A certain discrete mathematics class consists of 28 students. Of these, 13 plan to major in mathematics and 14 plan to major in computer science. Five students are not planning to major in either subject. How many students are planning to major in both subjects

The probability that Tamika's result is greater than Carlos' result is $\boxed{\frac{4}{9}}$.

To solve this problem, we can start by finding all the possible sums that Tamika can get by adding two different numbers from the set $\{8,9,10\}$:

- $8+9=17$
- $8+10=18$
- $9+10=19$

Similarly, we can find all the possible products that Carlos can get by multiplying two different numbers from the set $\{3,5,6\}$:

- $3\times5=15$
- $3\times6=18$
- $5\times6=30$

Now we need to compare each sum with each product to see which ones satisfy the condition that Tamika's result is greater than Carlos' result. We can organize this information in a table:

| Tamika's sum | Carlos' product | Tamika's sum > Carlos' product? |
| ------------ | -------------- | ----------------------------- |
| 17           | 15             | Yes                           |
| 17           | 18             | No                            |
| 17           | 30             | No                            |
| 18           | 15             | Yes                           |
| 18           | 18             | No                            |
| 18           | 30             | No                            |
| 19           | 15             | Yes                           |
| 19           | 18             | Yes                           |
| 19           | 30             | No                            |

Out of the 9 possible combinations, there are 4 that satisfy the condition, namely when Tamika gets a sum of 17, 18 (twice), or 19 and Carlos gets a product of 15 or 18. Therefore, the probability that Tamika's result is greater than Carlos' result is $\boxed{\frac{4}{9}}$.

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The horizontal distance along the grid line from the highest grid elevation point to the 97 contour is 52.38 feet.

To solve this problem, we first need to determine the location of the highest grid elevation point on the grid line labeled 96.33 and 97.48.

Let's assume that the highest grid elevation point is located at a distance of x feet from the grid line labeled 96.33. Therefore, the distance from the same point to the grid line labeled 97.48 would be 50 - x feet (as the total length of the grid line is 50 feet).

Now, we need to determine the location of the 97 contour on the same grid line. Let's assume that the 97 contour intersects the grid line at a distance of y feet from the grid line labeled 96.33.

Since the highest grid elevation point is on the same grid line, it must also be on the 97 contour. Therefore, we can set the elevation at the highest point equal to 97 and use this information to solve for x and y.

We can set up two equations based on the information we have:

x² + y² = d² (Equation 1)

x + (50 - x) = y (Equation 2)

where d is the horizontal distance we are trying to find.

We can simplify Equation 2 to:

50 = y

Substituting this into Equation 1, we get:

x² + 50² = d²

Rearranging this equation, we get:

d² = x² + 2500

Now we can substitute 97 for the elevation at the highest point, and solve for x:

(97 - 96.33)/0.01 = x/50

x = 33.5 feet

Substituting this value of x into the equation for d², we get:

d² = (33.5)² + 2500 = 2742.25

Taking the square root of both sides, we get:

d = 52.38 feet (approx.)

Therefore, the horizontal distance along the grid line from the highest grid elevation point to the 97 contour is approximately 52.38 feet.

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The mean, of the sampling distribution of the mean, for samples of size 48 equals 65.

The central limit theorem states that the sampling distribution of the mean of a large number of random samples taken from a population will be approximately normally distributed, regardless of the shape of the population distribution. The mean of the sampling distribution of the mean is equal to the population mean, which in this case is 65.

The standard deviation of the sampling distribution of the mean is equal to the population standard deviation divided by the square root of the sample size. Therefore, the standard deviation of the sampling distribution of the mean for samples of size 48 is 10.2 / √48 ≈ 1.47.

Since the sampling distribution of the mean is approximately normally distributed with a mean of 65 and a standard deviation of 1.47, the mean of the sampling distribution of the mean for samples of size 48 is 65.

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Since the output of the sigmoid function is 0.64, the predicted probability of the observation being malignant is 0.64. We need to set a threshold probability to classify the observation as malignant or benign.

If we set the threshold probability at 0.5, the observation would be classified as malignant, since the predicted probability (0.64) is greater than the threshold probability. However, the choice of threshold probability depends on the specific problem and the costs associated with false positives and false negatives. So, the predicted category would be malignant if the threshold probability is set at 0.5.

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The component of statistical methodology that encompasses the collection, organization, and summarization of data is referred to as descriptive statistics.

