Assume that in a given year the mean mathematics SAT score was 572, and the standard deviation was 127. A sample of 72 scores is chosen. Use the TI-84 Plus calculator. Part 1 of 5 (a) What is the probability that the sample mean score is less than 567? Round the answer to at least four decimal places. The probability that the sample mean score is less than 567 is _____

In the given relationship, the independent variable is the number of books ordered, and the dependent variable is the cost to join the book club.

Now, let's answer the questions:

1. What is the independent variable in this relationship?

  Answer: The independent variable is the number of books ordered.

2. What is the dependent variable in this relationship?

  Answer: The dependent variable is the cost to join the book club.

3. What is the fixed cost in this relationship?

  Answer: The fixed cost is $5.00 per month, which is the cost to join the book club.

4. What is the variable cost in this relationship?

  Answer: The variable cost is $2.50 for every book ordered.

5. Write an equation to represent the relationship between the number of books ordered (x) and the cost to join the book club (y).

  Answer: The equation is y = 5 + 2.50x, where y represents the cost and x represents the number of books ordered.

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True, when dividing a sample into subsamples, it is generally recommended to have a minimum sample size of 30 for each subsample. This guideline is based on the Central Limit Theorem, which states that the distribution of sample means approaches a normal distribution as the sample size increases.

With a sample size of 30 or more, the sampling distribution becomes reasonably close to a normal distribution, allowing for more accurate inferences and hypothesis testing.

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The expression that has a value of 2/3 is option A. (8+24) ÷ (12 × 4).

Finding the expression that has a value of 2/3, simplify each expression and see which one equals 2/3.

A. (8+24) ÷ (12 × 4) = 32 ÷ 48 = 2/3

B. 8+24÷12 x 4 = 8+2 x 4 = 8+8 = 16/12 ≠ 2/3

C. 8+(24 ÷12) x 4 = 8+2 x 4 = 8+8 = 16/12 ≠ 2/3

D. 8+24 ÷ (12x4) = 8+24 ÷ 48 = 8+1/2 = 16/2 ≠ 2/3

Therefore, the expression that has a value of 2/3 is A. (8+24) ÷ (12 × 4).

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The value of the expression 2(cos 45°sin 45° + tan²30°) is 5/3.

Let's evaluate the given expression :

cos 45° = √2/2 (This is a standard value for cosine of 45 degrees.)

sin 45° = √2/2 (This is a standard value for sine of 45 degrees.)

tan 30° = sin 30° / cos 30° = (1/2) / (√3/2) = √3/3 (This is a standard value for tangent of 30 degrees.)

Now, let's substitute these values back into the original expression:

2(cos 45°sin 45° + tan²30°)

= 2(√2/2 * √2/2 + (√3/3)²)

= 2(1/2 + 3/9)

= 2(1/2 + 1/3)

= 2(3/6 + 2/6)

= 2(5/6)

= 10/6

= 5/3

Therefore, the value of the expression 2(cos 45°sin 45° + tan²30°) is 5/3.

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The measure of angle D in triangle DEF can be found using trigonometry. By applying the tangent function, we can determine that the measure of angle D is approximately 41 degrees.

In triangle DEF, we are given that angle F is a right angle (90 degrees), FD has a length of 3.3 feet, and DE has a length of 3.9 feet. To find the measure of angle D, we can use the tangent function.

Tangent is defined as the ratio of the length of the side opposite an angle to the length of the side adjacent to it. In this case, we can use the tangent function with respect to angle D.

The tangent of angle D is equal to the ratio of the length of side DE (opposite angle D) to the length of side FD (adjacent to angle D). Thus, tan(D) = DE / FD.

Substituting the given values, we have tan(D) = 3.9 / 3.3. Using a calculator or a trigonometric table, we can find the value of D to be approximately 41 degrees to the nearest degree. Therefore, the measure of angle D in triangle DEF is approximately 41 degrees.

