advance pile up trigonometry

It is advised that lower pressure test should be administered.

Probability of survival of pressure vessel the pressure vessel is tested under the lower pressure test at 58 bar, the probability of survival is given by the sum of the probability of survival if the vessel is one of the 60% that will survive 70 bar and the probability of survival if the vessel is one of the 40% that will fail at 70 bar but will survive 58 bar or less. If P1 represents the probability of survival of the vessel if it is one of the 60% that will survive 70 bar, and P2 represents the probability of survival if it is one of the 40% that will fail at 70 bar but will survive 58 bar or less, then the probability of survival of the vessel, if it is tested under the lower pressure test at 58 bar, is given by:

P = 0.60 x 1 + 0.40 x (1 - 0.60) = 0.76

If the pressure vessel is tested under the higher pressure test at 65 bar, the probability of survival is given by the sum of the probability of survival if the vessel is one of the 60% that will survive 70 bar, and the probability of survival if the vessel is one of the 40% that will fail at 70 bar but will survive 65 bar or less. If P3 represents the probability of survival of the vessel if it is one of the 40% that will fail at 70 bar but will survive 65 bar or less, then the probability of survival of the vessel, if it is tested under the higher pressure test at 65 bar, is given by:

P = 0.60 x 1 + 0.40 x (1 - 0.80 x P3)

The condition that the probability of survival of the vessel, if it is tested under the higher pressure test at 65 bar, is at least 0.95 is therefore:

0.60 + 0.40 x (1 - 0.80 x P3) ≥ 0.95

This simplifies to: P3 ≤ 0.625

Using the above values for P1, P2, and P3, it is clear that the probability of the vessel surviving if tested at the lower pressure of 58 bar is greater than 0.95. Therefore, the lower pressure test should be carried out.

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Given [tex]v=4i-j[/tex], and [tex]w=3i+2j\\[/tex], the angle between v and w is 47.7°.

To find the angle between vectors v and w, we can use the dot product formula:

v · w = |v| |w| cos(θ)

where v · w represents the dot product of v and w, |v| and |w| represent the magnitudes of vectors v and w, and θ represents the angle between the vectors.

First, let's calculate the magnitudes of vectors v and w:

|v| = √(4² + (-1)²) = √(16 + 1) = √17

|w| = √(3² + 2²) = √(9 + 4) = √13

Next, let's calculate the dot product of v and w:

v · w = (4)(3) + (-1)(2) = 12 - 2 = 10

Now, we can substitute the values into the dot product formula to find the angle θ:

10 = (√17)(√13) cos(θ)

cos(θ) = 10 / (√17)(√13)

cos(θ) = 10 / (√(17 * 13))

cos(θ) = 10 / (√221)

θ = cos⁻¹ (0.6717)

θ = 47.7°.

Therefore, the angle between vectors v and w is approximately 47.7° .

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Answer:

6

Step-by-step explanation:

No. of people going to beach = 46 .

Using Unitary Method ,

9 people can go in one van .

1 person can go in 1/9

46 people can go in 1/9 * 46 = 5.1

Since vans can't be in fraction , 1 extra van for 1 person is need that is for 46th person .

So total number of vans = 5 + 1 = 6

Answer:

Step-by-step explanation:

x = 6

arc RT = 49°

"It is a line that intersects the circle exactly at one point."

"It is a line that intersects circle at two points."

For given example,

arc QT = (27x + 3)°

arc RT = (9x – 5)°  

∠RST = (10x – 2)°

From figure we can observe that line ST is tangent and line SQ is secant.

∠RST is the angle subtended by tangent ST and secant SQ

We know, the angle subtended by the tangent and the secant is half the difference of the measures of the intercepted arcs.

⇒ ∠RST = (QT - RT)/2

⇒ 10x - 2 = [(27x + 3) - (9x - 5)] /2

⇒ 2(10x - 2) = 27x + 3 - 9x + 5

⇒ 20x - 4 = 18x + 8

⇒ 20x - 18x = 8 + 4

⇒ x = 6

So, arc RT would be,

⇒ 9x - 5 = 9(6) - 5

⇒ 9x - 5 = 49°

Therefore, arc RT = 49°

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Solution: Given, Abigail (A) and Balan (B) want to share a pizza of size

1. Both agents have the same utility function u(x) = 2 for pizza, Abigail discounts with 8A = 1/2. Balan discounts with 88 1/2 Abigail moves first.

