I need some help……..

The probability that 3 of the 9 randomly selected subjects entered a profession closely related to their college major is approximately 0.1665, or 16.65%.

To find the probability that 3 out of 9 randomly selected subjects entered a profession closely related to their college major, we can use the binomial probability formula:
[tex]P(X = k) = (n choose k) * p^k * (1 - p)^{n - k}[/tex]
where:
- P(X = k) is the probability of k successes (in this case, 3 people entering a profession closely related to their major)
- n is the number of trials (9 subjects)
- k is the number of successes (3 people)
- p is the probability of success (53% or 0.53)
- (n choose k) is the number of combinations of n items taken k at a time, which can be calculated as C(n, k) = n! / (k! * (n - k)!)
Plugging in the values, we get:
[tex]P(X = 3) = C(9, 3) * (0.53)^3 * (1 - 0.53)^{9 - 3}[/tex]
First, calculate the combinations (n choose k):
C(9, 3) = 9! / (3! * (9 - 3)!)
C(9, 3) = 9! / (3! * 6!)
C(9, 3) = 362880 / (6 * 720)
C(9, 3) = 84
Now, calculate the probabilities:
[tex]P(X = 3) = 84 * (0.53)^3 * (0.47)^6[/tex]
P(X = 3) = 84 * 0.148877 * 0.013325
P(X = 3) ≈ 0.1665.

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For the given statement after evaluating both the options the correct option is true under the condition that scores increase and null hypothesis is used to find out Treatment effect.

Here, null hypothesis clearly states that there is no significant difference is observed in comparison of sample mean and population mean.

Null hypothesis refers to statistical process which takes certain assumptions regarding two sets of different variables. In the branch of science it is used to find credibility regarding a sample data.

For the given case, the null hypothesis presents   that the population mean remains unchanged (m = 60) post  treatment, doesn't matter if it is greater than or equal to 60. The alternative hypothesis will be increases the mean  for the treatment (m > 60).

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True. Your statement is: A researcher administers a treatment to a sample from a population with a mean of m = 60. If the treatment is expected to increase scores and a one-tailed test is used to evaluate the treatment effect, then the null hypothesis would state that m ≥ 60.

The null hypothesis typically represents no effect or no difference. In this case, the null hypothesis would state that the population mean remains unchanged (m = 60) after the treatment, not that it is greater than or equal to 60. The alternative hypothesis would be that the treatment increases the mean (m > 60).

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Thus, the on average the contents weight for the transatlantic shipping is found as  24.7  pounds.

Given dimension of rectangular prism

Length l = 4ft

width w = 9.5 ft

height h = 13 ft

Volume of rectangular prism = l*w*h

V = 4*9.5*13

V = 494 ft³

Now,

1  ft³ = 0.05 pounds

So,

weight of  494 ft³ =  494*0.05 pounds

weight of 494 ft³ =  24.7  pounds

Thus, the on average the contents weigh for the transatlantic shipping is found as  24.7  pounds.

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The volume of the trapezoidal prism is 180 cubic meters.

What are parallel lines?

Parallel lines are two lines in a plane that never intersect. This means that they maintain the same distance between each other at all points.

To find the volume of a trapezoidal prism, we need to multiply the area of the trapezoidal base by the height of the prism.

The trapezoidal base has a length of 10m and 8m, and a height of 4m. The formula for the area of a trapezoid is:

Area = (a + b) * h / 2

where a and b are the lengths of the parallel sides, and h is the height.

Using the formula, we can calculate the area of the trapezoidal base:

Area = (10m + 8m) * 4m / 2

Area = 36m²

Therefore, the volume of the trapezoidal prism is:

Volume = Area of base * Height

Volume = 36m² * 5m

Volume = 180 cubic meters

Therefore, the volume of the trapezoidal prism is 180 cubic meters.

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The critical value of the chi-square distribution corresponding to a sample size of 5 and a confidence level of 98% is given as follows:

0.297 and 13.277.

To obtain a critical value, we need three parameters, given as follows:

Then, with the parameters, the critical value is found using a calculator.