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We may need to consider other methods of estimation, such as maximum likelihood estimation or Bayesian estimation

To estimate the parameter θ using the method of moments, we first find the first moment of the distribution in terms of the parameter θ, and then set it equal to the sample mean. Solving for θ gives us our estimate.

For this problem, the first moment of the distribution with density Ox®-1 is:

E[X] = ∫x(Ox®-1)dx from 0 to 1

= ∫x^(2-1)dx from 0 to 1

= ∫x dx from 0 to 1

= 1/2

Setting this equal to the sample mean of the three observations X1 = 0.4, X2 = 0.7, and X3 = 0.9, we have:

1/2 = (X1 + X2 + X3)/3

Solving for the sample mean, we get:

(X1 + X2 + X3)/3 = 1/2

X1 + X2 + X3 = 3/2

Substituting the sample values, we have:

0.4 + 0.7 + 0.9 = 3/2

Simplifying, we get:

2 = 3/2

This is clearly not true, so there must be some mistake in our calculations. Checking our work, we see that the first moment of the distribution is actually undefined since the integral diverges as x approaches 1. Therefore, we cannot use the method of moments to estimate the parameter θ in this case.

We may need to consider other methods of estimation, such as maximum likelihood estimation or Bayesian estimation

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To determine how many erasers Ayita can buy for the same amount that she would pay for 2 notepads, we need to compare the costs of erasers and notepads.

The cost of one eraser is $0.05, and the cost of one notepad is $0.65.

Let's calculate the total cost for 2 notepads:

Total cost of 2 notepads = 2 * $0.65 = $1.30

To find out how many erasers Ayita can buy for the same amount, we can divide the total cost of 2 notepads by the cost of one eraser:

Number of erasers Ayita can buy = Total cost of 2 notepads / Cost of one eraser

Number of erasers = $1.30 / $0.05 = 26

Therefore, Ayita can buy 26 erasers for the same amount that she would pay for 2 notepads.

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The correct statement regarding the rate of change of each linear function is given as follows:

The rate of change is greater for Function B then for Function A.

The slope-intercept equation for a linear function is presented as follows:

y = mx + b

The coefficients m and b represent the slope and the intercept, respectively, and are explained as follows:

For function A, when x increases by 1, y increases by 1, hence the rate of change is given as follows:

1.

For function B, considering the slope-intercept definition, the function is given as follows:

2.

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The angular velocity of the wheel at the beginning of the 4.50-s interval was 19.125 rad/s.To find the angular velocity at the beginning of the 4.50-s interval, we can use the formula:

ω = ω₀ + αt

where:
ω = final angular velocity
ω₀ = initial angular velocity (what we're trying to find)
α = angular acceleration (given as 2.25 rad/s²)
t = time interval (given as 4.50 s)

Plugging in the values, we get:

ω = ω₀ + αt
30.0 rad/s = ω₀ + (2.25 rad/s²)(4.50 s)

Simplifying and solving for ω₀, we get:

ω₀ = 30.0 rad/s - (2.25 rad/s²)(4.50 s)
ω₀ = 19.125 rad/s

Therefore, the angular velocity of the wheel at the beginning of the 4.50-s interval was 19.125 rad/s.

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The ratio test for the series ∑n=1infinitynn4 shows that it converges.

To apply the ratio test, we evaluate the limit of the absolute value of the ratio of successive terms:

l = limn→[infinity]∣∣∣an+1/an∣∣∣

= limn→[infinity]∣∣∣(−8)(n+1)(n+1)4/n4(−8)nn4∣∣∣

= limn→[infinity]∣∣∣(n/n+1)4∣∣∣

Since the limit of the ratio is less than 1, the series converges absolutely by the ratio test.

Therefore the ratio test for the series ∑n=1infinitynn4 shows that it converges.