We have to calculate the Rubinstein solution of the bargaining problem. Bargaining Solution Using Rubinstein's alternating offers model, the bargaining solution is:

Take x as the size of the pizza that Abigail gets.

Hence, Balan gets 1 - x.

The possible utility that they get are:

Abigail: 2x(1/2) + 0(1/2) = x

Balan: 2(1 - x)(88 1/2) + 0(11 1/2) = 177 - 177x The minimum utility that they both need to be satisfied is:

minimum value = 2 x 177/2 = 177

The bargaining range is [0,1], thus there are infinite pairs that satisfy the minimum utility requirement. However, Rubinstein assumes that the final solution should be somewhere between both parties' ideal points, so we can restrict the bargaining range to [1/2, 1]. Abigail gets x and Balan gets 1 - x. Now, we have to see what happens if Balan rejects this offer.

When Balan rejects, the bargaining range is [0, x) for Abigail and (x, 1] for Balan. In this range,

Abigail's ideal point is 2x(1/2) + 0(1/2) = x and

Balan's ideal point is 2(1 - x)(88 1/2) + 0(11 1/2) = 177 - 177x.

The bargaining range is again restricted to [1/2, 1]. When Balan rejects, the bargaining range is [0, x) for Abigail and (x, 1] for Balan. In this range, Abigail's ideal point is 2x(1/2) + 0(1/2) = x and Balan's ideal point is 2(1 - x)(88 1/2) + 0(11 1/2) = 177 - 177x.The bargaining range is again restricted to [1/2, x) and (x, 1].

Now, if Abigail rejects, then the bargaining range is (0, x) for Abigail and [x, 1] for Balan. In this range, Abigail's ideal point is 2x(88 1/2) + 0(11 1/2) = 177x and Balan's ideal point is 2(1 - x)(1/2) + 0(1/2) = 1 - x. The bargaining range is again restricted to (1/2, x) and (x, 1/2 + 1/176). In the next step, if Balan rejects, then the bargaining range is [0, x) for Abigail and (x, 1] for Balan. In this range, Abigail's ideal point is 2x(1/2) + 0(1/2) = x and Balan's ideal point is 2(1 - x)(1/2) + 0(1/2) = 1 - x. The bargaining range is again restricted to [1/2, x) and (x, 1/2 + 1/176).

Repeating the steps,

the solution is: x = 2/3, 177 - 177x = 59.

After calculating the Rubinstein solution of the bargaining problem, we can see that Abigail gets 2/3 of the pizza and Balan gets 1/3 of the pizza. There are two reasons why Abigail gets a larger share of the pizza: Abigail moves first, so she has an advantage because she can propose a deal that is more favorable to her. This is why the bargaining range is initially restricted to [1/2, 1]. Abigail has a lower discount rate than Balan, so she is willing to wait longer for a deal. This means that Abigail can drive a harder bargain because she has a higher reservation utility.

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Answer:

1695579

Step-by-step explanation:

Answer:

a = 12.

Step-by-step explanation:

Sum of n terms = n/2[2a + d(n-1)]

For 25 terms

S25 = 12.5(2a + 24d)

S25 = 25a + 300d

For 4 terms

S4 = 2(2a + 3d)

So:

S25 = 15*2(2a + 3d)

S25 = 60a + 90d

25a + 300d = 60a + 90d

35a =  210d

a = 6d

Take  a to be 12 and d to be 2:

25th term = 12.5(2*12 + 24 * 2) = 900

4th term = 2(24 + 6) = 60

900 = 15 * 60 so a = 12.

Answer:

Large number=12

Smaller number=6

Step-by-step explanation:

Let the two numbers be x and y

x+y=18

x-y=6

Answer:

I don't know how to do it the subject

Answer:

1/6

Step-by-step explanation:

1 out of the 6 cards is 4

Answer:  its 4x(3+2)-6÷ 1=14

Step-by-step explanation: in the picture

Answer:

Uh i dont really get it

Step-by-step explanation:

best of luck though

Based on the illustration above, the value of margin of error M.E is 6.961

Margin of error (M.E) is calculated as the product of critical value (CV) and standard error (SE) of sample mean.