The parameters for this problem are given as follows:

Using a chi-square distribution calculator, the critical values are given as follows:

0.297 and 13.277.

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where t is measured in days, and A(t) represents the amount of flooded land at time t. This function has a B-value of -0.3118.

To model the situation of the flood, we can use an exponential decay function, which represents the decreasing amount of flooded land over time. The function can be written as:

[tex]A(t) = A0 * e^{(-kt)}[/tex]

where A(t) is the amount of flooded land at time t, A0 is the initial amount of flooded land, k is a constant representing the rate of decay, and e is the mathematical constant approximately equal to 2.718.

To determine the value of k, we can use the given information that after 2 days, only 3375 acres of land were under water. Substituting t = 2 and A(t) = 3375 into the equation above, we get:

[tex]3375 = A0 * e^{(-2k)[/tex]

We also know that initially, there were 6000 acres of land under water. Substituting A0 = 6000 into the equation above, we get:

Dividing both sides by 6000, we get:

ln(0.5625) = -2k[tex]ln(0.5625) = -2k[/tex]

Taking the natural logarithm of both sides, we get:

[tex]ln(0.5625) = -2k[/tex]

Solving for k, we get:

[tex]k = -ln(0.5625)/2[/tex]

k ≈ 0.3118

Therefore, the function to model the situation of the flood is:

[tex]A(t) = 6000 * e^{(-0.3118t)}[/tex]

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The probability of the sample mean being less than 79 is 77.64%

In order to solve the given problem we have to take the help of Standard error mean

SEM = ∑/√(n)

here,

∑ = population standard deviation

n = sample size

hence, the z-score can be calculated as

z = ( x' - μ)/σ/√(n)

here,

x' = sample mean

μ = population mean

σ = population standard deviation

n = sample size

adding the values into the formula

SEM = σ / √(n)

= 21/√64

= 2.625

z = (x' - μ)/SEM

= (79-77)/2.625

= 0.76

now, using standard distribution table we find that probability of a z-score is less than 0.77 then converting it into percentage

0.77 x 100

= 77%

The probability of the sample mean being less than 79 is 77.64%

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The center-radius form of the circle is:

(x + 3)² + (y - 5)² = 25

What is a circle?

It is the center of an equidistant point drawn from the center. The radius of a circle is the distance between the center and the circumference.

Given the equation (x - 11)² + (y + 4)² = 15, we can see that the equation is in standard form:

(x - h)² + (y - k)² = r²

where (h, k) is the center of the circle, and r is the radius. Comparing the given equation with the standard form, we can see that:

h = 11, k = -4, and r² = 15

Taking the square root on both sides, we get:

r = √15

Therefore, the center of the circle is (11, -4) and the radius is √15.

The center-radius form of the circle with center (-3, 5) that passes through the point (0, 1) can be found using the formula:

(x - h)² + (y - k)² = r²

where (h, k) is the center of the circle and r is the radius. We are given that the center of the circle is (-3, 5), so we can substitute these values into the formula:

(x - (-3))² + (y - 5)² = r²

Simplifying the expression on the left-hand side, we get:

(x + 3)² + (y - 5)² = r²

Now, we need to find the value of r. Since the circle passes through the point (0, 1), we can substitute these values into the equation above:

(0 + 3)² + (1 - 5)² = r²

Simplifying the expression on the left-hand side, we get:

9 + 16 = r²

25 = r²

Taking the square root on both sides, we get:

r = 5

Therefore, the center-radius form of the circle is:

(x + 3)² + (y - 5)² = 25

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Yes, this would be a valid matched pair test. In a matched pair test, two samples are taken from the same group or individual, and the samples are matched on some criteria such as age, sex, or in this case, location in the glass of water.

The researcher is using a matched pair test, which is an acceptable method to account for individual variations and boost the statistical power of the test, by collecting samples from the top and bottom of the glass of water and matching them according to the position. Due to the fact that any additional changes (such as in the source of the water or pollution) should be uniformly distributed across the two groups, this design also enables the researcher to ascertain whether there is a substantial difference in zinc levels between the top and bottom of the glass of water.

