the data set monarch from computer-active data analysis by lunn and mcneil (1991) contains the years lived after inauguration, election, or coronation of u.s. presidents, popes, and british monarchs from 1690 to roughly the present (nixon, carter, reagan, etc., are not included). do the groups differ? the stats output is

For an independent-measures t statistic, the statement "the estimated standard error measures how much difference is reasonable to expect between the two sample means if the null hypothesis is true" is True.

Your answer: True. The estimated standard error in an independent-measures t statistic indeed measures the reasonable difference between the two sample means, assuming the null hypothesis is true. This value helps to determine if the observed difference in means is significantly different from what is expected by chance alone.

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The function that represents the number of minutes Alejandro drove to reach mile marker m is f(m) = 4(m - 136).

The function that represents the number of minutes Alejandro drove to reach mile marker m on his route is:
f(m) = 4(m - 136)
This is because he drove at a constant speed, so the time it took to reach each mile marker was the same. From the table, we can see that he drove 5 miles in 4 minutes, so his speed was 5/4 miles per minute. Using this speed, we can write the equation:
distance = rate x time
where distance is (m - 136) miles (the distance from his starting point to the mile marker m), rate is 5/4 miles per minute, and time is the number of minutes it took to drive that distance.
Solving for time, we get:
time = distance / rate = (m - 136) / (5/4) = 4(m - 136)

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The directional derivative at P in the direction of Q is (0,4) dot (2/√5,1/√5) = 4/√5.

To determine the rate of change of the function at point P(0,1) when moving in the direction of point Q(2,2), we need to calculate the directional derivative of the function at P in the direction of Q. The directional derivative is the dot product of the gradient of the function at P and the unit vector in the direction of Q.

The gradient of the function is given by ∇f(x,y) = (3e^(3x)LN(2y^2-1), 4ye^(3x)/(2y^2-1)), so at point P(0,1), the gradient is (0, 4e^0/1) = (0, 4).

The unit vector in the direction of Q is (2-0)/sqrt((2-0)^2+(2-1)^2), (2-1)/sqrt((2-0)^2+(2-1)^2) = (2/√5,1/√5).

Therefore, the directional derivative at P in the direction of Q is (0,4) dot (2/√5,1/√5) = 4/√5.

To determine the direction to move from P(0,1) for the maximum rate of decrease in the function, we need to move in the direction opposite to the gradient. At point P, the gradient is (0,4), so the direction of maximum decrease is in the opposite direction, which is (0,-1) or straight down.

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The situation you are describing, in which the value of the solution may be made infinitely large in a maximization linear programming problem or infinitely small in a minimization problem without violating any constraints, is known as (b) unbounded.

In linear programming, unboundedness occurs when there is no upper limit on the value of the objective function in a maximization problem or no lower limit in a minimization problem. This happens because the feasible region (i.e., the set of points that satisfy all the constraints) extends indefinitely in the direction that improves the objective function value.

To better understand this concept, let's break it down step-by-step:

1. Linear programming problems involve an objective function (which needs to be maximized or minimized) and a set of constraints.
2. The feasible region is formed by the intersection of all constraint boundaries and represents the solution space where all constraints are satisfied.
3. If the feasible region is unbounded, it means that there is no limit to the value of the objective function in the direction of optimization.
4. For a maximization problem, unboundedness means the solution value can be increased infinitely, while for a minimization problem, it can be decreased infinitely without violating any constraints.

It's important to note that unboundedness is not the same as infeasibility, semi-optimality, or infiniteness. Infeasibility occurs when there are no solutions that satisfy all constraints, semi-optimality refers to a situation where the optimal solution lies at the boundary of the feasible region, and infiniteness is not a standard term used in linear programming.

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The profit at a sales level of 10 trees can be found by substituting x = 10 into the profit function P(x) = 20x - 0.0122 - 100.

b) To find the profit at a sales level of 10 trees, substitute x = 10 into the profit function P(x) = 20x - 0.0122 - 100. Simplify the expression to obtain the profit value, rounding it to the nearest cent.