The formula for standard error of sample mean is:

SE = σ/√n

where σ is the population standard deviation and n is the sample size. The formula for margin of error is:

M.E. = CV x SE

where CV is the critical value.

The critical value for a 95% confidence level with 22 degrees of freedom (sample size 23 - 1) is 2.074 (rounded to 3 decimal places).

The sample mean is 37.6 and the population standard deviation is 16.1.

Sample size, n = 23.

Using the formula,

SE = σ/√n

SE = 16.1/√23

SE = 3.365 (rounded to 3 decimal places)

Now, using the calculated value of SE and CV,

ME = CV x SE

ME = 2.074 × 3.365

ME = 6.961 (rounded to 1 decimal place)

Therefore, the margin of error (M.E.) is 6.961 (rounded to 1 decimal place).

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Answer: Where is the rest of the question?

Step-by-step explanation:

Answer:

Polymer to be mixed with water to produce 350 gallons of a 0.5% solution is  1.75 gallons.

Step-by-step explanation:

Solution weight-age   100% = 350 gallons

Polymer weight-age = 0.5 %  = ?

Water weight-age = 99.5 % = ?

100 =99.5 w + 0.5 p

350 = ?      + ?

Using ratios

100          350

0.5           p

Applying the cross product rule

p = 350 *0.5/100= 1.75 gallons

Polymer to be mixed with water to produce 350 gallons of a 0.5% solution is  1.75 gallons

Using ratios

100          350

99.5           w

Applying the cross product rule

w = 350*99.5 /100= 348.25 gallons

Water to be mixed with water to produce 350 gallons of a 0.5% solution is  348.25 gallons

The probability that Astronaut Joe, who is currently on Zorgon, will be affected by the impact is 0.667%.

To determine the probability that Astronaut Joe will be affected by the impact of the asteroid on planet Zorgon, we need to consider the area of the blast zone in relation to the total area of the planet.

An asteroid is heading for the planet Zorgon with a diameter of 2600 miles. When it hits, it will create a blast zone that extends 150 miles in all directions from the point of impact.

What is the probability that Astronaut Joe, who is currently on Zorgon, will be affected by this impact?

The total surface area of Zorgon is given by:2 * 3.14 * (1,300 miles)2 = 10.6 million sq Miles

The blast zone covers an area of:3.14 * (150 miles)2 = 70,685 sq Miles

To calculate the probability that Astronaut Joe will be affected by the impact, we divide the area of the blast zone by the total surface area of the planet.

That is,70,685 / 10.6 million = 0.00667 = 0.667%.

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Answer:

hmmm I think u need to talk to ur teacher

Answer:

6

Step-by-step explanation:

The GCF of 42 and 12 is 6

The profit function is; P(x) = -0.01·x² + 3.2·x + 150

What is a profit?

Profit is the amount gained following a business transaction, which is the difference between the amount received as payment for doing a business transaction, within a specified period, known as the revenue and the amount amount spent or invested in doing the business, including the fixed and variable expenses, which is the cost of the business.

The cost and the revenue functions, obtained from a similar question on the internet are;

The cost function is; C(x) = 150 + 5.8·x

The profit function is; R(x) = 9·x - 0.01·x²

The profit function, P(x), is therefore; P(x) = 9·x - 0.01·x² - (150 + 5.8·x) = -0.01·x² + 3.2·x + 150

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Answer:

{48, 64, 81}

Step-by-step explanation:

Complete question :

On their first dive, researchers explore a part of the ocean floor that is 60 feet below sea level. This depth can be represented by the integer -60. On their second dive, researchers explore a deeper depth. Write an inequality that represents the possible depth, d, of the researchers' second dive.

Answer:

d < - 60

Step-by-step explanation:

Depth explored during first dive = 60 feets below sea level = - 60 feets

The depth, d explored during second dive is deeper Than that explored during first dive

The inequality representing depth on second,

This means they the depth exceeds 60 feets below sea level. And hence. Deeper than - 60

Therefore, the depth will be values less Than - 60

Hence, d < - 60

The null hypothesis (H0) assumes that the proportion of adults annoyed by television violence is equal to or greater than 0.5, while the alternative hypothesis (Ha) assumes that the proportion is less than 0.5.