A paired t-test will be used to conduct the test in order to see if there is a significant difference between the zinc levels at the top and bottom of the water glass.

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The congruence of the various parts are demonstrated as given below.

2)

3) In the quilt design shown, the m∠STR is 62°. This is because ΔRST ≅ ΔRWX.

In geometry, two parts are said to be congruent if they have the same size, shape, and measure. This means that they are essentially identical and can be superimposed on each other without any gaps or overlaps.

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The measure of the center is 19.

we can predict that about 169 principals

A pie chart shows how the whole is divided into parts

A bar graph with the title favorite sport and the x-axis labeled sport and the y-axis labeled the number of students,

the proportion of students in the sample who prefer ice cream:

81/225 = 0.36

we can predict that about 1440 students prefer ice cream.

What is proportion?

The size, number, or amount of one thing or group as compared to the size, number, or amount of another. The proportion of boys to girls in our class is three to one.

Answer to Question 2:

The appropriate measure of the center for the given box plot is the median, and its value is 19.

Answer to Question 5:

Since 15 out of 80 people in the exhibit room are principals, we can estimate that 15/80 of the total attendees are principals. To estimate the total number of attendees who are principals, we can multiply this fraction by the total number of attendees:

15/80 x 900 = 168.75

So, we can predict that about 169 principals were in attendance at the conference.

Answer to Question 6:

Since the teacher gathered data on the subject that students preferred, a pie chart would be the best graphical representation of the data. A pie chart shows how the whole is divided into parts, which is exactly what the teacher is trying to show.

Answer to Question 7:

A bar graph with the title favorite sport and the x-axis labeled sport and the y-axis labeled the number of students, with the first bar labeled basketball going to a value of 17, the second bar labeled baseball going to a value of 12, the third bar labeled soccer going to a value of 27, and the fourth bar labeled tennis going to a value of 44 correctly displays the data.

Answer to Question 8:

A circle graph titled New York City visitor's transportation, with five sections labeled walk 40 percent, bicycle 8 percent, car service 15 percent, bus 10 percent, and subway 27 percent correctly represents the data in the table.

Answer to Question 9:

To estimate the number of students who prefer ice cream, we can use the proportion of students in the sample who prefer ice cream:

81/225 = 0.36

We can estimate the total number of students who prefer ice cream by multiplying this proportion by the total number of students:

0.36 x 4000 = 1440

So, we can predict that about 1440 students prefer ice cream.

Hence, the answers to all question are:

the measure of the center is 19.

we can predict that about 169 principals

A pie chart shows how the whole is divided into parts

A bar graph with the title favorite sport and the x-axis labeled sport and the y-axis labeled the number of students,

the proportion of students in the sample who prefer ice cream:

81/225 = 0.36

we can predict that about 1440 students prefer ice cream.

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Margin of error is equal to half of this width:

6.544 / 2 = 3.272

In a confidence interval, the margin of error is half of the width of the interval.

So, the width of the confidence interval is:

26.272 - 19.728 = 6.544

Margin of error is equal to half of this width:

6.544 / 2 = 3.272

Rounding to three decimal places, the margin of error is 3.272.

This means that the researchers are 99% confident that the true mean time for the medication to take effect falls between 19.728 and 26.272 minutes.

The margin of error tells us how much we can expect the sample mean (23 minutes) to differ from the true mean. So, we can say with 99% confidence that the true mean time it takes for the medication to take effect is within 3.272 minutes of the sample mean.

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the probability that a randomly selected passenger car gets more than 35 mpg is approximately 0.3665.

the probability that the average mpg of four randomly selected passenger cars is more than 35 mpg is approximately 0.087

the probability that all of the passenger cars get more than 35 mpg is approximately 0.015.

We need to find [tex]P(X > 35),[/tex] where X is the mpg rating of a randomly selected passenger car.

The standard normal distribution and Table 1, we have:

[tex]z = (35 - 33.8) / 3.5 = 0.34[/tex]

[tex]P(X > 35) = P(Z > 0.34) = 0.3665[/tex]

[tex]P(\bar X > 35)[/tex], were [tex]\bar X[/tex] is the sample mean mpg rating of four randomly selected passenger cars.

