giving brainliest for correct answer ! not a hard problem .

The length of  the outside arc of each piece compared to the inside arc is 5.57 inches

Length of outer track = sum of length of 10 pieces = circumference of the outer circle

if R is the Radius of outer circle then...

Circumference of the outer track = 2pi*R

Similarly the circumference of the inner track (with radius r) = 2pi*r

length of each outer piece is 3.5 inch more than length of inner piece

So total outer length is 10*3.5 =35 inches more than the inner length.

=> Outer Circumference - Inner Circumference = 35 inches

=> 2pi*R - 2pi*r = 35

=> 2pi(R -r) = 35

=> R-r = 35/2pi = 5.57 inches

=> R-r = Width of the track = 5.57 inches

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For part (a), we can use Cauchy's Integral Formula which states that for a function f(z) that is analytic inside and on a simple closed contour C, and a point a inside C, we have:   The value of the integral is 2πi i0^(m+1).


f^(m)(a) = (1/2πi) ∮ C f(z)/(z-a)^(m+1) dz

where f^(m)(a) denotes the m-th derivative of f evaluated at a, and the integral is taken counterclockwise around C.

In our case, we have f(z) = 1, which is analytic everywhere, and C is the circle {izl = r} with counterclockwise orientation. So we can write:

iizml dz = i(1/2πi) ∮ {izl = r} 1/(z-i0) dz

where i0 is any point inside the circle, and the integral is taken counterclockwise around the circle.

Using Cauchy's Integral Formula with a = i0 and m = 0, we get:

iizml dz = i

So the value of the integral is just i.

For part (b), we need to evaluate the derivative of the integral, which is:

d/dz (iizml) = -m iizm-1

Using Cauchy's Integral Formula with a = i0 and m = 1, we get:

iizmlldzl = i(-m) (1/2πi) ∮ {izl = r} z^(m-1)/(z-i0)^2 dz

Note that the only difference from part (a) is the z^(m-1) term in the integral. We can simplify this using the Residue Theorem, which states that for a function f(z) that has a pole of order k at z = a, we have:

Res[f(z), a] = (1/(k-1)!) lim[z->a] d^(k-1)/dz^(k-1) [(z-a)^k f(z)]

In our case, the integral has a simple pole at z = i0, so we have:

Res[z^(m-1)/(z-i0)^2, i0] = lim[z->i0] d/dz [(z-i0)^2 z^(m-1)] = i0^m

Therefore, we can write:

iizmlldzl = -2πi Res[z^(m-1)/(z-i0)^2, i0] = -2πi i0^m

Note that the minus sign comes from the fact that the residue is negative. So the value of the integral is -2πi i0^m.

For part (c), we need to evaluate the integral of z^m around the same circle. Again, we can use Cauchy's Integral Formula with a = i0 and m = -1, which gives:

izm dz = (1/2πi) ∮ {izl = r} z^(m+1)/(z-i0) dz

Using the Residue Theorem, we can find the residue at z = i0, which is:

Res[z^(m+1)/(z-i0), i0] = lim[z->i0] z^(m+1) = i0^(m+1)

Therefore, we can write:

izm dz = 2πi Res[z^(m+1)/(z-i0), i0] = 2πi i0^(m+1).

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The length of the microorganism that measure 5μm is equivalent to 0.005 mm

It is the transformation of a value expressed in one unit of measurement into an equivalent value expressed in another unit of measurement of the same nature.

To solve this problem the we have to convert the units with the given information.

1mm is equal to 1000 μm

5μm * (1 mm/1000μm) = (5*1) / 1000 = 5/1000 = 0.005 mm = 5x10^-3 mm

The length of the microorganism that measure 5μm is equivalent to 0.005 mm

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Answer:

In mathematics, a function is a binary relation between two sets that associates every element of the first set to exactly one element of the second set. Typical examples are functions from integers to integers, or from the real numbers to real numbers.