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a. There are 26 options for each of the 6 letter spots, and 10 options for each of the 2 number spots, so the total number of possible passwords is 26^6 * 10^2 = 56,800,235,584,000.

b. Since there is only one correct password and there are a total of 26^6 * 10^2 possible passwords, the probability of guessing the correct password is 1/(26^6 * 10^2) = 1/56,800,235,584,000.

c. There are 26 options for the first letter spot, 26 options for the second letter spot, and so on, down to 26 options for the sixth letter spot. For the first number spot, there are 10 options, and for the second number spot, there are 9 options (since the number cannot be repeated). Therefore, the total number of possible passwords is 26^6 * 10 * 9 = 40,810,243,200.

d. Using the same logic as in part (c), the total number of possible passwords is 26^6 * 10 * 9, but now we must subtract the number of passwords where the digit 9 appears twice. There are 6 options for where the 9's can appear (the first and second number spots, the first and third number spots, etc.), and for each of these options, there are 26^6 * 1 * 8 = 4,398,046,848 passwords (26 options for each of the 6 letter spots, 1 option for the first 9, and 8 options for the second 9). Therefore, the total number of possible passwords is 26^6 * 10 * 9 - 6 * 4,398,046,848 = 39,150,220,352.

e. For the first letter spot, there are 26 options, for the second letter spot, there are 25 options (since we cannot reuse the letter from the first spot), and so on, down to 21 options for the sixth letter spot. For the first number spot, there are 10 options, and for the second number spot, there are 9 options. Therefore, the total number of possible passwords is 26 * 25 * 24 * 23 * 22 * 21 * 10 * 9 = 4,639,546,400.

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To find out how many miles apart the school and the park are, we need to convert the distance from kilometers to miles.

Given that there are 1.6 km in a mile, we can set up a conversion factor:

1 mile = 1.6 km

Now, we can calculate the distance in miles by dividing the distance in kilometers by the conversion factor:

Distance in miles = Distance in kilometers / Conversion factor

Distance in miles = 6 km / 1.6 km/mile

Simplifying the expression:

Distance in miles = 3.75 miles

Therefore, the school and the park are approximately 3.75 miles apart.

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False.  in minimizing a unimodal function of one variable by golden section search,the point discarded at each iteration is always thepoint having the largest function value

In minimizing a unimodal function of one variable by golden section search, the point discarded at each iteration is always the one that leads to the smallest interval containing the minimum. This is achieved by comparing the function values at two points that divide the interval into two subintervals of equal length, and discarding the one with the larger function value. This process is repeated until the interval becomes sufficiently small, and the point with the smallest function value within that interval is taken as the minimum.

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Thus,  the average cost per unit for an output of q units is given by the equation c/q = 12000/q + 7, where the fixed cost is $12,000 and the variable cost is given by the function cv = 7q.

The given equation for the total cost of producing q units of a product is c = 5000 + 6q.

To find the average cost per unit for an output of q units, we need to divide the total cost by the number of units produced.

Thus, the average cost per unit can be written as c/q.

Substituting the given equation for c in terms of q, we get

c/q = (5000 + 6q)/q.

Simplifying this expression, we get c/q = 5000/q + 6.

Now, we are given that the fixed cost is $12,000 and the variable cost is given by the function cv = 7q.

The total cost equation c can be written as the sum of the fixed cost and the variable cost, i.e., c = 12000 + cv. Substituting the given equation for cv, we get c = 12000 + 7q.

Substituting this equation for c in terms of q in the expression we derived earlier for c/q, we get c/q = (12000 + 7q)/q. Simplifying this expression, we get c/q = 12000/q + 7.

Therefore, the average cost per unit for an output of q units is given by the equation c/q = 12000/q + 7, where the fixed cost is $12,000 and the variable cost is given by the function cv = 7q.

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The projection of w onto each vector in the basis is -v1 - 5v2 + 4v3.

We can use the orthogonal projection formula to find the coordinates of w with respect to the basis {v1, v2, v3}.

The coordinates of w are given by:

w1 = ⟨w, v1⟩ / ⟨v1, v1⟩ = -3/3 = -1

w2 = ⟨w, v2⟩ / ⟨v2, v2⟩ = -40/8 = -5

w3 = ⟨w, v3⟩ / ⟨v3, v3⟩ = 64/16 = 4

So, the coordinates of w with respect to the basis {v1, v2, v3} are (-1, -5, 4).

