PLEASE HELP ASAP!!!
Dontaya is at the top of a lighthouse
which is 250 feet above sea level. From the top, the measure of the angle of depression to Brace's boat on the water is 48 degrees. How far is Brace's boat from the bottom of the lighthouse? (round your FINAL
answer to the nearest whole foot)

Answer: 1  gallon

Step-by-step explanation:

The expression for  d=rt in terms of the time is t = d/r; t = 5.

Therefore,

In the equation d=rt

                          t = d/r

when distance is 40 and the rate is 8

                          t = d/r

Replace d with 40 and rate with 8

                          t = 40/8

                          t = 5

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 A suggested variable control chart in the education field is a Student Attendance Rate Control Chart. This chart tracks the attendance metric and calculates it as the percentage of students present in a given time period. The information would be tracked regularly, and variations in attendance rates would be interpreted to identify trends and address potential issues.

The Student Attendance Rate Control Chart is a valuable tool in monitoring and managing attendance in educational institutions. The metric tracked on this chart is the attendance rate, which is calculated as the percentage of students present in a specific time period, such as daily, weekly, or monthly.
To track the attendance rate, the educational institution would collect attendance data for each class or session and calculate the percentage of students present. This data can be collected manually or through an automated attendance tracking system. The attendance rate for each time period is plotted on the control chart, allowing for visual representation and tracking over time.
Interpreting the information on the control chart involves analyzing the patterns and variations in the attendance rate. A stable attendance rate would indicate consistent student attendance, while fluctuations or downward trends could indicate potential issues that need attention. By monitoring the control chart, educational institutions can identify periods of low attendance, investigate the reasons behind it, and take appropriate actions such as implementing interventions or improving communication with students and parents to improve attendance rates. The control chart provides a visual representation of attendance patterns and enables proactive measures to be taken to address any attendance-related concerns.

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Answer:

25%

Step-by-step explanation:

If you raised it by 50.

\(\frac{200}{50} =\frac{100}{y}\)

200 × y = 50 × 100

200y = 5000

200y ÷ 200 = 5000 ÷ 200

y = 25

Answer:

Each soccer ball cost $12.20

Step-by-step explanation:

183/15 = 12.20

Answer:

The correct option is;

A total of forty hours a week

Step-by-step explanation:

The given information in the question are;

The number of hours of sleep Nina gets during weeknights = five hours

The number of hours of sleep Nina gets per night on weekends = ten hours

The number of days in a week = 5 days

The number of days in a weekend = 2 days

Therefore;

The number of hours of sleep Nina gets per week = 5 days × 5 hours/day + 2 days × 10 hours/day

∴ The number of hours of sleep Nina gets per week = 25 hours + 20 hours = 45 hours

The number of hours of sleep Nina gets per week = 45 hours

To better concentrate on schoolwork, Nina could get a total of forty hours a week of sleep a week to increase the number of hours she spends weekly on her schoolwork by up to 5 hours (45 hours - 40 hours).

Answer:

nine to ten hours every night hope o helped bbbbbbbbbbbbbbbbbbbbyyyyyyyyyyyyeeeeeeeee

Step-by-step explanation:

Answer: C

Step-by-step explanation:

Answer: I think the answer is A.

Step-by-step explanation:

Answer:

C

Step-by-step explanation:

it would be 2/5 = 4/10 = 40/100 = 0.4 = 40%

8/19 or 42.1%

add all values up to a total, then find the percentage from that total.

8 + 2 + 1 + 3 + 5 = 19 balls total

8 tennis valls to 19 total.

8/19 or 42.1%

The phase diagrams provide a visual representation of the system's behavior by plotting the vector field and trajectories in the x-y plane.

The given system of differential equations is described by:

\(˙x = a - x^2˙y = x - y\)

To find the equilibria, we set ˙x and ˙y equal to zero:

\(a - x^2 = 0 -- > x^2 = a -- > x = ±√ax - y = 0 -- > y = x\)

So, the equilibria are (±√a, ±√a).

Now let's analyze the behavior of the system for different values of 'a'.

For a > 0:

In this case, there are two real equilibria, (√a, √a) and (-√a, -√a). We can observe that (√a, √a) is a stable node, as the eigenvalues of the linearized system around this point have negative real parts. On the other hand, (-√a, -√a) is a saddle point, as the eigenvalues have opposite signs (one positive and one negative).

For a < 0:

In this case, there are no real equilibria since √a and -√a are imaginary. Therefore, the system has no equilibrium points.