In this case, the sample proportion is calculated as the number of adults indicating annoyance divided by the total sample size: 1,152/2,400 = 0.48.

Next, we can calculate the test statistic, which follows a standard normal distribution under the null hypothesis. The test statistic formula is z = (p - P) / sqrt(P(1-P)/n), where p is the sample proportion, P is the hypothesized proportion under the null hypothesis (0.5 in this case), and n is the sample size.

Using the given values, we can calculate the test statistic:

z = (0.48 - 0.5) / sqrt(0.5(1-0.5)/2400) ≈ -1.67.

Finally, we compare the test statistic to the critical value. At a significance level of 0.10, the critical value for a one-tailed test is approximately -1.28. Since the test statistic (-1.67) is smaller than the critical value, we reject the null hypothesis. This suggests that there is evidence to support the claim that less than half of all adults are annoyed by violence on television.

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Answer:

$18.5

Step-by-step explanation:

You just add up all the costs and divide them by two and then you would get your answer

Answer:

1

Step-by-step explanation:

Answer:

324

...................

Answer: 7,833

Step-by-step explanation:

Answer:

1)

Triangle formula:

A = 1/2bh

A = 1/2(3)(5.9)

A = 8.85

2)

Parallelogram Area:

A = bh

A = (8.9)(6)

A = 53.4

Answer:

B

Step-by-step explanation:

The average rate of change in the closed interval [ a, b ] is

[tex]\frac{f(b)-f(a)}{b-a}[/tex]

Here [ a , b ] = [ 15, 35 ]

and f(b) = f(35) = 400 ← from graph

f(a) = f(15) = 200 ← from graph

Then average rate of change is

[tex]\frac{400-200}{35-15}[/tex] = [tex]\frac{200}{20}[/tex] = 10 m/ s → B

Given that we randomly select 100 drivers ages 16 to 19 from example 4. We are to determine the probability that the mean distance traveled each day is between 19.4 and 22.5 miles. The probability that the mean distance traveled each day is between 19.4 and 22.5 miles is approximately 1.00.

Probability distribution is a function which represents the probabilities of all possible values of a random variable.

When the probability distribution of a random variable is unknown, we can use the Central Limit Theorem (CLT) to estimate the mean of the population.

Let X be the mean distance traveled each day by the 100 drivers ages 16 to 19.

Then, the distribution of X is approximately normal with the mean μ = 20.4 miles and the standard deviation σ = 3.8 miles.

Therefore, we can calculate the z-score as follows; z = (X - μ) / (σ / √n), where X = 19.4 and n = 100.

z₁ = (19.4 - 20.4) / (3.8 / √100)

z₁ = -2.63 and

z₂ = (22.5 - 20.4) / (3.8 / √100)

z₂ = 5.53

Hence, the probability that the mean distance traveled each day is between 19.4 and 22.5 miles is;

P(19.4 < X < 22.5) = P(z₁ < z < z₂).

Using the z-table, the probability is found to be; P(-2.63 < z < 5.53) ≈ 1.00.

Therefore, the probability that the mean distance traveled each day is between 19.4 and 22.5 miles is approximately 1.00.

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The AIC, or the Akaike Information Criterion, strikes a balance between model complexity and goodness of fit.

In statistical modeling, it is crucial to find a balance between the complexity of a model and its ability to accurately capture the underlying patterns in the data. On one hand, a complex model with numerous parameters may be able to fit the data very closely, resulting in a low error or residual.

However, such a model runs the risk of overfitting, meaning it may become too specific to the training data and perform poorly when applied to new, unseen data.

On the other hand, a simpler model with fewer parameters may not capture all the nuances of the data and may have a higher error or residual. This is known as underfitting, as the model fails to capture the underlying complexity of the data.

The AIC addresses this trade-off by considering both the goodness of fit and the complexity of the model. It penalizes models with a higher number of parameters, encouraging a balance between model complexity and goodness of fit.

The AIC takes into account the residual sum of squares (RSS) or the likelihood of the model, and adjusts it based on the number of parameters used. The goal is to select the model with the lowest AIC value, indicating a good compromise between complexity and fit.

By striking this balance, the AIC provides a reliable criterion for model selection, allowing researchers and statisticians to choose the most appropriate model for their data while avoiding both overfitting and underfitting.

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