To find the projection of w onto each vector in the basis, we can use the formula for orthogonal projection:

proj_v1(w) = ⟨w, v1⟩ / ⟨v1, v1⟩ × v1 = (-3/3) × v1 = -v1

proj_v2(w) = ⟨w, v2⟩ / ⟨v2, v2⟩ × v2 = (-40/8) × v2 = -5v2

proj_v3(w) = ⟨w, v3⟩ / ⟨v3, v3⟩ × v3 = (64/16) × v3 = 4v3

The projection of w onto each vector in the basis is -v1 - 5v2 + 4v3.

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The norm of vector w in span(v1, v2, v3) is ||w|| = 13.

Given an orthogonal set of vectors v1, v2, v3 in R^5, and a vector w in the span of v1, v2, v3, we are provided with the inner products between v1, v2, v3, and w.

To find the norm of vector w, we use the formula:

||w|| = sqrt(⟨w, w⟩)

We are given the inner products between w and v1, v2, v3:

⟨w, v1⟩ = -3

⟨w, v2⟩ = -40

⟨w, v3⟩ = 64

The norm of w can be computed as follows:

||w|| = sqrt((-3)^2 + (-40)^2 + 64^2)

      = sqrt(9 + 1600 + 4096)

      = sqrt(5705)

      ≈ 13

Therefore, the norm of vector w in the span of v1, v2, v3 is approximately 13.

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construct a 99% confidence interval for the mean age of U.S. college students Confidence Interval is (21.458, 23.902)

To construct a 99% confidence interval for the mean age of U.S. college students, we can use the formula for a confidence interval for a population mean when the population standard deviation is known.

a. The function commonly used to create the confidence interval is the "z-score" or "standard normal distribution."

b. The confidence interval can be calculated using the following formula:

Confidence Interval = sample mean ± (z-value * (population standard deviation / √(sample size)))

For a 99% confidence interval, the corresponding z-value is 2.576, which can be obtained from the standard normal distribution table or using statistical software.

Plugging in the given values:

Sample mean = 22.68 years

Population standard deviation = 4.74 years

Sample size = 100

Confidence Interval = 22.68 ± (2.576 * (4.74 / √100))

Confidence Interval = 22.68 ± (2.576 * 0.474)

Confidence Interval ≈ 22.68 ± 1.222

c. Interpretation: We are 99% confident that the true mean age of U.S. college students lies between 21.458 years and 23.902 years based on the given sample. This means that if we were to take multiple random samples and construct 99% confidence intervals using the same method, approximately 99% of those intervals would contain the true population mean.

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Equation f(x) = ax² + bx + c reveals its extreme value without needing to be altered.

The extreme value of this equation has a minimum or maximum at the point (h, k).

Explanation: The extreme value of a quadratic function is also known as the vertex of the parabola. The vertex is the highest or lowest point on the parabola, depending on the coefficient of the x² term. For a quadratic function of the form f(x) = ax² + bx + c, the vertex can be found using the formula: h = -b/2a and k = f(h) = a(h²) + b(h) + c. The value of h represents the x-coordinate of the vertex, while the value of k represents the y-coordinate of the vertex. The sign of the coefficient of the x² term determines whether the vertex is a minimum or maximum. If a > 0, the parabola opens upwards and the vertex is a minimum. If a < 0, the parabola opens downwards and the vertex is a maximum. Therefore, equation f(x) = ax² + bx + c reveals its extreme value without needing to be altered. The extreme value of this equation has a minimum or maximum at the point (h, k).