Descriptive statistics is a fundamental aspect of statistical methodology that focuses on the initial stages of data analysis. It involves the collection of data through various methods such as surveys, experiments, or observational studies. This data is then organized and structured in a systematic manner to facilitate a comprehensive understanding of its characteristics.

The first step in descriptive statistics is data collection. This can involve various techniques such as sampling, where a subset of the population is selected to represent the entire group. The collected data can be quantitative (numerical) or qualitative (categorical), depending on the nature of the study.

Once the data is collected, it needs to be organized in a meaningful way. This can involve sorting, categorizing, and arranging the data into different groups or categories. For quantitative data, measures such as frequency distributions, histograms, and scatter plots can be used to organize and display the data. For qualitative data, methods such as tables, charts, or graphs may be employed to summarize the information.

Finally, descriptive statistics involves summarizing the collected and organized data to extract key insights and characteristics. This can include measures such as central tendency (mean, median, mode), variability (range, variance, standard deviation), and correlation. These measures provide a concise summary of the data, enabling researchers to gain a better understanding of its overall patterns, trends, and distribution.

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The probability is 28/45, which simplifies to 0.6222 or approximately 62.22%.

To calculate the probability of both light bulbs being good, we'll use the terms:

sample space, favorable outcomes, and probability.
Sample space:

This is the total number of possible outcomes when selecting two light bulbs.

Since there are 10 light bulbs in the drawer, the sample space is the number of ways to choose 2 light bulbs from 10, which can be calculated using combinations.

So, the sample space is C(10,2) = 10! / (2! * (10-2)!) = 45 possible outcomes.
Favorable outcomes:

These are the outcomes where both light bulbs are good.

There are 8 good light bulbs in the drawer,

so the number of favorable outcomes is the number of ways to choose 2 good light bulbs from the 8, which is C(8,2) = 8! / (2! * (8-2)!) = 28 favorable outcomes.
Probability: To find the probability of both light bulbs being good, divide the number of favorable outcomes by the sample space.

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The perimeter of the triangle is 23 ft.

We have,

We can use the triangle inequality theorem to check whether this triangle can exist.

According to the theorem, the sum of the lengths of any two sides of a triangle must be greater than the length of the third side.

Let's check whether this condition holds for the sides given:

5 + 7 = 12, which is greater than 11, so the condition holds.

5 + 11 = 16, which is greater than 7, so the condition holds.

7 + 11 = 18, which is greater than 5, so the condition holds.

Therefore, this triangle can exist.

To find the perimeter of the triangle, we simply add up the lengths of the three sides:

Perimeter = 5 + 7 + 11 = 23 ft

Therefore,

The perimeter of the triangle is 23 ft.

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The triangle inequality theorem states that a triangle with sides of 5, 7, and 11 feet is feasible.

The polygonal shape of a triangle has a number of sides and three independent variables. Angles in the triangle add up to 180°.

Any two triangle sides' lengths added together must be bigger than the third side's length.

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Let G be a triangulation with n vertices, m edges and f faces. Since G is a triangulation, we know that each face has three edges and each edge is incident to two faces. Therefore, we have:

3f = 2m (1)

Now, let us consider the sum of the degrees of all the vertices in G. Each vertex v is incident to some number of edges, say d(v). Since each edge is incident to exactly two vertices, the sum of the degrees of all the vertices is given by:

2m = Σv∈G d(v) (2)

Using the handshake lemma, we know that the sum of degrees of all vertices in a graph is twice the number of edges, which gives us equation (2).

Now, we can find the average degree of a vertex in G by dividing the sum of degrees of all vertices by the number of vertices:

average degree = (Σv∈G d(v))/n

Substituting equation (2) into the above expression, we get:

average degree = 2m/n

Now, we can use Euler's formula to relate the number of vertices, edges, and faces in a planar graph:

n - m + f = 2

Substituting equation (1) into the above expression, we get:

n - (3f/2) + f = 2

n/2 = f + 2

Substituting the above expression into equation (2), we get:

2m = Σv∈G d(v) <= Σv∈G 6 = 6n

Dividing by n on both sides, we obtain:

2m/n <= 6

Substituting this expression into the expression for the average degree, we have:

average degree = 2m/n <= 6

Therefore, the average degree of a vertex in a triangulation is strictly less than 6.

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(G) (-9, 12) is the point on the given line.

We can use the point-slope form of the equation of a line to find the equation of the line with slope -1/3 and passing through the point (6, 7):

y - y' = m(x - x'), where m is the slope, and (x', y') is the given point.

