height of 1/(5-0.1) = 0.2 over the interval [0.1, 5].

Therefore, the probability that X has a value less than 2.1 is the area of the triangle formed by the points (0.1, 0), (2.1, 0), and (2.1, 0.2), which is given by:

(1/2) × base × height = (1/2) × (2.1 - 0.1) × 0.2 = 0.2

So the probability that X has a value less than 2.1 is 0.2 or 20%.

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Answer:

Step-by-step explanation:

If Angelique is n years old, then Jamila's age can be expressed as:

Jamila's age = 2(Angelique's age + 1)

Substituting n for Angelique's age, we get:

Jamila's age = 2(n + 1)

Therefore, an expression in terms of n for Jamila's age is 2(n + 1)

If width of a rectangle is 4 meters less than its length which have an area of 140 square meters, then the length of rectangle is 14 meter.

The "Area" is defined as a mathematical measure of the amount of space enclosed by a two-dimensional shape, such as a rectangle, triangle, circle, or any other polygon.

Let the length of rectangle be "L" meters and

Let width be "W" meters.

We know that, width is 4 meter shorter than length,

So, Width = Length - 4 meters

Area = 140 square meters

The formula to find area of rectangle is : Area = (Length)×(Width),

Substituting the length and breadth,

We get,

⇒ 140 = L×(L - 4),

⇒ 140 = L² - 4L,

⇒ L² - 4L - 140 = 0,

⇒ (L + 10)(L - 14) = 0,

⇒ L + 10 = 0 or L - 14 = 0,

⇒ L = -10 or L = 14,

Since length cannot be negative, we discard the solution L = -10.

Therefore, the length is 14 meters.

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The probability that a randomly selected observation exceeds 43 is 0.7.

Since x is a uniform random variable over the interval [40, 50], we know that the probability density function is constant over this interval. That means that any sub-interval of [40, 50] has the same probability of being selected.

To find the probability that a randomly selected observation exceeds 43, we need to find the area under the probability density function from 43 to 50. This area represents the probability that x is greater than 43.

To do this, we can calculate the total area under the probability density function from 40 to 50, and then subtract the area from 40 to 43. The total area is simply the length of the interval, which is 50 - 40 = 10. Since the probability density function is constant over the interval, its value is 1/10 for any sub-interval.

So, the area from 40 to 43 is (43 - 40) * (1/10) = 3/10, and the area from 43 to 50 is (50 - 43) * (1/10) = 7/10. Therefore, the probability that a randomly selected observation exceeds 43 is 7/10, or 0.7.

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d. Smaller than 0.01

Explanation: To determine if managers from Country B are more motivated than managers from Country A, we need to conduct a hypothesis test.

Null Hypothesis (H0): Managers from Country B are not more motivated than managers from Country A.
Alternative Hypothesis (Ha): Managers from Country B are more motivated than managers from Country A.
We can conduct a two-sample t-test to compare the means of the two samples.
t = (79.83 - 65.75) / sqrt((6.41^2 / 100) + (11.07^2 / 211)) = 6.70
The degrees of freedom is (100 - 1) + (211 - 1) = 309.
Using a t-distribution table, we find the p-value to be smaller than 0.01. Therefore, we reject the null hypothesis and conclude that managers from Country B are more motivated than managers from Country A.

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