The population standard deviation, we use the t-distribution with [tex]n-1[/tex] degrees of freedom (were [tex]n = 4[/tex]) and Table 1. We have:

[tex]t = (35 - 33.8) / (3.5 / \sqrt(4)) = 1.83[/tex]

Using Table 1 with 3 degrees of freedom ([tex]n-1 = 4-1[/tex]), we find:

[tex]P(T > 1.83) = 0.087[/tex]

We need to find [tex]P(X1 > 35[/tex] and [tex]X2 > 35[/tex] and [tex]X3 > 35[/tex] and [tex]X4 > 35[/tex]), where X1, X2, X3, and X4 are the mpg ratings of four randomly selected passenger cars.

Since the mpg ratings of the four cars are independent and identically distributed, we have:

[tex]P(X1 > 35[/tex]and[tex]X2 > 35[/tex] and [tex]X3 > 35[/tex] and [tex]X4 > 35[/tex]) =[tex]P(X > 35)^4[/tex]

From part (a), we know that[tex]P(X > 35) = 0.3665.[/tex]

[tex]P(X1 > 35[/tex]and [tex]X2 > 35[/tex] and[tex]X3 > 35[/tex] and [tex]X4 > 35) = 0.3665^4 \approx 0.015[/tex]

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The expression represents the height of the, rectangular prism has a square base with edge length, which is 3 cm.

The expression represents the height of the rectangular prism with a square base of edge length and volume .

To make this more concrete, let's assume some values for and . Let's say that the edge length of the square base is 4 cm, and the volume of the rectangular prism is 48 cubic cm.

Using the formula for the volume of a rectangular prism, we can write:

Volume = Base Area x Height

Since the base of the rectangular prism is a square with edge length 4 cm, its area is:

Base Area = 4 x 4 = 16 square cm

Substituting the given values into the formula for volume, we get:

48 cubic cm = 16 square cm x Height

To solve for the height, we can isolate it on one side of the equation by dividing both sides by 16 square cm:

48 cubic cm ÷ 16 square cm = Height

3 cm = Height

Therefore, in this scenario, the expression represents the height of the rectangular prism, which is 3 cm.

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Answer:

Step-by-step explanation:

25

=

a

b

−

2

10

=

a

b

1

Answer:

236 cm^2  and  8 cm

Step-by-step explanation:

width=w

240=6(5)(w)

w=8 cm

area=2[(6)(5)+(6)(8)+(5)(8)]

area=236 cm^2

The correct statement is that a fairly strong negative linear relationship exists between the x and y variables.

The correlation coefficient is a measure of the strength and direction of the linear relationship between two variables. It ranges from -1 to 1, where a value of -1 indicates a perfect negative correlation, 0 indicates no correlation, and 1 indicates a perfect positive correlation.

In this case, the correlation coefficient is -0.88, which indicates a strong negative linear relationship between the x and y variables. This means that as the value of x increases, the value of y decreases in a predictable manner.

The negative sign of the correlation coefficient indicates that the relationship is negative, meaning that as one variable increases, the other variable tends to decrease. The absolute value of the correlation coefficient, 0.88, indicates a strong relationship, meaning that the values of the two variables are closely related and can be used to predict each other's values.

Therefore, the correct statement is that a fairly strong negative linear relationship exists between the x and y variables.

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Maintain the 95% level of confidence but report a confidence interval with a smaller margin of error, the medical researcher should increase the sample size.

This will provide a more precise estimate of the mean birth weight of babies born to women over the age of 40.

Maintain the 95% level of confidence but report a confidence interval with a smaller margin of error, the researcher should increase the sample size.

The larger the sample size, the smaller the margin of error, which means that the estimated mean birth weight of all babies born to women over the age of 40 will be more precise.
Redoing the study and choosing a different sample of size 100 will not necessarily reduce the margin of error, as the variability in the sample may be the same.