Plugging in m = -1/3, x' = 6, and y' = 7, we get:

y - 7 = (-1/3)(x - 6)

Multiplying both sides by -3, we get:

-3y + 21 = x - 6

x + 3y = 27

This is the equation of the line.

To find another point on this line, we can substitute each of the given points into the equation and see which one satisfies it. We can also check the answer choices one by one. Let's start with (F) (-3, 8):

x + 3y = 27

-3 + 3(8) = 21, so this point does not satisfy the equation and is not on the line.

Next, let's try (G) (-9, 12):

x + 3y = 27

-9 + 3(12) = 27, so this point does satisfy the equation and is on the line.

We can stop here and conclude that the answer is (G) (-9, 12). However, just for completeness, let's also check the other answer choices:

(H) (12, 13):

x + 3y = 27

12 + 3(13) = 51, so this point does not satisfy the equation and is not on the line.

(J) (18, -3):

x + 3y = 27

18 + 3(-3) = 9, so this point does not satisfy the equation and is not on the line.

Therefore, the answer is (G) (-9, 12).

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The correct answer is "the model of arrivals." A Poisson process is a statistical model used to describe the arrival times of events that occur randomly over time. These events are assumed to occur independently of each other and with a constant rate or intensity. The process is named after French mathematician Siméon Denis Poisson.

The model of departure times, on the other hand, describes the times at which objects or individuals leave a certain location or system. It is not necessarily a Poisson process and can depend on various factors such as the size of the system or the behavior of the individuals.

Dependent events are those that are influenced by previous events or conditions. They are not typically modeled using a Poisson process, as this assumes independence between events. However, there are other statistical models that can be used to describe dependent events.

Overall, it is important to understand the characteristics and assumptions of different statistical models in order to choose the appropriate one for a given situation.

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we can expect there to be approximately 696 rats (rounded to the nearest whole) in the bay area of the city after 18 months of growth at a rate of 6% per month.

To solve this problem, we can use the formula for exponential growth:
[tex]P(t) = P(0)e^{rt}[/tex]

where P(0) is the initial population, r is the growth rate (in decimal form), t is the time period, and e is the mathematical constant approximately equal to 2.718.

In this case, P(0) = 310, r = 0.06 (since the population grows at a rate of 6% per month), and t = 18 months. So we have:

[tex]P(18) = 310 e^{(0.06 * 18)}[/tex]
P(18) =696

Therefore, we can expect there to be approximately 696 rats (rounded to the nearest whole) in the bay area of the city after 18 months of growth at a rate of 6% per month.

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Answer:

20fish

Step-by-step explanation:

so 1/2 of 16 is 8

or 1/4 of 32 is 8

so 8+32=40

40 1/2 is 20

so 20 fish caught on Monday

Answer:

the second option

Step-by-step explanation:

because that is supposed to be the median of the data

Answer: (x+7)(x+7), 7 plus 7 is 14 and 7 times 7 is 49

Answer:

A

Step-by-step explanation:

the answer is A. because the direction of arow is left. and at point 8, the point is hollow.

There are 1,602,562,500 different passwords that can be made up using the given pattern and character choices.

We need to make a password with eight characters, where the first seven characters follow the pattern CVCVCVC, and the eighth character is a digit. There are 21 consonants and 5 vowels available, and there are 10 digits (0-9) available for the eighth character.

To find the number of possible passwords, we can count the number of choices for each character in the password, and then multiply the choices together.

For the first character, we can choose from 21 consonants. For the second character, we can choose from 5 vowels. For the third character, we can choose from 21 consonants again, and so on, alternating between consonants and vowels. For the eighth character, we can choose from 10 digits.

Therefore, the total number of possible passwords is:

21 x 5 x 21 x 5 x 21 x 5 x 21 x 10 = 1,602,562,500

So there are 1,602,562,500 different passwords that can be made up using the given pattern and character choices.

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There is about a 26.5% chance of randomly selecting one fork, one spoon, and one knife from the drawer of 18 pieces of silverware.

