What is 29 multiplied by 84

Using the concept of proportion, Gianna will have enough yards to make 18 bows

To solve this problem, we need to apply the concept of proportions.

In order to make 1 bow, she needs 1/5 yard of ribbon

Representing this in an equation form will be;

1 bow = 1/5 yard

18 bow = x yard

cross multiply both sides and solve for x

x * 1 = 18 * (1/5)

x = 3.6 yards

From the above, there will be enough yards to make 18 bows.

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Given the number 64,473

From the right:

• Unit digit = 3

• Tens digit = 7

• Hundred digit = 4

• Thousand digit =4

• Ten thousand digit =6

To round 64,473 to the nearest thousand, we first identify the thousand digit.

Thousand digit = 4

Next, identify the number after the thousand digit.

The number after the thousand digit = 4

When rounding numbers:

• If the number after the required number place is (0,1,2,3,4), we simply write the number.

• If the number after the required number place is (5,6,7,8,9), we round up.

Since the number after the thousand digit is 4. we therefore have that:

64,473 rounded to the nearest thousand = 64,000

Answer:

4/7 greater

Step-by-step explanation:

5/7-1/7=4/7

Answer:

a

Step-by-step explanation:

it sows that for every 1.35n the N represents the amount ordered

The probability that the sample mean nicotine content is less than 0.77 is approximately 0.0003.

The probability that the sample mean nicotine content will be less than 0.79 can be found by using the Central Limit Theorem. The Central Limit Theorem states that the distribution of the sample means approaches a normal distribution as the sample size increases. Since the sample size is 100, we can assume that the sample means nicotine content is approximately normally distributed.

The mean of the sample means nicotine content is equal to the population means, which is 0.8 mg. The standard deviation of the sample means nicotine content is equal to the population standard deviation divided by the square root of the sample size. So, the standard deviation of the sample means nicotine content is 0.1 mg/sqrt (100) = 0.01 mg.

Using these values, we can find the probability that the sample mean nicotine content is less than 0.79 by using the standard normal distribution table or calculator.

z = (0.79 - 0.8) / 0.01 = -1

Using a standard normal table or calculator, P(z < -1) = 0.1587.

So, the probability that the sample mean nicotine content is less than 0.79 is approximately 0.1587.

Similarly, for the sample mean nicotine content less than 0.77

z = (0.77 - 0.8) / 0.01 = -3

P(z < -3) = 0.0003

So, the probability that the sample mean nicotine content is less than 0.77 is approximately 0.0003

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The coefficients are calculated by taking the derivatives of sin(x) at b = 0, which is the base point. The 3rd order Taylor polynomial is the 0th, 1st and 2nd derivatives, the 4th order Taylor polynomial is the 0th, 1st, 2nd and 3rd derivatives, and so on.

T3(x) = sin(x) - x^3/6

T4(x) = sin(x) - x^3/6 + x^5/120

T5(x) = sin(x) - x^3/6 + x^5/120 - x^7/5040

T6(x) = sin(x) - x^3/6 + x^5/120 - x^7/5040 + x^9/362880

We will use the formula for the Taylor polynomial of degree n:

Tn(x) = f(b) + f'(b)(x-b) + f''(b)(x-b)^2/2! + f'''(b)(x-b)^3/3! + ...+ f^(n)(b)(x-b)^n/n!

Since b = 0, we have:

T3(x) = sin(0) + sin'(0)(x-0) + sin''(0)(x-0)^2/2!

     = 0 + 1(x-0) + (-1)(x-0)^2/2!

     = 0 + x - x^3/6

     = sin(x) - x^3/6

T4(x) = sin(0) + sin'(0)(x-0) + sin''(0)(x-0)^2/2! + sin'''(0)(x-0)^3/3!

     = 0 + 1(x-0) + (-1)(x-0)^2/2! + (-1)(x-0)^3/3!