To visualize the phase diagrams for a = 1 and a = -1:

For a = 1:

The system has two real equilibria, (1, 1) and (-1, -1). The point (1, 1) is a stable node, and (-1, -1) is a saddle point. The phase diagram would show trajectories converging towards (1, 1).

For a = -1:

Since a < 0, there are no equilibrium points, and thus the phase diagram would show no fixed points or trajectories.

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Answer:

Cream = 3 cups

Chocolate = 6 cups

Step-by-step explanation:

Cream = 1 cup

Chocolate = 2 cups

Total = 3 cups

Cream : chocolate = 1 : 2

He uses 9 cups of these two ingredients. How many cups of chocolate does he use in this candy recipe?

Cream = ratio of cream/total ratio of total cups

= 1/3 of 9

= 1/3 × 9

= 3 cups

Cream = 3 cups

Chocolate = ratio of chocolate/total ratio of total cups

= 2/3 of 9

= 2/3 × 9

= 6 cups

Chocolate = 6 cups

A measure that results in drastically different ratings over time lacks test-retest reliability.

Test-retest reliability refers to the consistency of measurements taken over time. If a measure results in drastically different ratings over time, it indicates a lack of consistency and therefore, a lack of test-retest reliability. This means that the measure is not dependable or accurate in measuring what it intends to measure. For example, if a survey measuring job satisfaction is administered to the same group of employees at two different time points, and the results show a significant difference, it may be due to a lack of test-retest reliability. In this case, the survey may need to be revised or replaced with a more reliable measure.

Test-retest reliability is crucial in ensuring the accuracy and dependability of a measure. A lack of test-retest reliability can lead to inaccurate results and can undermine the validity of the measure.

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Answer:

(-11/24)

Step-by-step explanation:

  3         5

------- - -------

  8         6

 3(3)    5(4)

------- - -------

 8(3)     6(4)

  9        20       - 11

------- - ------- = -------

  24      24        24

I hope this helps!

For the first sample {2.038 2.054 2.053 2.055 2.059 2.059 2.009 2.042 2.053 2.047}, the process is still "in order," while for the second sample {2.022 1.997 2.044 2.044 2.032 2.045 2.045 2.047 2.030 2.044}, the process might be "out of order."

To determine whether the process is still "in order" or "out of order," we can compare the current sample of output to the known mean and standard deviation of the process.

For the first sample {2.038 2.054 2.053 2.055 2.059 2.059 2.009 2.042 2.053 2.047}:

Calculate the sample mean by summing up all the values in the sample and dividing by the number of values (n = 10):

Sample mean = (2.038 + 2.054 + 2.053 + 2.055 + 2.059 + 2.059 + 2.009 + 2.042 + 2.053 + 2.047) / 10 = 2.048.

Compare the sample mean to the known process mean (2.050):

The sample mean (2.048) is very close to the process mean (2.050), indicating that the process is still "in order."

Calculate the sample standard deviation using the formula:

Sample standard deviation = sqrt(sum((x - mean)^2) / (n - 1))

Using the formula with the sample values, we find the sample standard deviation to be approximately 0.019 liters.

Compare the sample standard deviation to the known process standard deviation (0.020):

The sample standard deviation (0.019) is very close to the process standard deviation (0.020), further supporting that the process is still "in order."

For the second sample {2.022 1.997 2.044 2.044 2.032 2.045 2.045 2.047 2.030 2.044}:

Calculate the sample mean:

Sample mean = (2.022 + 1.997 + 2.044 + 2.044 + 2.032 + 2.045 + 2.045 + 2.047 + 2.030 + 2.044) / 10 ≈ 2.034

Compare the sample mean to the process mean (2.050):

The sample mean (2.034) is noticeably different from the process mean (2.050), indicating that the process might be "out of order."

Calculate the sample standard deviation:

The sample standard deviation is approximately 0.019 liters.

Compare the sample standard deviation to the process standard deviation (0.020):

The sample standard deviation (0.019) is similar to the process standard deviation (0.020), suggesting that the process is still "in order" in terms of variation.

In summary, for the first sample, the process is still "in order" as both the sample mean and sample standard deviation are close to the known process values.

However, for the second sample, the difference in the sample mean suggests that the process might be "out of order," even though the sample standard deviation remains within an acceptable range.

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Answer:

Germany - 90

Step-by-step explanation:

Here are the options to this question

Germany 90

Sweden   78

Japan       63

Canada    75

The appropriate answer should be a multiple of 2, 3, 5, 6, and 9. That is when the number is divided by 2, 3, 5, 6, and 9 it should have a remainder of zero.