To find the probability of selecting one fork, one spoon, and one knife out of the 18 pieces of silverware in the drawer, we can use the formula for probability:

Probability = (number of favorable outcomes) / (total number of possible outcomes)

First, let's find the total number of possible outcomes. Since we are selecting three pieces of silverware without replacement, the total number of possible outcomes is the number of ways to choose three pieces from 18:

Total possible outcomes = 18C3 = (18 x 17 x 16) / (3 x 2 x 1) = 816

Next, let's find the number of favorable outcomes, i.e., the number of ways to choose one fork, one spoon, and one knife. We can break this down into three steps:

Step 1: Choose one fork from the 6 available forks
Step 2: Choose one spoon from the 6 available spoons
Step 3: Choose one knife from the 6 available knives

The number of ways to perform each step is simply the number of available items, so:

Number of favorable outcomes = 6 x 6 x 6 = 216

Therefore, the probability of selecting one fork, one spoon, and one knife is:

Probability = 216 / 816 = 0.265

This means that there is about a 26.5% chance of randomly selecting one fork, one spoon, and one knife from the drawer of 18 pieces of silverware.

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Thus, there are 18 ways to choose one book, 153 ways to choose two books, and 360 ways to choose three books, one from each category.

To find the number of ways a student can choose from the given library, we need to use the formula for combinations.

The formula for combinations is:
nCr = n! / r!(n-r)!

where n is the total number of items, r is the number of items to be chosen, and ! denotes factorial.

Let's consider the different ways a student can choose:

1. Choosing one book from any category:
Total number of books = 5+3+6+4 = 18
n = 18, r = 1
Number of ways = 18C1 = 18! / 1!(18-1)! = 18

2. Choosing two books from any category:
n = 18, r = 2
Number of ways = 18C2 = 18! / 2!(18-2)! = 153

3. Choosing three books, one from each category:
For this, we need to choose one book from each category, and the order of selection does not matter.
n1 = 5, r1 = 1 (for history)
n2 = 3, r2 = 1 (for sociology)
n3 = 6, r3 = 1 (for anthropology)
n4 = 4, r4 = 1 (for psychology)
Number of ways = (5C1 x 3C1 x 6C1 x 4C1) = (5 x 3 x 6 x 4) = 360

Therefore, there are 18 ways to choose one book, 153 ways to choose two books, and 360 ways to choose three books, one from each category.

In summary, a student can choose:
- 18 ways to choose one book
- 153 ways to choose two books
- 360 ways to choose three books, one from each category

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The critical points of the function f(x) = 4sin(x)cos(x) in the interval (0, 2π) are:
x = π/4, 3π/4, 5π/4, 7π/4

To find the critical points of the function f(x) = 4sin(x)cos(x) in the interval (0, 2π), we need to find the values of x where the first derivative, f'(x), is equal to 0 or undefined.

First, let's find the derivative using the product rule:

f'(x) = (4sin(x))'(cos(x)) + (4sin(x))(cos(x))'
f'(x) = (4cos(x))(cos(x)) - (4sin(x))(sin(x))
f'(x) = 4(cos^2(x) - sin^2(x))

Now, we set f'(x) = 0 and solve for x:

4(cos^2(x) - sin^2(x)) = 0
cos^2(x) = sin^2(x)

Recall that sin^2(x) + cos^2(x) = 1. So, cos^2(x) = 1 - sin^2(x). Substitute this into the\:

1 - sin^2(x) = sin^2(x)
2sin^2(x) = 1
sin^2(x) = 1/2
sin(x) = ±√(1/2)

So, x = arcsin(±√(1/2)).

We need to find the solutions for x in the interval (0, 2π):

x = π/4, 3π/4, 5π/4, 7π/4

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we need to first calculate the deviation of a GPA less than 1.85 from the mean GPA of 2.3, Deviation = 1.85 - 2.3 = -0.45 Next, we need to calculate the z-score for this deviation using the formula: z = (x - μ) / σ .

where x is the value we want to convert to a z-score, μ is the population mean, and σ is the population standard deviation. z = (-0.45 - 2.3) / 0.7 = -3.07, We can use a z-score table or calculator to find the percentage of the population that falls below this z-score.

According to the table, the percentage of the population with a z-score less than -3.07 is approximately 0.001. Therefore, the percentage of students who will be dropped from college is approximately 0.1% (or 0.001 x 100).
The Z-score formula is: Z = (X - μ) / σ.

Where X is the GPA value (1.85), μ is the mean (2.3), and σ is the standard deviation (0.7). Z = (1.85 - 2.3) / 0.7 = -0.64
Now, we'll use the standard normal distribution table to find the percentage of students corresponding to a Z-score of -0.64. The table gives us a value of 0.2611.Thus, approximately 26.11% of the students with a GPA less than 1.85 will be dropped from college.