     = 0 + x - x^3/6 + x^5/120

     = sin(x) - x^3/6 + x^5/120

T5(x) = sin(x) - x^3/6 + x^5/120 - x^7/5040

     = 0 + 1(x-0) + (-1)(x-0)^2/2! + (-1)(x-0)^3/3! + 1(x-0)^4/4!

     = 0 + x - x^3/6 + x^5/120 - x^7/5040

     = sin(x) - x^3/6 + x^5/120 - x^7/5040

T6(x) = sin(x) - x^3/6 + x^5/120 - x^7/5040 + x^9/362880

     = 0 + 1(x-0) + (-1)(x-0)^2/2! + (-1)(x-0)^3/3! + 1(x-0)^4/4! + (-1)(x-0)^5/5!

     = 0 + x - x^3/6 + x^5/120 - x^7/5040 + x^9/362880

     = sin(x) - x^3/6 + x^5/120 - x^7/5040 + x^9/362880

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To prove that AC ⊕ EC, we need to show that quadrilateral DEFG being a rectangle and BC ⊕ DC implies that AC ⊕ EC.

To begin, we know that quadrilateral DEFG is a rectangle. In a rectangle, opposite sides are equal in length and parallel to each other.

Given that BC ⊕ DC, we can infer that BC and DC are not equal in length.

Since DEFG is a rectangle, this means that AB and DE are also not equal in length, as they are opposite sides. Similarly, AD and BC are not equal in length.

Now, let's consider triangle ABC. In a triangle, the sum of the lengths of any two sides must be greater than the length of the third side. Applying this to triangle ABC, we have:

AB + BC > AC
AD + DC > AC

Since AB and DC are not equal in length, and BC and AD are not equal in length, we can conclude that AC is the longest side in triangle ABC.

Now, let's look at triangle CDE. Again, using the same rule for triangles:

AC + CE > EC
AD + DE > EC

Since AC is the longest side in triangle ABC, and AD is not equal in length to DE, we can conclude that AC is longer than EC.

Therefore, we have proved that if quadrilateral DEFG is a rectangle and BC ⊕ DC, then AC ⊕ EC.

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The area under the curve of f(x) = x^2 on the interval (0, 3] using right endpoints and rectangles.

a. Using 4 rectangles:
Step 1: Divide the interval (0, 3] into 4 equal subintervals: Δx = (3-0)/4 = 0.75. So, the subintervals are [0, 0.75], [0.75, 1.5], [1.5, 2.25], and [2.25, 3].
Step 2: For each subinterval, use the right endpoint to calculate the height of the rectangle. Then, multiply it by the width (Δx) to find the area of each rectangle.
Step 3: Sum the areas of all rectangles to estimate the total area under the curve.

b. Using 6 rectangles:
Step 1: Divide the interval (0, 3] into 6 equal subintervals: Δx = (3-0)/6 = 0.5. So, the subintervals are [0, 0.5], [0.5, 1], [1, 1.5], [1.5, 2], [2, 2.5], and [2.5, 3].
Step 2: Repeat the process from Step 2 of part a, using the right endpoints of each subinterval to calculate the height and area of the rectangles.
Step 3: Sum the areas of all rectangles to estimate the total area under the curve.

c. The more accurate estimate is the one using 6 rectangles. The reason is that as the number of rectangles increases, the approximation becomes more precise. This is because smaller rectangles can better fit the curve, resulting in less discrepancy between the rectangles' combined area and the actual area under the curve. In this case, using 6 rectangles provides a closer estimate to the true area than using 4 rectangles.

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An expression approximating the CDF of Vn(-p) can be given by F(c) ≈ Φ(-c), where Φ denotes the standard normal CDF.

Let X be the standardized sample mean, i.e., X = Vn(Y-p)/√(VP(1-p)), where Y1,...,Yn are independent and identically distributed as Bernoulli(p). Then, X ~ N(0,1) by the Central Limit Theorem (CLT).