To find the profit at a sales level of 10 trees, we substitute x = 10 into the profit function P(x) = 20x - 0.0122 - 100:

P(10) = 20(10) - 0.0122 - 100

P(10) = 200 - 0.0122 - 100

P(10) = 99.9878 (rounded to the nearest cent)

The profit at a sales level of 10 trees is approximately $99.99. This means that selling 10 palm trees will result in a profit of approximately $99.99.

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Answer:

B

Step-by-step explanation:

the median is the middle value of the data set arranged in ascending order.

the stem and leaf diagram shows the data in ascending order.

there are 21 items of data from lowest 50 to highest 99

the middle value for 21 items is 10- 1- 10

that is the 11th item

counting from 50 the median is then 86

The complex partial fraction for the rational functions are: 16/(z⁴+4) = (-4i/√2)/(z² + 2i) + (4i/√2)/(z² - 2i)

To find the complex partial fractions, we first factor the denominator as follows:

z⁴ + 4 = (z² + 2i)(z² - 2i)

Then we can write the rational function as:

16/(z⁴ + 4) = A/(z² + 2i) + B/(z² - 2i)

where A and B are constants to be determined.

We now need to find the values of A and B. To do this, we multiply both sides of the equation by the common denominator (z⁴ + 4), which gives:

16 = A(z² - 2i) + B(z² + 2i)

We can now substitute z = i√2 into this equation, which gives:

16 = A(-2) + B(2i√2)

Solving for A, we get:

A = -4i/√2

Similarly, substituting z = -i√2 gives:

A = 4i/√2

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The steps for writing the equation of this cubic polynomial function involve, substituting given points in f(x) = k(x - a)²(x - b) and taking derivative.

If a cubic polynomial function has the same zeroes, it means that it has a repeated root. Let's say that the repeated root is "a". Then, the function can be written in the form:

f(x) = k(x - a)²(x - b)

Where "k" is a constant and "b" is the other root. However, we still need to determine the values of "k" and "b".

To do this, we can use the fact that the function passes through the coordinate (0, -5). Plugging in x = 0 and y = -5 into the equation, we get:

-5 = k(a)²(b)

We also know that "a" is a repeated root, which means that the derivative of the function at "a" is equal to zero:

f'(a) = 0

Taking the derivative of the function, we get:

f'(x) = 3kx² - 2akx - ak²

Setting x = a and f'(a) = 0, we get:

3ka² - 2a²k - ak² = 0

Simplifying this equation, we get:

a = 3k

Substituting this into the equation -5 = k(a)²(b), we get:

-5 = k(3k)²(b)

Simplifying this equation, we get:

b = -5 / (9k²)

Now we know the values of "k" and "b", and we can write the cubic polynomial function:

f(x) = k(x - a)²(x - b)

Substituting the values of "a" and "b", we get:

f(x) = k(x - 3k)²(x + 5 / 9k²)

Therefore, this is the equation of the cubic polynomial function that has the same zeroes and passes through the coordinate (0, -5).

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If Leg 1 is 2 leg 2 is 2 then the hypotenuse of the triangle is 2.828.

Using Pythagoras theorem to find the hypotenuse c of the right angled triangle with base b and height a,

c² = a² + b²

In this case, leg 1 and leg 2 have lengths of 2, so we can substitute,

c² = 2² + 2²

c² = 4 + 4

c² = 8

c = √(8)

We can simplify this by factoring out a 2 from the square root,

c = √(4 x 2)

c = √(4) x √(2)

c = 2 x √(2)

c = 2.828

Hence the hypotenuse is found to be 2.828.

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Based on the given information, there is convincing evidence of a difference in the proportions of households with and without school-aged children that would support starting the school year a week earlier.

Based on the 90% confidence interval given, which ranges from 0.03 to 0.36, there is convincing evidence of a difference in the true proportions of households that would support starting the school year a week earlier, between those with school-aged children and those without. This is because the interval does not include 0, which suggests that the difference is statistically significant. However, it's important to note that this conclusion is based on the specific confidence level of 90%. If a different confidence level was used, the interval could potentially contain 0, indicating that there may not be a significant difference. Therefore, it's important to consider the level of confidence when interpreting the results. Additionally, the fact that different sample sizes were used could potentially impact the validity of the results. It's generally preferred to have equal sample sizes in order to increase the accuracy of the comparison. However, in this case, the difference in sample sizes does not necessarily invalidate the results, but it should still be taken into consideration.