To achieve a smaller margin of error, the researcher needs to increase the sample size.
With a larger sample size, the researcher will have a more representative sample of the population, which will lead to a more accurate estimate of the mean birth weight of all babies born to women over the age of 40.

However, the larger sample size may require more resources and time to collect the data.

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The probability that the golfer will hit at least 6 times in his next 10 attempts is A. 20 %

To estimate the probability of the golfer hitting at least 6 times in his next 10 attempts using a table of random numbers, we can perform a simulation.

Let's use the given table of random numbers to simulate 10 attempts for each trial. We can consider each pair of digits as one attempt. We will perform 10 trials and count how many times the golfer hits at least 6 times in 10 attempts.

Now count the number of trials with at least 6 hits:

Trial 2, Trial 5, and Trial 9 have at least 6 hits. That's 3 out of 10 trials.

To estimate the probability, divide the number of successful trials (at least 6 hits) by the total number of trials:

Probability = (Number of successful trials) / (Total number of trials)

Probability = 3 / 10 = 0.3

The estimated probability that the golfer will hit at least 6 times in his next 10 attempts is 30%. There is no exact match among the possible answers, but the closest one is 20%.

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The correct answer to the given problem is choice B - No.

Jace's earnings are not proportional to the number of hours that he works  because if he worked twice as many hours, he would earn twice as much but he is not earning twice the amount.

Jace's earnings are not proportional to the number of hours that he works. Proportional means that one quantity is a constant multiple of the other. In this case, if Jace's earnings were proportional to the number of hours he works, we would expect that if he worked twice as many hours, he would earn twice as much. However, we can see from the table that this is not the case.

For example, when Jace works 1 hour, he earns $20, but when he works 2 hours, he earns $30, which is not double his earnings for 1 hour of work.

Therefore, Jace's earnings are not proportional to the number of hours that he works.

Hence, the correct option is "B".

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The length from point A to point B on the clock is approximately 24.083 cm, which is closest to 24 cm. This is calculated using the Pythagorean theorem.

Using the Pythagorean theorem, we can calculate the length from point A to point B as follows

First, we need to find the length of the vertical line segment from point D to point A. This is equal to the radius of the clock, which is 24 cm.

Next, we can find the length of the horizontal line segment from point D to point B. This is equal to the distance from the top of the clock at point D to the hanger at point B, which is given as 2 cm.

Now, we can use the Pythagorean theorem to find the length from point A to point B

AB² = AD² + DB²

AB² = (24 cm)² + (2 cm)²

AB² = 576 cm² + 4 cm²

AB² = 580 cm²

AB ≈ 24.083 cm

Therefore, the length from point A to point B is approximately 24.083 cm, which is closest to 24 cm.

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Answer:

The length from point A to point B on the clock is approximately 24.083 cm, which is closest to 24 cm. This is calculated using the Pythagorean theorem.

Hope this helps :)

Pls brainliest...

Answer:

Step-by-step explanation:= x+48=180 ( linier pair )

                                            = x=180-48

                                            = x=132

                                              = x+12=180 (liner pair)

                                              = x=180-12

                                              = x=168

For the given numbers, 78 < 0. 708

To compare two numbers, we need to look at their values and determine which one is larger or smaller. In this case, we have 78 and 0.708. We can start by comparing their whole number parts, which are 78 and 0, respectively. Since 78 is greater than 0, we know that 78 is a larger number.

But what about the decimal parts of these numbers? To compare them, we need to look at the place value of each digit. The first digit after the decimal point in 78 is 0, and the first digit after the decimal point in 0.708 is 7. Since 7 is greater than 0, we know that 0.708 is a larger number than 0.78 in terms of their decimal parts.

Now that we have compared the whole number parts and decimal parts separately, we can combine the results to determine the final comparison. Since 78 is larger than 0 and 0.708 is larger than 0.78 in terms of their decimal parts, we can conclude that:

78 < 0.708

We use the symbol "<" here because 78 is smaller than 0.708.

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The probability that the sample mean would be greater than 87.78 wpm is  0.8933.

