What is the probability that either event will occur?
Now, find the probability of event B.
A
6
20
6
B
20
P(B) = [?]
Enter as a decimal rounded to the nearest hundredth.
Enter

there are 1365 possible committees that can be formed from this group of 15 people, regardless of gender.

To form a committee of 4 people from a group of 9 women and 6 men, we need to consider all possible combinations of 4 people, regardless of gender.

The number of ways to choose 4 people from a group of 15 (9 women and 6 men) is given by the combination formula:

C(15,4) = 15! / (4! * (15-4)!) = 15! / (4! * 11!) = (15 * 14 * 13 * 12) / (4 * 3 * 2 * 1) = 1365

Therefore, there are 1365 possible committees that can be formed from this group of 15 people, regardless of gender.

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The steady-state solutions of y'(t) =

[tex] y^2 - 15y + 56[/tex]

are y = 7 and y = 8, with y = 7 being a stable equilibrium point and y = 8 being an unstable equilibrium point.

The steady-state solutions of a differential equation are the values of the function that remain constant over time. To find the steady-state solutions of the given differential equation, we need to set y'(t) = 0 and solve for y.

[tex]y^2 - 15y + 56 = 0[/tex]

We can factor this quadratic equation as (y-7)(y-8) = 0, so the steady-state solutions are y = 7 and y = 8. These values are called equilibrium points or fixed points because if y(t) starts at one of these values, it will remain there as time goes on.

To understand the behavior of the system around these steady-state solutions, we can use the first derivative test. If y'(t) > 0 for y < 7 or y > 8, then y(t) is increasing and moving away from the steady-state solution. If y'(t) < 0 for 7 < y < 8, then y(t) is decreasing and moving towards the steady-state solution. Hence, y = 7 is a stable equilibrium point, and y = 8 is an unstable equilibrium point.

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You asked to sketch the function f(t) and find its Fourier Transform, where f(t) = 1 for 0 ≤ t < 1, and f(t) = 0 otherwise.

(i) To sketch the function f(t), follow these steps:
1. Set up a coordinate system with the horizontal axis representing time (t) and the vertical axis representing the amplitude of the function (f(t)).
2. For the time interval 0 ≤ t < 1, draw a horizontal line at f(t) = 1.
3. For any other time intervals (t < 0 or t ≥ 1), draw a horizontal line at f(t) = 0.

(ii) To find the Fourier Transform of the function f(t), use the following formula:
F(ω) = ∫[f(t) * e^(-jωt)] dt, where ω is the angular frequency and the integral is evaluated over the entire domain of the function.

Since f(t) is non-zero only in the interval 0 ≤ t < 1, we can limit the integration to that interval:
F(ω) = ∫[e^(-jωt)] dt from 0 to 1.

Now, integrate the function with respect to t:
F(ω) = [-1/jω * e^(-jωt)] evaluated from 0 to 1.

Evaluate the limits of the integral:
F(ω) = [-1/jω * e^(-jω)] - [-1/jω * e^(0)].
F(ω) = (-1/jω * e^(-jω)) + (1/jω).

So, the Fourier Transform of the function f(t) is given by:
F(ω) = (1/jω) * (1 - e^(-jω)).

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The approximated value of the volume of the cone cup is 18.5 cubic cm

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

Diameter = 2.8 cm

Height = 9 cm

The volume of the cone cup is calculated as

Volume = 1/3 * 3.14 * r^2h

substitute the known values in the above equation, so, we have the following representation

Volume = 1/3 * 3.14 * (2.8/2)^2 * 9

Evaluate the products

So, we have

Volume = 18.4632

Approximate

Volume = 18.5

Hence, the volume is 18.5

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To begin, let's recall that synthetic division is a method used to divide a polynomial by a linear factor (i.e. a binomial of the form x-a, where a is a constant). The result of synthetic division is the quotient of the division, which is a polynomial of one degree less than the original polynomial.

In this case, we are given that x is a solution of a third-degree polynomial equation. This means that the polynomial can be factored as (x-r)(ax^2+bx+c), where r is the given solution and a, b, and c are constants that we need to determine.

To use synthetic division, we will divide the polynomial by x-r, where r is the given solution. The result of the division will give us the coefficients of the quadratic factor ax^2+bx+c.