Step-by-step explanation:

The value of Standard Deviation is needed to calculate the minimum sample size accurately. If you have the value of Standard Deviation, you can substitute it into the equation to find the minimum sample size.

To determine the minimum number of CEOs that the journalist must survey to be within $50,000 of the true average annual salary, we need to consider the margin of error in the confidence interval.

The margin of error is determined by the z-value associated with the desired confidence level and the standard deviation of the population.

Given that the z-value associated with a 95% confidence interval is 1.96, we can use the following formula to calculate the margin of error:

Margin of Error = z-value * (Standard Deviation / sqrt(sample size))

To be within $50,000 of the true average annual salary, we can set up the equation:

$50,000 = 1.96 * (Standard Deviation / sqrt(sample size))

Solving for the sample size (number of CEOs):

sqrt(sample size) = (1.96 * Standard Deviation) / $50,000

sample size = (($50,000)^2 * (Standard Deviation)^2) / (1.96)^2

The value of Standard Deviation is needed to calculate the minimum sample size accurately. If you have the value of Standard Deviation, you can substitute it into the equation to find the minimum sample size.

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Hello!

\(\large\boxed{\text{Infinite discontinuity at x = 2}}\)

\(f(x) = \frac{x^{2} - 4x - 12}{x - 2}\)

Recall that in a rational function, the denominator contains the vertical asymptote (an infinite discontinuity).

If terms can be canceled from the denominator and the numerator, then the function contains a hole. We can check whether this function contains such by factoring:

\(f(x) = \frac{(x - 6)(x + 2)}{x - 2}\)

There is no common factor, so the function only contains a discontinuity at its vertical asymptote.

Find the vertical asymptote by setting the denominator equal to 0:

x - 2 = 0

x = 2.

Answer:

140x2−252

Step-by-step explanation:

Answer:

TV = 9.71

Step-by-step explanation:

sin 47° = TV/13.28

0.7314 = TV/13.28

TV = 9.71

Answer:

Can you please provide more information about the rectangle? Do you have a graph or some points?

Answer:c

Step-by-step explanation:

A bell-shaped histogram is a type of graph that displays a normal distribution, which is a probability distribution that is symmetrical and has a characteristic bell shape.

The bell-shaped histogram is created by plotting the data on a horizontal axis and the frequency or probability on a vertical axis. The data points are grouped into intervals called bins, and the number of data points that fall into each bin is plotted as a bar. The bars are typically drawn adjacent to one another and connected with lines to create a continuous curve that represents the normal distribution.

The resulting histogram will have a characteristic bell shape, with a high point at the mean, and decreasing frequency or probability as the values move away from the mean in either direction. The width of the curve is determined by the standard deviation of the data, with wider curves indicating greater variation in the data.

The bell-shaped histogram is commonly used in statistical analysis to represent normally distributed data, such as the heights or weights of a population, test scores, or other measurements that tend to cluster around a central value with a predictable range of variation.

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Answer:

150 degrees

Step-by-step explanation:

The sum of all angles in a pentagon is 540 degrees. So you add the measurements of the 4 you know - 95 + 95 + 100 + 100 = 390. Then you subtract 540 - 390 - 150 degrees for the last angle.

jehejejdjdjjdjdkjfjf

Total sales = $450*40= $18000

Commision = 18000*0.025 = $450

--------------------------------------------------------------------------------------

Total earnings = 30000 + commision

comission = 4*175000*0.13 = 91000

Total earnings = 30000+91000 = $121000

(a) The Laplace Transform of f(t) = te^(at) is defined as:

Lf(t) = ∫₀^∞ f(t) e^(-st) dt

Substituting f(t) into this formula, we get:

Lf(t) = ∫₀^∞ te^(at) e^(-st) dt

= ∫₀^∞ t e^((a-s)t) dt

We can integrate this expression by parts, using u = t and dv = e^((a-s)t) dt. Then du = dt and v = (1/(a-s)) e^((a-s)t).