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Since ln() = ∞ this integral divergent. Therefore, by the integral test, the series ∑ 1/n^2+1 also diverges.

To show that the series ∑(1/n^2 + 1) converges using the integral test, follow these steps:

1. Define the function: Let f(x) = 1/x^2 + 1.

2. Confirm that f(x) is positive, continuous, and decreasing on the interval [1, ∞).

  - Positive: Since x^2 is always non-negative, x^2 + 1 is always greater than 0. Thus, f(x) is positive.
  - Continuous: The function f(x) is a rational function and is continuous for all real values of x.
  - Decreasing: The derivative of f(x) is f'(x) = -2x/(x^2 + 1)^2. Since the numerator is negative and the denominator is positive, f'(x) is always negative for x > 0. Therefore, f(x) is decreasing.

3. Evaluate the integral: Now, we will evaluate the integral of f(x) from 1 to ∞ to determine whether it converges or diverges:

  ∫(1/x^2 + 1) dx from 1 to ∞

4. Use substitution: Let u = x^2 + 1, so du = 2x dx. Then, the limits of integration become 2 to ∞, and the integral becomes:

  (1/2)∫(1/(u-1)) du from 2 to ∞

5. Solve the integral: The antiderivative of 1/(u-1) is ln|u-1|. So, we have:

  (1/2)[ln|u-1|] evaluated from 2 to ∞

6. Evaluate the limit: Taking the limit as the upper bound goes to infinity, we get:
∫1 to ∞ 1/x^2+1 dx

To do this, we can use the substitution u = x^2+1:

∫1 to ∞ 1/x^2+1 dx = (1/2) ∫1 to ∞ 1/u du

= (1/2) ln|u| from 1 to ∞

= (1/2) ln(∞) - (1/2) ln(2)

Since ln(∞) = ∞, this integral diverges. Therefore, by the integral test, the series ∑ 1/n^2+1 also diverges.
Since the integral diverges, this indicates that the original series ∑(1/n^2 + 1) also diverges. However, we made a mistake in the problem statement; the series should have been ∑(1/n^2) instead of ∑(1/n^2 + 1). If you need help proving that the series ∑(1/n^2) converges using the integral test.

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According to the formula for the area of a rectangle, which is A = l x w, where A is the area, l is the length, and w is the width. The length of the rectangle is 12 feet and the width is 8 feet.

To solve this problem, we can use the formula for the area of a rectangle, which is A = l x w, where A is the area, l is the length, and w is the width.

We know that the area of the rectangle is 96 ft^2, so we can plug that in for A:

96 = l x w

We also know that the width is 4 feet less than the length, so we can write:

w = l - 4

Now we can substitute this expression for w into our equation for the area:

96 = l x (l - 4)

Expanding the right side, we get:

96 = l^2 - 4l

Rearranging this equation, we get a quadratic equation in standard form:

l^2 - 4l - 96 = 0

We can solve this equation by factoring or using the quadratic formula, but in this case, it's easier to factor:

(l - 12)(l + 8) = 0

This gives us two possible values for l: l = 12 or l = -8. Since the length of a rectangle can't be negative, we discard the second solution and conclude that the length of the rectangle is 12 feet.

To find the width, we can use the equation we had earlier:

w = l - 4

Substituting l = 12, we get:

w = 12 - 4 = 8

Therefore, the length of the rectangle is 12 feet and the width is 8 feet.

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The probability of winning at least one award is 1 - 0.2373 = 0.7627 or 76.27%.

If the probability of winning an MTV music award after being nominated is 25%, the probability of not winning is 75%. Thus, the probability of not winning any of the five awards is (0.75)^5 = 0.2373.

As for how many awards Ariana Grande should expect to win, we can use the expected value formula: E(x) = n * p, where n is the number of trials (in this case, 5) and p is the probability of success (0.25). Therefore, E(x) = 5 * 0.25 = 1.25. So, Ariana Grande can expect to win about 1 award.

Finally, to calculate the standard deviation associated with this probability, we can use the formula: σ = sqrt(n * p * (1-p)). Plugging in the values, we get σ = sqrt(5 * 0.25 * 0.75) = 0.866. Therefore, the standard deviation associated with this probability is approximately 0.866.