Now, we want to approximate the CDF of Vn(-p), i.e., we want to find P(X ≤ -c), where c = Vn(-p).

Using the standardization formula, we have X = (Vn(Y-p) - Vn(-p))/√(VP(1-p)), and thus, we can rewrite the probability as:

P(X ≤ -c) = P(Vn(Y-p) - Vn(-p) ≤ -c√(VP(1-p)))

Using Chebyshev's inequality, we get:

P(|Vn(Y-p) - Vn(-p)| ≥ c√(VP(1-p))) ≤ VP(1-p)/(c^2n)

Since Y1,...,Yn are Bernoulli(p), we have VP(1-p) = p(1-p), and thus, we can write:

P(|Vn(Y-p) - Vn(-p)| ≥ c√(p(1-p))) ≤ p(1-p)/(c^2n)

By the union bound, we get:

P(|Vn(Y-p) - Vn(-p)| ≥ c√(p(1-p))) ≤ 2exp(-2nc^2/p(1-p))

Now, we can use the fact that for any ε > 0, there exists a constant K such that P(|X| > K) < ε, and choose ε = 2exp(-2nc^2/p(1-p)) to get:

P(Vn(Y-p) ≤ Vn(-p) - c√(p(1-p))) ≤ ε

Therefore, we can approximate the CDF of Vn(-p) as F(c) ≈ Φ(-c), where Φ denotes the standard normal CDF.

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Answer:

x>4y−5

Step-by-step explanation:

Answer:

54.65

Step-by-step explanation:

Answer: 85

Yupyupyupypu

The doping concentration at a position of 2 microns inside the emitter after 25 minutes is 1.36*10^22 cm^-3.

To calculate the doping concentration at a position of 2 microns inside the emitter after 25 minutes, we need to consider the diffusion process of dopant atoms.

Diffusion can be described by Fick's second law, which relates the rate of change of dopant concentration to the diffusion coefficient and the distance traveled.

In this case, we can assume a constant diffusion coefficient and a uniform dopant distribution in the emitter region. Therefore, we can use the equation C(x, t) = C0*erfc(x/(2*sqrt(D*t))),

where C0 is the initial doping concentration, erfc is the complementary error function, D is the diffusion coefficient, x is the distance traveled, and t is the time. Plugging in the values given, we get C(2 microns, 25 min) = 1.36*10^22 cm^-3, which is option (i).

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Answer:

Step-by-step explanation:

Due to the cast of the shadow regardless of that the line will still be 11 feet due to the lines length

If the coordinates of A be (2,3) coordinates of B be (2,-2) , coordinates of C be (-1,-4) coordinates of \(A^{I}\) be (-3,6) coordinates of \(B^{I}\) be (-3,1) and coordinates of \(C^{I}\) be (-6,-1) then the correct translation be

(x-5,y+3).

Given a figure in which the coordinates of A be (2,3) coordinates of B be (2,-2) , coordinates of C be (-1,-4) coordinates of \(A^{I}\) be (-3,6) coordinates of \(B^{I}\) be (-3,1) and coordinates of \(C^{I}\) be (-6,-1).

We are required to find the correct translation of figure from ABC to \(A^{I} B^{I} C^{I}\).

Translation is basically the displacement of a figure or a shape from one place to another.

To reach the coordinates of A to \(A^{I}\), we need to subtract 5 from 2  and add 3 to 3.

To reach the coordinates of B to \(B^{I}\), we need to subtract 5 from 2  and add 3 to -2.

To reach the coordinates of C to \(C^{I}\), we need to subtract 5 from -1  and add 3 to -4.

Hence if the coordinates of A be (2,3) coordinates of B be (2,-2) , coordinates of C be (-1,-4) coordinates of \(A^{I}\) be (-3,6) coordinates of \(B^{I}\) be (-3,1) and coordinates of \(C^{I}\) be (-6,-1) then the correct translation be

(x-5,y+3).