Here's an example of how to do this using synthetic division:

Suppose we are given the polynomial P(x) = x^3 + 2x^2 - 5x - 6 and we know that x=2 is a solution.

1. Write the polynomial in descending order of powers of x:

P(x) = x^3 + 2x^2 - 5x - 6

2. Set up the synthetic division table with the given solution r=2:

2 | 1  2  -5  -6

3. Bring down the leading coefficient:

2 | 1  2  -5  -6
  ---
   1

4. Multiply the divisor (2) by the result in the first row, and write the product in the second row:

2 | 1  2  -5  -6
  ---
   1  2

5. Add the second row to the next coefficient in the first row, and write the sum in the third row:

2 | 1  2  -5  -6
  ---
   1  2 -3

6. Multiply the divisor by the result in the third row, and write the product in the fourth row:

2 | 1  2  -5  -6
  ---
   1  2 -3
       4

7. Add the fourth row to the next coefficient in the first row, and write the sum in the fifth row:

2 | 1  2  -5  -6
  ---
   1  2 -3
       4 -2

The final row gives us the coefficients of the quadratic factor: ax^2+bx+c = x^2 + 2x - 3. Therefore, the factorization of P(x) is

P(x) = (x-2)(x^2+2x-3).

To find the real solutions of the equation, we can use the quadratic formula or factor the quadratic further:

x^2 + 2x - 3 = (x+3)(x-1).

Therefore, the real solutions of the equation are x=2, x=-3, and x=1.

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Answer: The cooling of a body can be modeled using Newton's Law of Cooling, which states that the rate of cooling of an object is proportional to the temperature difference between the object and its surroundings. The equation for Newton's Law of Cooling is:

T(t) = T_0 + (T_s - T_0) * e^(-kt)

where T(t) is the temperature of the body at time t, T_0 is the initial temperature of the body, T_s is the temperature of the surroundings, k is the cooling constant, and e is the base of the natural logarithm.

Assuming that the temperature of the surroundings is constant at 68°F, we can use the given information to solve for t:

76.5°F = 68°F + (T_0 - 68°F) * e^(-kt)

Simplifying this equation, we get:

8.5°F = (T_0 - 68°F) * e^(-kt)

Taking the natural logarithm of both sides, we get:

ln(8.5°F / (T_0 - 68°F)) = -kt

Solving for t, we get:

t = -ln(8.5°F / (T_0 - 68°F)) / k

The cooling constant k depends on various factors such as the body's mass, the body's surface area, and the body's initial temperature. For a human body, k is typically estimated to be around 0.00087 per minute.

Assuming that the initial temperature of the body was 98.6°F (the average temperature of a living human body), we can plug in the values and solve for t:

t = -ln(8.5°F / (98.6°F - 68°F)) / 0.00087

t ≈ 16.5 hours

Therefore, it has been approximately 16.5 hours since the person died.

Step-by-step explanation:

Answer: it will take 20 min to type 350 words

105 words in 6 min

Step-by-step explanation:

Answer:

It will take 20 minutes to type 350 words.

In 6 minutes, 105 words can be typed.

Step-by-step explanation:

To find the time taken to type 350 words, divide 4 by 70 and then multiply it by 350.

         [tex]\sf \text{Time taken to type 1 word = $\dfrac{4}{70} $}\\\\\text{Time taken to type 350 words = $\dfrac{4}{70}*350$}[/tex]

                                                          = 20 minutes

To find the number of words to be typed in 6 minutes, first find how many he can type in 1 minute.

      Number of words typed in 4 minutes = 70 words

       [tex]\sf \text{Number of word typed in 1 minute = $\dfrac{70}{4}$}\\\\\text{Number of word typed in 6 minute = $\dfrac{70}{4}*6$}[/tex]

                                                               = 105 words

The joint distribution for (X,Y) is given by the table below, and the marginal distributions for X and Y are given by the tables below.