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The Wason task is a classic problem in cognitive psychology that involves conditional reasoning. In the version of the task that you mentioned, participants are given the following information:

"If a person is drinking alcohol, then they must be at least 21 years old." They are then presented with four cards that show a person's age on one side and whether or not they are drinking alcohol on the other side. The task is to determine which cards need to be flipped over to test the conditional rule.

Research has shown that people perform better on the Wason task when it is presented in a meaningful context, such as the one you described involving age and drinking alcohol, rather than using abstract symbols or letters and numbers. This is because the meaningful context helps people to better understand and remember the conditional rule being tested. When the task is presented in terms of letters and numbers, it can be more difficult for people to make sense of the information and apply the conditional rule correctly.

Additionally, using a meaningful context can make the task more relevant and engaging to participants, which can improve their motivation and performance. Overall, presenting the Wason task with examples rather than letters and numbers can help to make the task more accessible and easier to understand for participants.

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The value of C from the column value table is C = 40

Given data ,

Let the table be represented as T

where ,

6 B D

10 25 35

A C 56

Now , the ratio of the table values is r = 35 / 56

r = 5 / 8

So , from the proportion , the value of C is

25 = ( 5/8 ) C

Multiply by 8 on both sides , we get

5C = 200

Divide by 5 on both sides ,we get

C = 40

Hence , the proportion is solved and C = 40

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a. The median age in the study is  6 years.

b. The mean age in the study is 10.9 years.

(a) To find the median age, we need to find the age at which 50% of the children are younger and 50% are older. Adding up the percentages provided in increasing order of age until the total just exceeds 50%, we have:

7% (age 3) + 19% (age 4) + 17% (age 5) + 39% (age 6) = 82%

This means that 82% of the children are three, four, five, or six years old. To find the median age, we need to find the age at which 41 out of the 175 children (50% of 175) are younger and 134 are older. Since 82% of the children are younger than age 7, and 7 is the oldest age group listed, we know that the median age is age 6.

Therefore, the median age in the study is 6 years.

(b) To find the mean age, we can use the formula:

mean = (sum of values) / (number of values)

We can calculate the sum of values by multiplying each age by the number of children with that age, and adding up the results:

(12 x 3) + (33 x 4) + (29 x 5) + (69 x 6) + (32 x 7) = 1902

So the sum of values is 1902.

The number of values is the total number of children in the sample, which is 175.

Therefore, the mean age is:

mean = 1902 / 175 ≈ 10.9

Rounding to one decimal place, the mean age in the study is 10.9 years.

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David is completing a Rorschach test, which is a type of projective psychological assessment. The test consists of a series of inkblots presented to the participant, and their responses are analyzed by the researcher to gain insights into their personality, thought processes, and emotional functioning.

The Rorschach test is a widely used tool in clinical psychology and has been subject to much controversy and debate over its validity and usefulness in assessment.

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To find a model that expresses the revenue R as a function of p, we need to use the formula for revenue, which is R = p*x. Substituting the demand equation x=-5p+200, we get R = p*(-5p+200), which simplifies to R = -5p^2 + 200p.

Therefore, the revenue R is a quadratic function of the price p. This means that as the price of the product increases, the revenue initially increases, reaches a maximum value, and then starts to decrease.

To maximize the revenue, we can take the derivative of the revenue function with respect to p and set it equal to zero. So, dR/dp = -10p + 200 = 0, which gives p = 20. Substituting this value of p into the revenue function, we get R = -5(20)^2 + 200(20) = 2000.

Therefore, the maximum revenue that can be generated from selling the product is $2000, when the price of the product is $20. It is important to note that this is only a theoretical maximum, and in practice, other factors such as competition and consumer behavior may affect the actual revenue generated.

In conclusion, by using the demand equation and the formula for revenue, we were able to find a model that expresses the revenue R as a function of p, which is R = -5p^2 + 200p. We also found the price that maximizes the revenue, which is $20.

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A 95% confidence interval for the mean length of the slide pins  is (3.03, 3.27).