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Answer:

3

Step-by-step explanation:

Answer:

3

Step-by-step explanation:

Sierra would travel approximately 316 feet in five revolutions.

We know that a revolution is equal to the circumference of a circle with a radius of 10 feet. The formula for circumference is:circumference = 2πr, where r is the radius of the circle.Using this formula, we can calculate the circumference of the carousel:circumference = 2π(10)circumference = 20πSo, one revolution of the carousel covers a distance of 20π feet.

In five revolutions, Sierra would travel a distance of:distance = 5(20π)distance = 100π feet.Now, we need to take into account that Sierra is located 1.5 feet from the edge of the car.

This means that the total distance she would travel is 100π + 1.5 x 2 x 5 = 100π + 15 feet, or approximately 315.7 feet.Rounding this off to the nearest whole number, Sierra would travel approximately 316 feet in five revolutions.

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Answer:

28 units

Step-by-step explanation:

Since the perimeter of both triangles is same,

the sum of all sides of first triangle = sum of all sides of second triangle

or, 6x + 3 + 2x + 4x = 5x + 5x + 3x + 2

or, 12x + 4 = 13x + 2

or, 4-2 = 13x - 12x

or, 2 = x

Now,

Putting the value of x in the perimeter of first triangle,

12x + 4= 12* 2+ 4

= 28 units

The value of the test statistic is 6.51.

The test statistic for this problem can be calculated using the formula:

z = (p - P) / √(P * (1 - P) / n)

Where p is the sample proportion (0.67 in this case), P is the hypothesized population proportion (we don't know this value, so we assume it to be 0.5 for a two-tailed test), n is the sample size (380), and z is the standard normal distribution value corresponding to the level of significance.

Plugging in the values, we get:

z = (0.67 - 0.5) / √(0.5 * (1 - 0.5) / 380) = 6.51

So the value of the test statistic is 6.51.

The test statistic is a measure of how far the sample proportion deviates from the hypothesized population proportion under the null hypothesis. In this case, we assume that the population proportion is 0.5 (since we have no reason to believe otherwise), and we calculate the probability of observing a sample proportion of 0.67 or greater assuming this null hypothesis is true.

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Step-by-step explanation:

Hindi ko poh alam ✌️

c = (185.6 * sin(C)) / sin(43.1°) calculate the value of c using the previously calculated value of C.

To solve triangle ABC with the given information, we have:

ZA = 43.1° (angle A)

a = 185.6 (side opposite angle A)

b = 244 (side opposite angle B)

To solve the triangle, we can use the Law of Sines and the fact that the sum of the angles in a triangle is 180 degrees.

Use the Law of Sines to find angle B:

sin(B) / b = sin(A) / a

sin(B) / 244 = sin(43.1°) / 185.6

Cross-multiplying and solving for sin(B):

sin(B) = (244 * sin(43.1°)) / 185.6

Taking the inverse sine of both sides to find angle B:

B = arcsin((244 * sin(43.1°)) / 185.6)

Calculate the value of B using the given numbers.

Find angle C:

Since the sum of the angles in a triangle is 180 degrees, we can find angle C by subtracting angles A and B from 180 degrees:

C = 180° - A - B

Find side c:

To find side c, we can use the Law of Sines again:

sin(C) / c = sin(A) / a

sin(C) / c = sin(43.1°) / 185.6

Cross-multiplying and solving for c:

c = (185.6 * sin(C)) / sin(43.1°)

Calculate the value of c using the previously calculated value of C.

Now, you can use the calculated values of angles B and C and the side c to fully solve triangle ABC.

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Answer:

y=-1x+8

Step-by-step explanation:

-1 because the line is going down, and it's one down one to the right, one down one to the right, the whole way down.

+8 because that's where the line hits the line going up and down, that's the y-intercept.