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Based on the above, the equation of the parabola shown in the graph is x=y²/8+y/2+9/2

Note that based on the question, we were given:

The Standard equation of parabola is one that is given by:

(y - k)2 = 4p (x - h)

Note also that:

Hence, by comparing the similarities of the give value with the one above:

(h + p, k)= (6,-2)

k=-2

h+p=6

h=6-p

Hence: directrix: x=h-p

h-p=2

So by Plugging  the value of h=6-p into the above equation:

6-p-p=2

6-2p=2

-2p=2-6

-2p=-4

p=-4/-2

p=2

Plugging p=2 into h-p=2, it will be:

h=2+p

h=2+2

h=4

By plugging k=-2, p=2, h=4 in standard equation of parabola will be:

(y - k)2 = 4p (x - h)

(y-(-2))² = 4(2) (x - 4)

(y+2)² = 8 (x - 4)

y2+4y+4=8x-32

y2+4y+4+32=8x

x=y²/8+4y/8+36/8

x=y²/8+y/2+9/2

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The matrix P_1 for the factorization A = P_1.D_1.P^-1_1 is P_1 = [15 -30 15 -75; 0 0 0 0; 0 0 0 0; -25 50 -25 125].

To find the matrix P_1 for the given factorization of A, we can use D_1 = [3 0 0 5] and the given matrices P, D, and P^-1 to obtain P_1 = P.D_1.(P^-1).

Given factorization of A is A = PDP^-1, where A = [9 -12 2 1], P = [1 -2 1 -3], D= [5 0 0 3], and P^-1 = [3 -2 1 -1]. We are also given a diagonal matrix D_1 = [3 0 0 5]. To find the matrix P_1 for the factorization A = P_1.D_1.P^-1_1, we can use the following steps:

Multiply P and D_1 to obtain PD_1:

PD_1 = [1 -2 1 -3] * [3 0 0 5] = [3 -6 3 -15 0 0 0 0]

Multiply PD_1 and P^-1 to obtain P_1:

P_1 = PD_1 * P^-1 = [3 -6 3 -15 0 0 0 0] * [3 -2 1 -1; -6 4 -2 2; 3 -2 1 -1; -15 10 -5 5]

= [15 -30 15 -75; 0 0 0 0; 0 0 0 0; -25 50 -25 125]

Therefore, the matrix P_1 for the factorization A = P_1.D_1.P^-1_1 is P_1 = [15 -30 15 -75; 0 0 0 0; 0 0 0 0; -25 50 -25 125].

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Answer: 1086.396 inches squared

Step-by-step explanation:

Hi there,

The area formula for an octagon is:

[tex]A=2s^{2} (1+\sqrt{2} )[/tex]

With "A" representing area and "S" representing side length.

You are given the side length, so just plug that in for "S" and input it into your calculator. It should look something like this:

[tex]A=2(15)^{2} (1+\sqrt{2} )\\[/tex]

A= 1086.396 inches squared.

I hope this helps.

Good luck :)

The Niagara Falls incline railway rises vertically by approximately 98 feet.

The angle of elevation of 30° indicates the angle between the incline railway and the horizontal ground. The total length of the incline railway is given as 196 feet.

To find the vertical rise, we can use trigonometry. The vertical rise can be determined by calculating the sine of the angle of elevation and multiplying it by the total length of the incline railway:

Vertical rise = Total length × sine(angle of elevation)

Vertical rise = 196 ft × sin(30°)

Vertical rise ≈ 196 ft × 0.5

Vertical rise ≈ 98 ft

Therefore, the Niagara Falls incline railway rises vertically by approximately 98 feet.

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The pair x(t) = e^3t, y(t) = e^t is a solution to the given system.

The given system consists of two differential equations: dx/dt = 3y^3 and dy/dt = y. We are given the pair x(t) = e^3t and y(t) = e^t. To verify if this pair is a solution, we need to substitute these values into the differential equations and check if they hold true.

Substituting x(t) = e^3t and y(t) = e^t into the first equation, we have dx/dt = 3(e^t)^3. Simplifying, we get dx/dt = 3e^(3t).

Similarly, substituting x(t) = e^3t and y(t) = e^t into the second equation, we have dy/dt = e^t.

We can see that both sides of the differential equations match the given pair (x(t), y(t)). Hence, x(t) = e^3t and y(t) = e^t satisfy the given system of differential equations.