90 / 2 = 45

90 / 3 = 30

90 / 5 = 18

90 / 6 = 15

90 / 9 = 10

Thus, the appropriate number is 90

When 78 is divided by 5 and 9, the remainder is not zero

When 63 is divided by 2, 5 and 6, the remainder is not zero

When 75 is divided by 2, 3, 6 and 9, the remainder is not zero

Answer:

1 and 5/18 I believe!

Step-by-step explanation:

Hope this helps

Answer:

0.74

Step-by-step explanation:

This is the correct answer. The reason is that 23/24 equals 0.9583. Next, when you divide 18/14, the answer is 1.29. When you divide 0.9583/1.29, the answer is 0.74

a) The forecasted number of disk drives to be made next year is 210.

b) The mean squared error (MSE) when using linear regression is 160.

c) The mean absolute percent error (MAPE) when using linear regression is approximately 7.51%.

Let's calculate the linear regression line using the given data points. We will use the least squares method to find the equation of the line:

Year (x)     Disk Drives (y)

1                   140

2                 160

3                 190

4                 200

5                210

Now calculate the means of x and y:

X = (1 + 2 + 3 + 4 + 5) / 5 = 3

Y= (140 + 160 + 190 + 200 + 210) / 5 = 180

The deviations from the means (dx and dy):

dx = (1 - 3, 2 - 3, 3 - 3, 4 - 3, 5 - 3) = (-2, -1, 0, 1, 2)

dy = (140 - 180, 160 - 180, 190 - 180, 200 - 180, 210 - 180)

= (-40, -20, 10, 20, 30)

The sums of squares (Sxx and Sxy):

Sxx = Σ(dx²) = (-2)² + (-1)² + 0² + 1² + 2² = 10

Sxy = Σ(dx × dy) = (-2× -40) + (-1 × -20) + (0 × 10) + (1 × 20) + (2× 30)

= 100

Now find the slope (b):

b = Sxy / Sxx = 100 / 10 = 10

Find the intercept (a):

a = Y - (b × X) = 180 - (10 × 3)

= 180 - 30

= 150

Now we have the equation of the regression line:

y = a + bx

y = 150 + 10x

To forecast the number of disk drives to be made next year (year 6), we substitute x = 6 into the equation:

y = 150 + 10×6

y = 150 + 60

y = 210

Therefore, the forecasted number of disk drives to be made next year is 210.

b) To compute the mean squared error (MSE) when using linear regression.

we need to calculate the residuals (differences between the actual and predicted values) for each data point, square them, and find the average.

Let Year (x), Disk Drives (y), Predicted (Y), Residual (d = y - Y), Residual Squared (d²)

X        y         Y          d            d²

1       140      160        -20      400

2      160      170        -10        100

3       190     180         10         100

4       200    190         10         100

5        210    200        10         100

MSE = Σ(d²) / n

= (400 + 100 + 100 + 100 + 100) / 5

= 800 / 5

= 160

(c)To compute the mean absolute percent error (MAPE), we need to calculate the absolute percent error for each data point, find the average, and express it as a percentage.

Year  Disk Drives  Predicted  Absolute Error  Percent Error

1              140               160             20                     14.29%

2             160               170             10                       6.25%

3             190               180             10                       5.26%

4             200              190             10                       5.00%

5             210              200             10                        4.76%

MAPE = Σ(|d| / y × 100) / n

= (14.29% + 6.25% + 5.26% + 5.00% + 4.76%) / 5

= 7.51%

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Considering computational complexity alone, the forward stepwise selection approach is preferred over the best subset selection approach. The statement is True.

Subset selection procedures involve trying out different combinations of predictors to find the best subset that provides the most accurate model. There are two commonly used subset selection approaches: best subset selection and forward stepwise selection.

In best subset selection, all possible subsets of predictors are considered, and the model with the best subset is selected based on some criterion (e.g., highest R-squared, lowest AIC, etc.). This approach involves a comprehensive search through all possible subsets, which can be computationally intensive, especially when the number of predictors is large. As the number of predictors increases, the computational complexity of best subset selection grows exponentially.

On the other hand, forward stepwise selection starts with an empty model and iteratively adds predictors one by one, selecting the predictor that improves the model the most at each step. This approach is less computationally complex than best subset selection because it explores a smaller number of combinations. Forward stepwise selection has a computational complexity of O(k^2n), where k is the number of predictors and n is the number of observations. It is much more efficient than the exponential complexity of best subset selection.