Answer: 30 gallons

Step-by-step explanation:

First translate 2 hours into 120 minutes.  Then multiply 120 * 4 = 480.  Then divide 480/16 = 30

The standard deviation is relatively small when the data are all concentrated close to the mean, exhibiting little variation or spread.

The standard deviation could be a degree of the changeability or spread of a set of information. It is calculated by finding the square root of the normal of the squared contrasts between each information point and the cruel(mean).

In other words, it tells us how much the information values are scattered around the mean.

When the information is all concentrated near the cruel(mean), it implies that the contrasts between each information point and the cruel are moderately little.

This comes about in a little while of squared contrasts, which in turn leads to a little standard deviation. On the other hand, when the information is more spread out, it implies that the contrasts between each information point and the cruel are bigger.

This comes about in a bigger entirety of squared contrasts, which in turn leads to a bigger standard deviation.

For case, let's consider two sets of information:

Set A and Set B.

Set A:

2, 3, 4, 5, 6

Set B:

1, 3, 5, 7, 9

Both sets have the same cruel(mean) (4.0), but Set A encompasses a littler standard deviation (1.4) than Set B (2.8).

This is because the information values in Set A are all moderately near to the cruel(mean), while the information values in Set B are more spread out.

Subsequently, we will say that the standard deviation is generally small when the information is all concentrated near the mean, showing a small variety or spread.

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The given statement that 'the standard deviation is used in conjunction with the mean to numerically describe distributions that are bell shaped' is true.

The standard deviation is a measure of the spread of a distribution, and is used in conjunction with the mean to describe bell-shaped distributions. The standard deviation is a measure of how much the data values are spread out from the mean. It is used to determine the range of values within which a certain percentage of data points can be expected to fall.

The standard deviation is calculated by taking the square root of the variance, which is the average of the squared differences of the data points from the mean. The standard deviation gives an indication of how spread out the data is around the mean. A small standard deviation indicates that the data is clustered closely around the mean, while a large standard deviation indicates that the data is more spread out. For a bell shaped distribution, 68% of the data will fall within one standard deviation of the mean.

Note: The question is incomplete. The complete question probably is: The standard deviation is used in conjunction with the MEAN to numerically describe distributions that are bell shaped. True or False.

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Answer:

h= 13.6 ft

Step-by-step explanation:

Let,

a= 8 ft

b= 11 ft

The ladder against the top of the house is creating a right triangle

So, we can find the length of the ladder using

\(h^{2} = {a}^{2} + {b}^{2} \\ h^{2} = {8}^{2} + {11}^{2} \\ h^{2} = 64 + 121 \\ h = \sqrt{185} \\ = 13.6ft\)

Therefore, the length of the ladder (h) = 13.6 ft ( rounded to the nearest tenth)

The range of values for which the provided function is defined is known as the domain. The domain of the given relation is (0,∞).

A set of values for which a specific function is defined is known as a domain. The entire collection of values that a particular function may return is known as a range. Suppose that up to 20 ounces of weight are included in the post office's $2 flat rate for parcels weighing less than 5 ounces. Every every ounce after that is $0.15. Mail weight is, thus, the independent variable in this connection. because the weight of the mail can exceed 0. As a result, (0,∞) is the relation's domain.

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the answer is 3/5

if that's not right I apologize

Answer:

3/5

Step-by-step explanation:

When dividing fractions, you change the division sign to multiplication and also flip the fraction that you are multiplying with.

So: 2/4 would become 4/2

3/10 x 4/2

12/20

Highest common factor between 12 and 20 is 4.

Divide both sided by 4:

3/5

Answer:

x + 7 ft and  x + 15 ft as the dimensions of the outside border of the walkway.

Step-by-step explanation:

\(x^{2} +12x + 20 = (x + 2)(x + 10)\)

The dimensions of the fountain is x + 2 and x + 10

Adding the 5-ft walkway, we get x + 7 ft and  x + 15 ft as the dimensions of the outside border of the walkway.