Y P(Y)

0 0

1 0.3686

2 0.0588

To determine the joint distribution for (X,Y), we need to calculate the probability of each possible outcome. There are 4 kings in the deck and 13 diamonds. We can use the formula for calculating probabilities of combinations to find the probabilities of each possible combination of kings and diamonds:

P(X = 0, Y = 0) = 36/52 * 35/51 = 0.5098

P(X = 0, Y = 1) = 36/52 * 16/51 = 0.2353

P(X = 0, Y = 2) = 36/52 * 1/51 = 0.0055

P(X = 1, Y = 0) = 16/52 * 36/51 = 0.2353

P(X = 1, Y = 1) = 16/52 * 15/51 = 0.0588

P(X = 1, Y = 2) = 16/52 * 0 = 0

P(X = 2, Y = 0) = 1/52 * 36/51 = 0.0055

P(X = 2, Y = 1) = 1/52 * 15/51 = 0.0007

P(X = 2, Y = 2) = 1/52 * 0 = 0

Therefore, the joint distribution for (X,Y) is:

To find the marginal distribution for X, we can sum the probabilities for each possible value of X:

P(X = 0) = 0.5098 + 0.2353 + 0.0055 = 0.7506

P(X = 1) = 0.2353 + 0.0588 + 0 = 0.2941

P(X = 2) = 0.0055 + 0.0007 + 0 = 0.0062

Therefore, the marginal distribution for X is:

To find the marginal distribution for Y, we can sum the probabilities for each possible value of Y:

P(Y = 0) = 0.5098 + 0.2353 + 0.0055 = 0.7506

P(Y = 1) = 0.2353 + 0.0588 + 0.0007 = 0.2948

P(Y = 2) = 0.0055 + 0 + 0 = 0.0055

Therefore, the marginal distribution for Y is:

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The equation that find the values of the table is y = 2x - 2.

Mrs Sanchez writes the following table of x and y values on the chalkboard. Therefore, let's find the equation that fits the values of the table.

using slope intercept form for linear equation,

y = mx + b

where

Hence,

m = -2 + 6 / 0 + 2

m = 4 / 2

m = 2

Therefore, lets' find the value of b, y intercepts using (0, -2)

Hence,

y = 2x + b

-2 = 2(0) + b

b = -2

Therefore, the equation is y = 2x -2

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This expression represents the change in the function values (f (x) - f (2)) divided by the change in the x-values (x - 2), which gives us the slope of the secant line between points P and Q.

The slope of the secant line through the points P (2, f (2)) and Q (x, f(x)) can be found using the slope formula:

slope = (f (x) - f (2))/ (x - 2)

This expression represents the change in y (f(x) - f (2)) divided by the change in x (x - 2) between the two points. It gives the average rate of change of the function over that interval.

Alternatively, we could use the point-slope form of a line to find the equation of the secant line through P and Q:

y - f(2) = slope(x - 2)

where slope is given by the expression above. This equation represents a line that passes through P and Q, and it can be used to approximate the behavior of the function between those points. As x gets closer to 2, the secant line becomes a better approximation of the tangent line to the curve at that point.

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★ Area of Semicircle:-

we have given Radius of Semicircle is 5.6 cm .

➺ Area = ½ π r²

➺ Area = ½ × 22/7 × 5.6²

➺ Area = ½ × 22/7 × 5.6 × 5.6

➺ Area = (22/2×7) × 5.6 × 5.6

➺ Area = 22/14 × 5.6 × 5.6

➺ Area = 11/7 × 5.6 × 5.6

➺ Area = (11 × 5.6 × 5.6/7)

➺ Area = (61.6 × 5.6/7)

➺ Area = (61.6 × 5.6/7)

➺ Area = 344.96/7

➺ Area = 49.28 cm

★ Perimeter of Semicircle:-

➺ Perimeter = πr + 2r

➺ Perimeter = 22/7 × 5.6 + 2 × 5.6

➺ Perimeter =( 22× 5.6/7 ) + 2 × 5.6

➺ Perimeter =123.2/7 + 2 × 5.6

➺ Perimeter =123.2/7 + 11.2

➺ Perimeter =123.2 + 78.4 / 7

➺ Perimeter =201.6/7

➺ Perimeter =28.8 cm

★ Therefore:-

Step-by-step explanation:

the area of a circle is

pi×r²

and of a half-circle (= half of a circle)

pi×r²/2

the area here is therefore

pi×5.6²/2 = pi×31.36/2= 15.68pi = 49.26017281... cm²

the perimeter is the sum of half of the circle's circumference plus the diameter (2×radius).