We are given:

sample size, n = 16

sample mean, x = 3.15

sample standard deviation, s = 0.2

confidence level, C = 95%

Since the sample size is less than 30, we use a t-distribution with n-1 degrees of freedom.

The formula for the confidence interval for the population mean is:

x ± tα/2 * s/√n

where tα/2 is the t-score with (n-1) degrees of freedom for the given confidence level and √n is the square root of the sample size.

Substituting the given values, we get:

Lower limit = x - tα/2 * s/√n

Upper limit = x + tα/2 * s/√n

From the t-distribution table with 15 degrees of freedom and a 95% confidence level, we find that the t-score is approximately 2.131.

Substituting the values, we get:

Lower limit = 3.15 - 2.131 * 0.2/√16 = 3.03

Upper limit = 3.15 + 2.131 * 0.2/√16 = 3.27

Therefore, the 95% confidence interval for the mean length of the slide pins is (3.03, 3.27).

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Answer:A

Step-by-step explanation:

Answer:

3/7

Step-by-step explanation:

Total spins: 9 + 7 + 5 = 21

Number of times landing on orange: 9

p(orange) = 9/21 = 3/7

Answer: 3/7

If  a random variable T is Exponential with u = 102 then the probability that T is less than or equal to 153 is 0.632

If T is an exponential random variable with parameter u, then the probability density function of T is given by:

[tex]f(t) = (1/u) \times e^(^-^t^/^u^)[/tex] for t ≥ 0

The cumulative distribution function (CDF) of T is given by:

F(t) = P(T ≤ t)

= ∫[0, t] f(x) dx

[tex]= 1 - e^(^-^t^/^u^)[/tex] for t ≥ 0

In this case, we are given that T is Exponential with u = 102.

To find P(T ≤ 153), we can use the CDF formula with t = 153:

P(T ≤ 153) = F(153)

= [tex]1 - e^(^-^1^5^3^/^1^0^2^)[/tex]

P(T ≤ 153) = 0.632

Therefore, the probability that T is less than or equal to 153 is 0.632.

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102 Degrees

Angle A and Angle B are supplementary to each other.

Angle A measure = 78 degrees

Find Angle B

We know that in a supplementary relationship between two angles, the sum of both of the angles are equal to 180 degrees.

Here we know that Angle A  = 78 degrees

Angle B = 180 - Angle A = 180 - 78 = 102 degrees.

Area is 0.9306. To find the area under the standard normal curve to the right of z=−1.48, we need to use a table or calculator that gives us the cumulative probability for a standard normal distribution.

The standard normal curve is a bell-shaped curve with a mean of 0 and a standard deviation of 1. The area under the curve represents the probability of a random variable falling within a certain range of values.

Using a standard normal table or calculator, we can find that the cumulative probability for z=−1.48 is 0.0694. This means that 6.94% of the total area under the standard normal curve is to the left of z=−1.48.

To find the area to the right of z=−1.48, we subtract this value from 1: 1 - 0.0694 = 0.9306. Therefore, the area under the standard normal curve to the right of z=−1.48 is 0.9306.

We can check this answer by graphing the standard normal curve and shading in the area to the right of z=−1.48. The shaded area should be approximately 0.9306 of the total area under the curve.

In summary, to find the area under the standard normal curve to the right of z=−1.48, we used the cumulative probability for a standard normal distribution to find the probability of a random variable falling within a certain range of values. We then subtracted this probability from 1 to find the area to the right of z=−1.48. The resulting area is 0.9306.

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Therefore, there are 12,650 distinct tetrahedra that can be formed using the given 25 points.

To form a tetrahedron using the given 25 points, we need to select 4 points from the total of 25. Since the order in which the points are selected does not matter, we can use the combination formula to calculate the number of ways to choose 4 points out of 25.

The combination formula is:

C(n, r) = n! / (r! * (n - r)!)

where n is the total number of items and r is the number of items to be selected.

In this case, we have 25 points and we want to select 4 points to form a tetrahedron. So we can plug these values into the combination formula as follows:

C(25, 4) = 25! / (4! * (25 - 4)!)

= (25 * 24 * 23 * 22 * 21!) / (4 * 3 * 2 * 1 * 21!)