To sketch the trajectory of the given solution in the phase plane, we can plot the points (x(t), y(t)) for different values of t. The trajectory would represent the path traced by the solution in the phase plane.

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The roots of the quadratic equation are -4 and 4, and the equation can be written as f(x) = x^2 - 16.

The graph provided depicts a parabolic curve. In order to determine the roots of the corresponding quadratic equation, we need to identify the x-values where the graph intersects the x-axis. Since the scales on both axes are going "by 2's," we can estimate the x-values accordingly.

Based on the graph, it appears that the curve intersects the x-axis at x = -4 and x = 4. Therefore, these are the roots of the quadratic equation associated with the graph.

To express the equation in standard form, we can use the roots to form the factors: (x + 4)(x - 4). Expanding this expression yields x^2 - 16. Thus, the roots of the quadratic equation are -4 and 4, and the equation can be written as f(x) = x^2 - 16.

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Simplifying further:

P(S = 5) =[tex]((1/3)^j)[/tex] (1 + (1/3) + [tex](1/3)^2[/tex] + [tex](1/3)^2[/tex] + [tex](1/3)^4[/tex]+ [tex](1/3)^5)[/tex]

The numerical value will be 5.

To determine the probability P(S = 5) for the compound Poisson random variable S, we need to use the probability mass function (PMF) of S, given the parameters λ = 4 and p(xi = i) = 1/3.

The PMF of a compound Poisson random variable is given by the formula:

P(S = k) =[tex]e^(-\lambda) \times (\lambda^k / k!) \times \sum[j=0 to k] (p(xi = i))^j[/tex]

In this case, we have λ = 4 and p(xi = i) = 1/3. Substituting these values into the formula, we get:

P(S = 5) = [tex]e^{(-4)} \times (4^5 / 5!) \times \times[j[/tex]=0 to 5] [tex]((1/3)^j)[/tex]

Simplifying further:

P(S = 5) =[tex]((1/3)^j)[/tex] (1 + (1/3) + [tex](1/3)^2[/tex] + [tex](1/3)^2[/tex] + [tex](1/3)^4[/tex]+ [tex](1/3)^5)[/tex]

Using a calculator or software, we can calculate the values and simplify the expression to obtain the numerical value of P(S = 5).

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To determine the probability of s being equal to 5, we first need to understand what a compound Poisson random variable is.

A compound Poisson random variable is a type of discrete random variable where the number of events (n) follows a Poisson distribution with parameter λ, and the values of each event (Xi) follow a probability distribution with mean μ and variance σ^2.

In this case, we know that λ = 4 and p(Xi = i) = 1/3. Therefore, we can say that μ = E(Xi) = 1/3 and σ^2 = Var(Xi) = 2/9.

Now, to find the probability of s being equal to 5, we can use the following formula:

P(s = 5) = e^-λ * (λ^5 / 5!) * P(Xi1 + Xi2 + ... + Xin = 5)

Here, we are using the Poisson distribution to calculate the probability of having exactly 5 events, and then multiplying it by the probability of their sum being equal to 5.

Since the values of each event (Xi) are independent and identically distributed, we can use the convolution formula to find the distribution of their sum:

P(Xi1 + Xi2 + ... + Xin = k) = ∑ P(Xi1 = i1) * P(Xi2 = i2) * ... * P(Xin = in)

Where the summation is over all possible values of i1, i2, ..., in such that i1 + i2 + ... + in = k.

In this case, since all Xi values have the same distribution, we can simplify this to:

P(Xi1 + Xi2 + ... + Xin = k) = (1/3)^n * (n choose k)

Where (n choose k) is the binomial coefficient that counts the number of ways to choose k events out of n.

Therefore, we can plug these values into the formula for P(s = 5):

P(s = 5) = e^-4 * (4^5 / 5!) * (1/3)^4 * (4 choose 5)

P(s = 5) = 0.0186

Therefore, the probability of s being equal to 5 is approximately 0.0186.

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From the circle the value of the variable x is 130 degree.