the circumference of a circle is

2×pi×r

and half of that is

2×pi×r/2 = pi×r

in our case that is

pi×5.6 = 17.59291886... cm

the full perimeter is then

17.59291886... + 2×5.6 = 28.79291886... cm

C is open and neither closed nor open. C is not compact.

a. A = [-1, 1]

int(A) = (-1, 1), bd(A) = {-1, 1}, A' = [-1, 1], cl(A) = [-1, 1]

A is closed and neither open nor closed. A is compact.

b. B = {(-1)^n + h : n ∈ N}

int(B) = ∅, bd(B) = B, B' = {-1, 1}, cl(B) = B ∪ {-1, 1}

B is closed and neither open nor closed. B is not compact.

c. C = {r ∈ Q+ : r^2 < 4}

int(C) = {r ∈ Q+ : r^2 < 4}, bd(C) = {r ∈ Q+ : r^2 = 4}, C' = {r ∈ R+ : r^2 ≤ 4}, cl(C) = {r ∈ R+ : r^2 ≤ 4}

C is open and neither closed nor open. C is not compact.

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The solution is, the solutions using the Zero Product Property: is x = 7 and -2.

The expression to be solved is:

x² - 5x - 14 = 0

we know that,

The zero product property states that the solution to this equation is the values of each term equals to 0.

now, we have,

x² - 5x - 14 = 0

or, x² - 7x + 2x - 14 = 0

or, (x-7) (x + 2) = 0

so, using the Zero Product Property:

we get,

(x-7) = 0

or,

(x + 2) = 0

so, we have,

x = 7 or, x = -2

The answers are 7 and -2.

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Answer:

o

Step-by-step explanation:

The assumption that P(Xi < 6) ≥ d for some 8 € (0, 1), we can show that Var(Xi) ≤ 6^2 - (6d)^

(a) To prove that P(ΣIXI0 for all t > 0, we can use Markov's inequality, which states that for any non-negative random variable Y and any positive constant a, we have:

P(Y ≥ a) ≤ E(Y)/a

Let Y = e^(tΣIXi) and a = e^t. Then we have:

P(ΣIXi ≥ t) = P(e^(tΣIXi) ≥ e^t) ≤ E(e^(tΣIXi))/e^t

Now, we need to show that E(e^(tΣIXi)) ≤ e^(t^2/2). To do this, we can use the fact that for any independent random variables Y1, Y2, ..., Yn, we have:

E(e^(t(Y1+Y2+...+Yn))) = E(e^(tY1)) E(e^(tY2)) ... E(e^(tYn))

Uszng this formula and the assumption that P(Xi < 6) ≤ 6 for all 6 € (0, 1), we get:

E(e^(tXi)) = ∫₀^₆ e^(tx) fXi(x) dx ≤ ∫₀^₆ e^(6t) fXi(x) dx = e^(6t) E(Xi)

Therefore, we have:

E(e^(tΣIXi)) = E(e^(tX1) e^(tX2) ... e^(tXn)) ≤ E(e^(6t)X1) E(e^(6t)X2) ... E(e^(6t)Xn) = (E(X1) e^(6t))^(n)

Since Xi is non-negative, we have E(Xi) = ∫₀^₆ fXi(x) dx ≤ 1, so we get:

E(e^(tΣIXi)) ≤ (e^(6t))^n = e^(6nt)

Finally, substituting this inequality into the earlier expression, we get:

P(ΣIXi ≥ t) ≤ E(e^(tΣIXi))/e^t ≤ (e^(6nt))/e^t = e^(6n-1)t

Since this inequality holds for all t > 0, we have:

P(ΣIXi ≥ 0) = lim t→0 P(ΣIXi ≥ t) ≤ lim t→0 e^(6n-1)t = 1

Therefore, we have shown that P(ΣIXi ≥ 0, as required.