= (25 * 24 * 23 * 22) / (4 * 3 * 2 * 1)

= 12,650

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Answer:

45.5

Step-by-step explanation:

i passed

For the function f(x) = (x + 6)°, there are no critical numbers and no relative maxima or minima. The function is an increasing function for all values of x, and it has a global minimum at x = -6.

To find the critical numbers for the function f(x) = (x + 6)°, we need to set its first derivative equal to zero and solve for x. So,
f(x) = (x + 6)°
f'(x) = 1
Setting f'(x) = 0 gives us no solutions, which means that there are no critical numbers for this function.
Since there are no critical numbers, we cannot use the second-derivative test or the first derivative test to decide whether the critical numbers lead to relative maxima or relative minima. However, we can still determine the nature of the function by looking at its graph or by analyzing its behavior for different values of x.
From the function f(x) = (x + 6)°, we can see that it is an increasing function for all values of x. Therefore, there are no relative maxima or minima for this function. In fact, the function has a global minimum at x = -6, where it takes the value of 0.

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According to the attached graph

The roots of the parabola (-3, 0)and (7, 0)

the vertex is at (2, 25)

two other points are (0, 21) and (-2.5, 5)

The vertex of a parabola signifies the highest or lowest point depending on the direction it opens.

To find the vertex, we use the formula with regards to a parabola in the format of y = ax^2 + bx + c:

Vertex x-coordinate = -b / (2a)

Vertex y-coordinate is equal to f(x) = ax²+bx+c, keeping x as the found vertex x-coordinate

Vertex x-coordinate = -b / (2a) for y = -x^2 + 4x + 21

b = 4

a = -1

Vertex x-coordinate = -4 / (2 * -1) = 2

substituting x = 2 into  y = -x^2 + 4x + 21  gives y as 25

hence the vertex is (2, 25

)

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The term var2 × var2 specifies that both the linear and quadratic terms for var2 should be included in the model.

Now, Let's an example code for fitting an MLR model with a linear and quadratic term for var2 using proc glm in SAS as;

proc glm data = your_dataset;

model var1 = var2 var2 × var2;

run;

Hence, In this code, your _ dataset refers to the name of the dataset that you are using.

The model statement specifies the variables in the model, where var1 is the dependent variable and var2 is the independent variable.

Thus, The term var2 × var2 specifies that both the linear and quadratic terms for var2 should be included in the model.

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We can answer the questions based on the given triangles in this way:

a) sin(BAC) depends only on AB, BC, and BCA, and are the same in both drawings, we have sin(BAC) = 3/5.

b) ∠BAC in the drawing where it is acute is ≈ 36.9°.

c) The ∠BAC in the drawing where it is obtuse is ≈ 143.1°.

The angles of a triangle when added together is always 180°.

To calculate the angles of a triangle, we use the formulas like the Law of Cosines, the Law of Sines, or trigonometric functions like sine, cosine, and tangent.

a) To find sin(BAC), we shall use the Law of Cosines to first find the length of AC:

(AC)² = (AB)² + (BC)² - 2(AB*BC)cos(BCA)

AC² = 15² + 18² - 2(15*18)cos(30°)

AC² = 729

AC = 27

Next, we use the Law of Sines to find sin(BAC):

sin(BAC) / AB = sin(BCA) / AC

sin(BAC) / 15 = 1/2 / 27

sin(BAC) = 3/5

Since sin(BAC) only depends on AB, BC, and BCA, which are the same in both drawings, we have sin(BAC) = 3/5 in both drawings.

b) In the acute triangle, we have:

sin(BAC) / AB = sin(BCA) / AC

sin(BAC) / 15 = 1/2 / 27

sin(BAC) = 3/5

BAC = arc sin(3/5)

BAC ≈ 36.9°

c) In the obtuse triangle, we have:

sin(BAC) / AB = sin(BCA) / AC

sin(BAC) / 15 = 1/2 / 27

sin(BAC) = 3/5

Since sin(BAC) is positive and ≤ 1, we know that BAC is an acute angle or a reflex angle.

But we are told that BAC is obtuse angle, meaning:

BAC = 180° - arc sin(3/5)

BAC ≈ 143.1°

Learn more about angles of a triangle at brainly.com/question/22262639

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