In the circle  we have to find the value of angle x and angle y

for the given circle there are two tangents which touches the circle at only point

In the figure a tangent and a line passing through the circle forms an angle x.

The measure of the arc opposite to the angle x is 180 degrees.

Now the sum of  angle x and fifty is equal to measure of the arc opposite to the angle x which is 180 degrees.

x+50=180

Subtract 50 from both sides:

x=180-50

When fifty is subtracted from one hundred eighty we get one hundred and thirty.

x=130 degrees

Hence, the value of the variable x is 130 degrees from the circle.

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The value of (3u − v)(u − 3v) = -57 when uu = 8, uv = 7, and vv = 6.

To find the result of (3u - v)(u - 3v) when uu = 8, uv = 7, and vv = 6, we will first need to rewrite the given expressions in terms of u and v, and then simplify the expression.

Let u² = uu = 8, u*v = uv = 7, and v² = vv = 6. Now, let's expand the given expression:

(3u - v)(u - 3v) = (3u - v) * u - (3u - v) * 3v

Expanding and simplifying the terms, we get:

= 3u² - 9uv - uv + 3v² = 3(u² - 3uv - v²)

Now, let's substitute the given values of u², uv, and v² into the expression:

= 3(8 - 3(7) - 6) = 3(8 - 21 - 6) = 3(-19)

So, (3u - v)(u - 3v) equals -57 when uu = 8, uv = 7, and vv = 6.

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The 95% confidence interval is 1.23 to 1.51

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

Sample, n = 22

Mean, x = 1.37 oz

Standard deviation, s = 0.33 oz

Start by calculating the margin of error using

E = s/√n

So, we have

E = 0.33/√22

E = 0.07

The 95% confidence interval is

CI = x ± zE

Where

z = 1.96 i.e. z-score at 95% CI

So, we have

CI = 1.37 ± 1.96 * 0.07

Evaluate

CI = 1.37 ± 0.14

This gives

CI = 1.23 to 1.51

Hence, the 95% confidence interval is 1.23 to 1.51

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The probability that an infant selected at random from among those delivered at the hospital measures more than 23.5 inches is 0.0475 or approximately 4.75%. (option c).

To find the probability that an infant selected at random from among those delivered at the hospital measures more than 23.5 inches, we need to calculate P(X > 23.5). To do this, we first standardize the variable X by subtracting the mean and dividing by the standard deviation:

Z = (X - µ)/σ

In this case, we have:

Z = (23.5 - 20)/2.1 = 1.667

Next, we use a standard normal distribution table or calculator to find the probability of Z being greater than 1.667. Using a standard normal distribution table, we can find that the probability of Z being less than 1.667 is 0.9525. Therefore, the probability of Z being greater than 1.667 is:

P(Z > 1.667) = 1 - P(Z < 1.667) = 1 - 0.9525 = 0.0475

Hence, the correct option is (c)

Therefore, we can conclude that it is relatively rare for an infant's length at birth to be more than 23.5 inches, given the mean and standard deviation of the distribution.

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Complete Question:

The medical records of infants delivered at the Kaiser Memorial Hospital show that the infants' lengths at birth (in inches) are normally distributed with a mean of 20 and a standard deviation of 2.1. Find the probability that an infant selected at random from among those delivered at the hospital measures is more than 23.5 inches.

a. 0.0485

b. 0.1991

c. 0.0475

d. 0.9515

e. 0.6400

So these 2 angles equal 180 degrees.

Angle 1 + Angle 2 = 180 degrees.

The problem tells us that angle 1 is 6x, and angle 2 is (x+26).

Substitute those into our equation.

6x + (x+26) = 180.

Now let's solve for x.

7x + 26 = 180

7x = 154

x = 22

Now go back and substitute x=22 into the info we were given.

Angle 1 = 6x = 6(22) = 132 degrees.

Angle 2 = (x+26) = (22+26) = 48 degrees.

Let's do a quick check - - - angle 1 and angle 2 should add to 180!

132 + 48 = 180.