(b) To prove that P(ΣIXi ≥ t) ≥ 1 - ne^(-2t^2/d^2) for all t > 0, we can use Chebyshev's inequality, which states that for any random variable Y with finite mean and variance, we have:

P(|Y - E(Y)| ≥ a) ≤ Var(Y)/a^2

Let Y = ΣIXi and a = t. Then we have:

P(|ΣIXi - E(ΣIXi)| ≥ t) ≤ Var(ΣIXi)/t^2

Now, we need to find an upper bound for Var(ΣIXi). Since the Xi are independent, we have:

Var(ΣIXi) = Var(X1) + Var(X2) + ... + Var(Xn)

Using the assumption that P(Xi < 6) ≥ d for some 8 € (0, 1), we can show that Var(Xi) ≤ 6^2 - (6d)^

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Answer:

Assuming that the distribution of section scores is still approximately normal with a mean of 500 and a standard deviation of 100, we can use the empirical rule (also known as the 68-95-99.7 rule) to estimate the probability that a randomly-selected student gets a section score of 700 or better.

According to the empirical rule, approximately 68% of the scores fall within one standard deviation of the mean, approximately 95% of the scores fall within two standard deviations of the mean, and approximately 99.7% of the scores fall within three standard deviations of the mean.

To estimate the probability of getting a section score of 700 or better, we need to find the proportion of scores that are more than two standard deviations above the mean.

Z-score = (X - μ) / σ = (700 - 500) / 100 = 2

From the standard normal distribution table, we find that the proportion of scores that are more than 2 standard deviations above the mean is approximately 0.0228.

Therefore, the estimated probability that a randomly-selected student gets a section score of 700 or better is about 0.0228, or 2.28%.

Step-by-step explanation:

The answer is (d) none of these.

For the differential equation (2D^2 + 12D + 2)y = 0,

The characteristic equation is: 2r^2 + 12r + 2 = 0

Solving this quadratic equation using the quadratic formula, we get:

r = (-12 ± sqrt(12^2 - 4(2)(2))) / (2(2))

r = (-6 ± sqrt(32)) / 2

r = -3 ± sqrt(8)

The roots of the characteristic equation are complex conjugates, which means that the solution to the differential equation will be of the form:

y = e^(-3x) (c1 cos(sqrt(8)x) + c2 sin(sqrt(8)x))

The damping ratio is given by:

ζ = (c * n) / (2 * sqrt(a))

where c is the damping coefficient, n is the natural frequency, and a is the coefficient of the second derivative term.

In this case, c = 12, n = sqrt(8), and a = 2. Substituting these values into the above formula, we get:

ζ = (12 * sqrt(8)) / (2 * sqrt(2))

ζ = 6

Since the damping ratio ζ is greater than 1, the system is overdamped.

Therefore, the answer is (a) Overdamping.

For the differential equation (3D^2 + 6D + 7)y = sin(x),

The characteristic equation is: 3r^2 + 6r + 7 = 0

Using the quadratic formula, we can see that the roots of the characteristic equation are complex conjugates, which means that the solution to the differential equation will be of the form:

y = e^(-3x) (c1 cos(sqrt(2)x) + c2 sin(sqrt(2)x))

Since the real part of the roots of the characteristic equation is negative, the system is stable

However, the right-hand side of the differential equation is not of the form that matches with the solution, which means that the system is not able to respond to the input sin(x).

Therefore, the answer is (d) none of these.

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a. The division of (x³ - 27/9 - x²) by (x² + 3x + 9/x² + 9x + 18) is x - 3.

b. The solution to the equation √3x + 2 - 2√x = 0 is 1/3.

c. The solution to the equation 3x⁷ - 24x⁴ = 0 is 0 or 2√2/3.

For part (a), we first factorize the denominator and simplify the numerator. Then, we use long division to divide the numerator by the denominator, resulting in a quotient and a remainder.

For part (b), we can simplify the equation by squaring both sides, rearranging, and then substituting y = √x. This results in a quadratic equation, which can be easily solved.

For part (c), we factorize the equation by taking out the common factor of 3x⁴. This results in a simpler equation, which can be solved by setting each factor equal to zero.

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The estimated total sales after 11 months is approximately 235.54 thousand video games. To find and in the given equation for total sales, The equation is: total sales = 89 + 45ln(number of months since release) We can see that the coefficient of the natural logarithm function is 45.