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The probability that the second inspector will find a flaw in an item that has been passed by the first inspector is simply the True Positive Rate, which is "b".

To find the probability that the second inspector will find a flaw in an item that has been passed by the first inspector, we need to consider the following terms:

1. Probability of the first inspector passing a flawed item (False Negative Rate)
2. Probability of the second inspector finding a flaw when examining a flawed item (True Positive Rate)

Let's assume the following probabilities:
- Probability of the first inspector passing a flawed item: P(False Negative) = a
- Probability of the second inspector finding a flaw in a flawed item: P(True Positive) = b

Now, let's calculate the probability that the second inspector will find a flaw in an item that has been passed by the first inspector:

P(Second Inspector finds flaw | First Inspector passes item) = P(True Positive | False Negative) = b

In this case, we don't need to account for the probability of the first inspector passing the flawed item, as we're given that the second inspector only examines items passed by the first inspector.

Therefore, the probability that the second inspector will find a flaw in an item that has been passed by the first inspector is simply the True Positive Rate, which is "b".

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Thus, the rate at which the boy's shadow is lengthening when he is 20 feet from the light is 3.75 feet/s.

To solve this problem, we need to use similar triangles.

Let's call the length of the boy's shadow "x" and the distance from the streetlight to the boy "y". At the moment he is 20 feet from the light, we have:

y = 20 feet (given)
x + 6 = length of the boy's shadow

We can set up a proportion to relate the length of the boy's shadow to the height of the streetlight:

(x + 6)/x = 15/6

Cross-multiplying and simplifying, we get:

6x + 90 = 15x
9x = 90
x = 10 feet

So at the moment the boy is 20 feet from the light, his shadow is 10 feet long. To find the rate at which his shadow is lengthening, we need to take the derivative of this equation with respect to time:
x + 6 = (y - 15)/y * (y') + 6

where y' is the rate at which the boy is walking away from the light (5 feet/s). Plugging in y = 20 feet and solving for x', we get:
x' = (15/20) * 5 = 3.75 feet/s

Therefore, the rate at which the boy's shadow is lengthening when he is 20 feet from the light is 3.75 feet/s.

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The correct answer to the question "The sampling distribution of a statistic probability distribution." is option c) is a probability distribution.

To understand the concept of a sampling distribution, we need to understand what a statistic is. A statistic is a numerical value that describes some aspect of a population. For example, the mean, median, mode, variance, and standard deviation are all examples of statistics.

In statistics, we are often interested in making inferences about a population based on a sample of that population. A sampling distribution is a probability distribution that shows all possible values that a statistic can take on, and the probability of getting each value under the assumption that it had resulted due to chance alone.

The sampling distribution is an important concept in statistics because it allows us to make inferences about a population based on a sample. By knowing the sampling distribution of a statistic, we can calculate the probability of getting a particular value of the statistic under the assumption of random sampling. This information can be used to make decisions about the population, such as whether a hypothesis is supported or rejected.

In conclusion, the sampling distribution of a statistic is a option c) It is a probability distribution that gives the probability of getting each value of a statistic under the assumption it had resulted due to chance alone. It is a critical tool for making inferences about populations based on samples.

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Answer: hi i am not sure what questions you need but look below.

1. D. The temperature dropped 4 degrees each hour for 5 consecutive days.

2. Brenda simplified the expression correctly.

Step-by-step explanation:

1. the equation is -4(5)=-20.

- means that the number is decreasing or below zero. so If the temp. dropped 4 degrees each hour for 5 days then the expression for that would be -4(5)=-20

2. Brenda is correct because -5x+(2+x)= -5+x+2

You must break the expression up. -5x +x and -5x + 2. Sine -5x+x= -4x and you cant simplify -5x+2 because they dont have the same variable, your answer is -4x+2.

You are welcome

The vertex of the  parabola is (1, -1), x = 1 as the equation of the axis of symmetry and the roots of the parabola are x = 0 and x = -2

The graph represents the given parabola

As a general rule:

The vertex of a parabola is the minimum or the maximum of a quadratic funtion

In this case, we have

Minimum = (1, -1)

This means that the vertex of the given parabola is (1, -1)

The equation of the axis of symmetry is the x-coordinate of the vertex

In this case, we have

x = 1 as the equation of the axis of symmetry

These are the points where the graph crosse the x-axis

In this case, the roots of the parabola are x = 0 and x = -2

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Thus, the length of a side of the regular hexagon is 8 centimeters using the Pythagorean theorem.