The integral becomes:

Lf(t) = [t (1/(a-s)) e^((a-s)t)] ∣₀^∞ - ∫₀^∞ (1/(a-s)) e^((a-s)t) dt

Since e^((a-s)t) goes to 0 as t goes to infinity, the first term evaluates to 0. The second term is an integral we can easily evaluate:

Lf(t) = [-1/(a-s)] [e^((a-s)t)] ∣₀^∞

= [1/(s-a)]

Therefore, the Laplace Transform of f(t) = te^(at) is:

Lf(t) = [1/(s-a)]

(b) Let f(t) = t cosh(at) for t > 0. Using the identity cosh(at) = (1/2) (e^(at) + e^(-at)), we can express f(t) as:

f(t) = (t/2) (e^(at) + e^(-at))

Using linearity and the result from part (a), the Laplace Transform of f(t) is:

Lf(t) = (1/2) Lt e^(at) + (1/2) Lt e^(-at)

= (1/2) [1/(s-a)^2] + (1/2) [1/(s+a)^2]

= [(s^2 + a^2)/(2s^2 - 2as + 2a^2)]

Therefore, the Laplace Transform of f(t) = t cosh(at) is:

Lf(t) = [(s^2 + a^2)/(2s^2 - 2as + 2a^2)]

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a. When the population standard deviation σ = 15, the population mean μ is approximately 168.2

b. When the population standard deviation σ = 25, the population mean μ is approximately 182

c. When the population mean μ = 136, the population standard deviation σ is approximately 10.94

d. When the population mean μ = 128, the population standard deviation σ is approximately 17.19

To solve this problem, convert the given probability to a z-score and using the z-score formula to solve for the unknown variable.

Given P(X > 150) = 0.10 and σ = 15,

z = (150 - μ) / σ = (150 - μ) / 15

Using a standard normal distribution table, the z-score corresponding to a probability of 0.10 is approximately -1.28.

Thus,

-1.28 = (150 - μ) / 15

Solving for μ,

μ = 150 - (-1.28) * 15 = 168.2

population mean μ is approximately 168.2 when the population standard deviation σ = 15.

Similarly,

z-score corresponding to P(X > 150) = 0.10 when σ = 25 as:

z = (150 - μ) / σ = (150 - μ) / 25

Using a standard normal distribution table, the z-score corresponding to a probability of 0.10 is approximately -1.28.

Thus,

-1.28 = (150 - μ) / 25

Solving for μ, we get:

μ = 150 - (-1.28) * 25 = 182

Therefore, the population mean μ is approximately 182 when the population standard deviation σ = 25.

Also,

Given μ = 136 and using the z-score formula

z = (150 - 136) / σ = 14 / σ

Using a standard normal distribution table, the z-score corresponding to a probability of 0.10 is approximately 1.28.

Thus,

1.28 = 14 / σ

Solving for σ, we get:

σ = 14 / 1.28 = 10.94

Therefore, the population standard deviation σ is approximately 10.94 when the population mean μ = 136.

Lastly,

Given μ = 128 and using the z-score formula,

z = (150 - 128) / σ = 22 / σ

Using a standard normal distribution table, the z-score corresponding to a probability of 0.10 is approximately 1.28.

Thus,

1.28 = 22 / σ

Solving for σ, we get:

σ = 22 / 1.28 = 17.19

Therefore, the population standard deviation σ is approximately 17.19 when the population mean μ = 128.

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Answer:

Step-by-step explanation:

-19x-11= -125 add 11 to both sides

-19x= -114   divide by -19

x= 6

Answer:

.067meters from the claculator

1. C

2. A

3.B

4.D

Step-by-step explanation:

A,B,C,D are the possible answers in order. 1,2,3,4 are the questions in order. 1. n is greater than or equal to 4 means that n's value is larger than 4 or 4. so it would be greater than with a line underneath. 2. n is less then 4. this means n's value is any real number less than 4. so it would be n is less than 4. n is less than or equal to 4 means that it can be any real number less than 4 or 4 itself, so it would be n is less than 4 with a line underneath. process of elimination leaves just 1 answer for 4

The given equation of the line is:

It is required to find the x-intercept and the y-intercept.