So, we have: 45 = k where k is the growth rate of the video game sales. Now, to estimate the total sales after 11 months, we need to substitute 11 for in the equation: total sales = 89 + 45ln(11) Using a calculator, we get: total sales ≈ 235.54 Rounding to the nearest hundredth, we get: total sales ≈ 235.54 thousand.

So, the estimated total sales after 11 months is approximately 235.54 thousand video games.

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The exponential function that represents the graph is given as follow:

y = 2^(x - 1) + 2.

An exponential function has the definition presented as follows:

y = ab^x.

In which the parameters are given as follows:

The function in this problem has a horizontal asymptote at y = 2, hence:

y = ab^x + 2.

When x increases by one, y is multiplied by two, hence the parameters a and b can given as follows:

a = 1, b = 2.

The function is translated one unit right, hence it is defined as follows:

y = 2^(x - 1) + 2.

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The mean of the data set is 9.33 minutes.

To find mean of the data set, we will add all the values and divide by the total number of values.

In this case, the sum of the values is:

= 0 + 2 + 4 + 6 + 8 + 10 + 12 + 14 + 16 + 18 + 20 + 22

= 112

There are 12 values in the data set, so the mean is:

= Sum of values / Total number of values

= 112 / 12

= 9.3333

= 9.33 minutes.

Therefore, the mean of the data set is 9.33 minutes.

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The probability that more than 40% of 100 randomly selected physicians were sued is about 10%. Therefore, the answer is b. About 10%.

To determine the probability that more than 40% of 100 randomly selected physicians were sued, we need to find the mean and standard deviation of the sampling distribution and then use the z-score to find the probability.

1. Find the mean (µ) and standard deviation (σ) of the sampling distribution:
µ = p = 0.34 (the proportion of physicians sued for malpractice)
q = 1 - p = 0.66 (the proportion of physicians not sued for malpractice)
n = 100 (sample size)

[tex]Standard deviation (σ) = \sqrt{\frac{pq}{n} }  = \sqrt{\frac{(0.34)(0.66)}{100} } = 0.047[/tex]

2. Calculate the z-score for the desired proportion (40% or 0.40):
[tex]z = \frac{X-µ}{σ}  = \frac{0.40-0.34}{0.047} = 1.28[/tex]

3. Use a z-table or calculator to find the probability associated with the z-score:
P(Z > 1.28) =0.100 (rounded to three decimal places)

The probability that more than 40% of 100 randomly selected physicians were sued is about 10%. Therefore, the answer is b. About 10%.

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If the money had been shared after Sarah's 7th birthday instead of now, she would have received an additional $12.95 because her share would have been increased from $54 to $66.95 based on the new age ratio of 8:7:4.

At present, James, Sarah, and Lucy have received $72, $54, and $36 respectively based on their age ratios of 8:6:4. If Sarah's birthday is in three weeks, then she would have turned 7 by then. So, the new age ratio would be 8:7:4. The total amount of money to be shared remains $180.

Therefore, the total parts for the new ratio are 8+7+4 = 19 parts.

The new share for Sarah is

(7/19) * $180 = $66.95 (rounded to the nearest cent)

So, if the money had been shared after Sarah's birthday, she would have received an additional $66.95 - $54 = $12.95.

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The relation "a-b a mod 4 = b mod 4" means that for any two numbers a and b, if their difference is divisible by 4, then they belong to the same equivalence class. To find the equivalence class of -, we need to find all the numbers that have the same modulus as - when divided by 4.

We can start by listing out some numbers with the same modulus as -. For example, we have {-9, -5, -1, 3, 7, ...}, since these numbers are all congruent to -1 mod 4. Similarly, we have {0, 4, 8, 12, ...} for numbers that are congruent to 0 mod 4, and {1, 5, 9, 13, ...} for numbers that are congruent to 1 mod 4.

Therefore, the equivalence class of - is {-9, -5, -1, 3, 7, ...}, which contains all the negative numbers that are congruent to -1 mod 4.

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6 The probabilities of both questions are a.1/20, and b.9/20.

(a) To find the probability that both David and Mary hit the target, we can use the formula for independent events: P(A and B) = P(A) x P(B).

So, P(David hits the target) = 1/5, and P(Mary hits the target) = 1/4.

Therefore, P(both hit the target) = (1/5) x (1/4) = 1/20.