The problem  provides information on the mean and variation of the amount of words per minute (wpm) read by sixth graders, and it asks for the likelihood of receiving a sample mean wpm bigger than a particular value if a random sample of 94 sixth graders is collected.

By using a standard normal distribution table or calculator and estimating the sampling distribution of the sample means as being normal using the central limit theorem, we can find the standard deviation of the sampling distribution and calculate the probability of obtaining a sample mean wpm that is less than or equal to the given value by subtracting this value from 1.

Calculations result in a likelihood of 0.8933, which means there is a good chance the sample mean wpm will be higher than the value provided.

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We can use the equation y = 38.8x to find how many miles Camila can drive her car for each gallon of gas, and then use that information to find how many gallons of gas she would need to drive the same distance as Julieta.

Julieta drives 333 miles using 10 gallons of gas, so her car can travel 333/10 = 33.3 miles per gallon.

To find how many miles Camila's car can travel per gallon, we can use the equation y = 38.8x, where x is the number of gallons of gas. If Camila uses 1 gallon of gas, then y = 38.8(1) = 38.8 miles. Therefore, Camila's car can travel 38.8 miles per gallon.

To travel 333 miles like Julieta, Camila would need to use:

333 miles / 38.8 miles per gallon = 8.58 gallons of gas

Therefore, Camila would need to use 8.58 gallons of gas to travel the same distance as Julieta.

The feasible solution is known as a locally optimal solution.

It may not be the best possible solution for the entire optimization problem.

If there are no other feasible solutions with a larger objective function value.

The immediate neighborhood, then the feasible solution is known as a locally optimal solution.

This means that the solution is optimal within a particular region of the feasible space but may not necessarily be the globally optimal solution. Bhe best possible solution over the entire feasible space.

In other words, a locally optimal solution is the best possible solution. Among all feasible solutions in its immediate neighborhood or region.

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No, the ratio of circumference to radius is not the same for every circle.

Ratio refers to the quantitative relation between two or more values, typically expressed in the form of a fraction or a proportion.

No, the ratio of circumference to radius is not the same for every circle. The ratio of circumference to diameter, also known as pi (π), is a constant value that remains the same for every circle. It is approximately equal to 3.14 or 22/7. However, the ratio of circumference to radius varies depending on the size of the circle.

The formula for circumference of a circle is C=2πr, where C is the circumference and r is the radius. Therefore, the ratio of circumference to radius is C/r = 2π. This means that for circles of different sizes, the ratio of circumference to radius will differ since the value of pi remains the same while the radius changes.

For example, if we consider two circles, one with a radius of 2 cm and the other with a radius of 4 cm, the ratio of circumference to radius for the first circle will be 2π (since C = 2πr = 2π x 2 = 4π) and for the second circle, it will be 2π (since C = 2πr = 2π x 4 = 8π). Thus, the ratio of circumference to radius is not the same for every circle.

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The number of possibilities in the given scenario are 144. The solution has been obtained by using permutations.

What is permutation?

Mathematical calculations are used to determine the number of different configurations for a given set, and this procedure is referred to as permutation. A permutation is a phrase that, simply put, refers to the variety of alternative configurations or orders. When employing permutations, the sequence of the arrangement is crucial.

We are given that a team of 12 lacrosse players need to choose a captain and co-captain.

This means that n is 12 and r is 2.

Using permutations, we get

⇒ Total possibilities = [tex]n^{r}[/tex]

⇒ Total possibilities = [tex]12^{2}[/tex]

⇒ Total possibilities = 144

Hence, the number of possibilities in the given scenario are 144.

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It is true that a linear programming problem can have an optimal solution that is not a corner point.

In linear programming, the optimal solution represents the point where the objective function is optimized while still satisfying all the constraints.

In some cases, the optimal solution may occur at a corner point of the feasible region, where two or more of the constraints intersect.

However, it is possible for the optimal solution to occur at a point that is not a corner point, but rather lies on an edge or a line segment of the feasible region.

This can occur when the objective function is parallel to one of the constraint lines or when there are redundant constraints that limit the feasible region.

Therefore, it is true that a linear programming problem can have an optimal solution that is not a corner point.

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