The key to solving this problem is to realize that the perpendiculars drawn from the interior point to the sides of the hexagon form a right triangle with one leg being the perpendicular and the other leg being a side of the hexagon. We also know that the hexagon is regular, meaning all sides have the same length.

Let's label the length of the side of the hexagon as "x". We can use the Pythagorean theorem to find the length of each perpendicular as follows:

- For the perpendicular that is 4 cm long, we have x^2 = 4^2 + (x/2)^2
- For the perpendicular that is 5 cm long, we have x^2 = 5^2 + (x/2)^2
- For the perpendicular that is 6 cm long, we have x^2 = 6^2 + (x/2)^2
- For the perpendicular that is 8 cm long, we have x^2 = 8^2 + (x/2)^2
- For the perpendicular that is 9 cm long, we have x^2 = 9^2 + (x/2)^2
- For the perpendicular that is 10 cm long, we have x^2 = 10^2 + (x/2)^2

Simplifying each equation and using a bit of algebra, we get:

- 3x^2 = 16^2
- 7x^2 = 25^2
- 12x^2 = 36^2
- 24x^2 = 64^2
- 33x^2 = 81^2
- 40x^2 = 100^2

Solving for x in each equation, we find that x = 8 cm. Therefore, the length of a side of the regular hexagon is 8 centimeters.

In summary, we used the fact that the perpendiculars from an interior point to the sides of a regular hexagon form right triangles to set up equations using the Pythagorean theorem. Solving for the length of a side of the hexagon in each equation, we found that it is 8 cm long.

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Answer:  How do you know how many solutions an equation has?

If solving an equation yields a statement that is true for a single value for the variable, like x = 3, then the equation has one soluti

Step-by-step explanation:

The probability that Max will get the job is 3/10 or 0.3.

To see why, we can use the fact that the sum of the probabilities of all possible outcomes is equal to 1. Let A, B, and C represent the events that the first, second, and third companies respectively get the job.

Then the probability that Max gets the job is equal to the probability of event AB~C (i.e., none of the other companies gets the job).

The probability of A is 1/5, the probability of B is 1/2, and the probability of C is 3/10 (since the sum of the probabilities of all three events is 1). Using the formula for the probability of the intersection of independent events, we have:

P(AB~C) = P(~A) * P(~B) * P(~C) = (4/5) * (1/2) * (7/10) = 14/50 = 0.28

So the probability that Max gets the job is 0.3, or 3/10.

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On flipping a coin, the number of total possibility for obtaining least one head if we flip the coin seven times are equal to 127.

We have an experiment for flip a coin and keep a record of the results.

Number of total possible outcomes on flipping a coin = 2 = { H, T}

Number of trials or a coin is flipped = 7

We have to determine the number of ways that at least one head if we flip the coin seven times. When we flip a two-sided coin n times, there are [tex]2^ n[/tex] possible outcomes. So, when a coin is flipped 7 times then total possible number of outcomes = 2⁷ = 128

Let's consider an Event A : getting at least one head in seven flips

Complement of this event is getting no head and it is denoted by [tex]A^ c =[/tex]{ T T T T T T T }

and this event will be occur in one way only. So, Number of ways of obtain at least one head if you flip the coin five times = 128 - 1 = 127 ways.

Hence, required value is 127 ways.

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If a pilot elects to proceed to the selected alternate, the landing minimums used at that airport should be equal to or higher than the minimums required for the original destination airport.

When a pilot chooses to proceed to the selected alternate airport, they must consider the weather conditions at that airport, particularly the landing minimums. The landing minimums are the lowest weather conditions in which an aircraft can safely land at an airport. They are determined by various factors, such as the visibility range and the height of the cloud ceiling.

Therefore, if a pilot decides to go to the alternate airport, they should use the landing minimums for that airport to ensure a safe landing. The landing minimums for the alternate airport should be equal to or higher than the minimums required for the original destination airport.

It's important to note that the pilot must have knowledge of the landing minimums for the alternate airport before deciding to proceed there. If they don't have the necessary information, they should consider other options, such as returning to the departure airport or diverting to a different airport with suitable weather conditions.

In summary, when a pilot chooses to proceed to an alternate airport, they should use the landing minimums for that airport to ensure a safe landing. The pilot must have knowledge of the minimums before proceeding to the alternate airport.

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