(b) To find the probability that the target will be hit at least once, we can use the formula P(A or B) = P(A) + P(B) - P(A and B).

So, P(David hits the target) = 1/5, and P(Mary hits the target) = 1/4.

Therefore, P(at least one hits the target) = P(David hits the target) + P(Mary hits the target) - P(both hit the target) = (1/5) + (1/4) - (1/20) = 9/20.

7. The probabilities of both questions are a.0.0625, and b.0.0588.

(a) If the first card is replaced, the probability of drawing a Heart on the first card is 13/52 (since there are 13 Hearts in a deck of 52 cards). After the first card is drawn and replaced, there are still 52 cards in the deck, with 13 of them being Hearts.

So, the probability of drawing a Heart on the second card is also 13/52.

Therefore, the probability of drawing two Hearts with replacement is (13/52) x (13/52) = 169/2704, which simplifies to 0.0625 (correct to 4 decimal places).

(b) If the first card is not replaced, the probability of drawing a Heart on the first card is 13/52 (since there are 13 Hearts in a deck of 52 cards). After the first card is drawn and not replaced, there are now only 51 cards left in the deck, with 12 of them being Hearts.

So, the probability of drawing a Heart on the second card is 12/51.

Therefore, the probability of drawing two Hearts without replacement is (13/52) x (12/51) = 156/2652, which simplifies to 0.0588 (correct to 4 decimal places).

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The equation of the line that passes through the points (-7,5) and (0,7) is equals to [tex] y = \frac{2}{7} x + 7 [/tex] and in point-slope form 7( y - 5) = 2( x +7).

The equation of a straight line is y = mx+ c, where, m is slope of line

Point-slope form of equation of line is written as y – y₁ = m(x – x₁), where

We have a line that passes through the points say A(-7,5) and B(0,7). We have to write an equation of line in point-slope form. Now, slope of line, [tex]m = \frac{ y_2 - y_1}{x_2- x_1}[/tex]

here, x₁ = -7, y₁ = 5, x₂ = 0, y₂ = 7

=> [tex]m = \frac{ 7 - 5}{0 + 7}[/tex]

[tex]= \frac{2}{7}[/tex]

Using the point slope equation of a line passes through A(-7,5) and B(0,7) is y – y₁ = m(x – x₁).

Substitute all known values, [tex]y - 5 = \frac{2}{7}( x + 7) [/tex]

Cross multiplication, 7( y - 5) = 2( x +7)

=> 7y - 35 = 2x + 14

=> 7y = 2x + 14 + 35

=> 7y = 2x + 49

=> [tex] y = \frac{2}{7} x + 7 [/tex]

Hence, required equation is [tex] y = \frac{2}{7} x + 7 [/tex] but in point slope form 7( y - 5) = 2( x +7).

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The surface area of the pyramid is 186 cm².

Given that the net diagram of a square pyramid, we need to find the surface area of the same,

SA = a² + 2al

a = side length, l = height

SA = 6² + 2×6×12.5

= 186 cm²

Hence, the surface area of the pyramid is 186 cm².

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Answer:

A

Step-by-step explanation:

Yes, given the conditions provided, a, b, and c are conditionally independent given d. Conditional independence means that the probability distribution of any one of the variables is independent of the others when the conditioning variable is known.

In this case, you have the following conditional independence relationships:

1. a and b are conditionally independent given d.
2. a and c are conditionally independent given d.
3. b and c are conditionally independent given d.

To show that a, b, and c are conditionally independent given d, we need to demonstrate that the joint probability distribution of a, b, and c given d can be factored into the product of their individual conditional probability distributions.

P(a, b, c | d) = P(a | d) * P(b | d) * P(c | d)

From the given relationships, we can infer the following:

P(a, b | d) = P(a | d) * P(b | d)
P(a, c | d) = P(a | d) * P(c | d)
P(b, c | d) = P(b | d) * P(c | d)

Now, we can substitute the individual conditional probabilities from the given relationships into the expression for the joint probability distribution:

P(a, b, c | d) = P(a | d) * P(b | d) * P(c | d)

Since the joint probability distribution of a, b, and c given d can be factored into the product of their individual conditional probability distributions, a, b, and c are conditionally independent given d.

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