To find the x-intercept, substitute y=0 into the equation and find x:

Hence, the x-intercept is -4.

To find the y-intercept, substitute x=0 into the equation and find y:

The y-intercept is -7.

Answers:

x-intercept: -4

y-intercepe: -7

The expected value of perfect information (EVPI) is a concept used in decision theory and health economics. It is the price that would be paid to gain access to perfect information, and it is a measure of the cost of uncertainty in decision making. The formula for EVPI is defined as the difference between the predicted payoff under certainty and the predicted monetary value.

The expected value of perfect information (EVPI) is a measure of the cost of uncertainty in decision making, and it is defined as the difference between the predicted payoff under certainty and the predicted monetary value. The formula for EVPI is:

EVPI = E(max) - E(act) where: E(max) is the expected maximum payoff under certainty, E(act) is the expected payoff with actual information.

The expected maximum payoff under certainty is the expected value of the best possible outcome that could be achieved if all information was known. The expected payoff with actual information is the expected value of the outcome that would be achieved with the available information. The difference between these two values is the cost of uncertainty, and it represents the price that would be paid to gain access to perfect information.

The formula for EVPI is defined as the difference between the predicted payoff under certainty and the predicted monetary value.

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Answer:

x = \(\frac{83}{36}\)

Step-by-step explanation:

Given

x - 2 \(\frac{1}{4}\) = \(\frac{1}{18}\) ( change mixed number to improper fraction )

x - \(\frac{9}{4}\) = \(\frac{1}{18}\)

Multiply through by 36 ( the LCM of 4 and 18 ) to clear the fractions

36x - 81 = 2 ( add 81 to both sides )

36x = 83 ( divide both sides by 36 )

x = \(\frac{83}{36}\)

The distance would change by 62.85

If the radius of the small gear is 1.5 inches and the radius of the large gear is 4.5 inches, we have;

Number of rotation of the small gear for each rotation of the large gear = 3 rotations

We have the number of rotation of the wheel = 3

Then we have to solve for distance

= 3 × 2 × π × 10 inches = 60*π inches

The difference in distance = 60*π inches - 40*π inches =

20·π inches

= 20 x 22/7

= 62.85

The distance traveled by the bicycle increases by   62.85 inches

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Answer:

1. $539

2. $300

3. C

Step-by-step explanation:

May I have brainliest?

Answer:

The answer is A) –$25

Step-by-step explanation:

she lost 25 dollars. hope this helps.

Answer:

They would have built 84 cars

Step-by-step explanation:

From the question, they have already built 9 cars

Now, the hourly production rate is 15 cars per hour;

So therefore, in 5 hours, total that would have been built excluding the initial 9 will be;

15 * 5 = 75 cars

Now, let us add the initial 9

we have this as 9 + 75 = 84 cars

The magnitude of the sum is approximately 5.66.

We can use the law of cosines to find the magnitude of the sum. Let S be the sum vector, then:

|S|^2 = |2u|^2 + |4v|^2 + 2|2u||4v|cos(30°)

Since u and v are unit vectors, this simplifies to:

|S|^2 = 4 + 16 + 16(cos(30°)) = 32

Taking the square root of both sides:

|S| = sqrt(32) ≈ 5.66

Rounding to 2 decimal places, the magnitude of the sum is approximately 5.66.

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Answer:

A. -4

Step-by-step explanation:

For solving for x intercepts analytically. You can set the the y in the equation to 0. So, 2x-3(0)=12, and solving for x will get you -4.

You can also solve graphically by plugging in the equation and looking at where it intercepts the x axis.

Answer:

It looks like the Bears have the higher wins, as they won 40 games while the Bulls won only 32 games.