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Answer:

x = 73

General Formulas and Concepts:

Step-by-step explanation:

Step 1: Define equation

(180 - x) + (90 - x) = 124

Step 2: Solve for x

Step 3: Check

Plug in x to verify it's a solution.

Answer:

Step-by-step explanation:

To solve the system of equations algebraically, we need to substitute the second equation into the first equation and solve for x:

y = 4x – 5 (equation 1)

y = -3 (equation 2)

Substitute equation 2 into equation 1:

-3 = 4x – 5

Add 5 to both sides:

2 = 4x

Divide both sides by 4:

x = 1/2

Now, we can substitute this value of x back into either equation to find y:

y = 4(1/2) – 5 = -3

Therefore, the solution to the system of equations is (1/2, -3).

To verify this solution using the graph, we can plot the two equations on the same set of axes:

y = 4x – 5 (red line)

y = -3 (blue line)

The two lines intersect at the point (1/2, -3), confirming our solution.

Therefore, the answer is (B) (1/2, -3).

Answer:

C. (3,-3)

Step-by-step explanation:

5x + 3y = 6

5(3) + 3(-3) = 6

15 + (-9) = 6

therefore point lies on the line

The probability that student chosen at random is 16 years is 0.28.

The table shows the distribution of student by age in a high school with 1500 students. Therefore, the probability that randomly chosen student is  16 years can be found as follows:

Therefore,

probability = number of favourable outcome to age / total number of possible outcome

Hence,

probability that student chosen at random is 16 years =  420 / 150

probability that student chosen at random is 16 years = 0.28

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Answer:

Y-2x=8

Y-x=8/2

Yx=4

Maths gradients

Answer:

b

Step-by-step explanation:

Using the tree diagram (which is a probability tool), the percentage of all graduates who plan to enter the workforce and reside locally is 12%.

What is the percentage?

The percentage refers to the proportion or ratio of a number or value to another.

Percentages are computed by dividing the numerator (the smaller number) by the denominator (the whole number) and multiplying the result by 100.

The percentage of high school graduates who enter college = 70%

The percentage of high school graduates who enter the workforce = 30% (1 - 70%).

The percentage of high school graduates who enter the workforce, moving out of state = 60%

The percentage of high school graduates who enter the workforce but reside locally = 40% (1 - 60%).

The percentage of high school graduates working and residing locally = 12% (30% x 40%).

Thus, the tree diagram shows that the percentage of high school graduates choosing to work and reside locally is 12%.

So, the manager should get all the required water from the local reservoir, resulting in a minimum daily water cost of $5510.

To minimize the daily water costs for the city, the water-supply manager needs to determine how much water to get from each source while meeting the minimum requirement of 19 million gallons per day. Let's denote the amount of water drawn from the local reservoir as R (in million gallons) and the amount of water drawn from the pipeline as P (in million gallons).

Given the constraints:

R ≤ 20 (maximum daily yield of the reservoir)

P ≥ 7 (minimum daily yield of the pipeline)

R + P ≥ 19 (minimum requirement of 19 million gallons)

We need to find the values of R and P that satisfy these constraints while minimizing the daily water costs.

Let's calculate the costs for each source:

Cost of 1 million gallons of reservoir water = $290

Cost of 1 million gallons of pipeline water = $365

The total daily cost can be expressed as:

Total Cost = (Cost of reservoir water per million gallons) * R + (Cost of pipeline water per million gallons) * P

To minimize the total cost, we can use linear programming techniques or analyze the possible combinations. In this case, since the costs per million gallons are provided, we can directly compare the costs and evaluate the options.

Let's consider a few scenarios:

If all the water (19 million gallons) is drawn from the reservoir:

Total Cost = (Cost of reservoir water per million gallons) * 19 = $290 * 19

If all the water (19 million gallons) is drawn from the pipeline:

Total Cost = (Cost of pipeline water per million gallons) * 19 = $365 * 19

If some water is drawn from the reservoir and the remaining from the pipeline:  Since the minimum requirement is 19 million gallons, the pipeline must supply at least 19 - 20 = -1 million gallons, which is not possible. Thus, this scenario is not valid. Therefore, to minimize the daily water costs, the manager should draw all 19 million gallons of water from the local reservoir. The minimum daily water cost would be:

Minimum Daily Water Cost = (Cost of reservoir water per million gallons) * 19 = $290 * 19 = $5510.

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The probability that a person has a disease given that they test positive, when 0.4% of the population has the disease and the test is positive with probability 0.99 if they have the disease and 0.03 if they don't have it, is 0.116 or about 11.6%.

Let D be the event that the person has the disease and T be the event that the person tests positive. We need to calculate P(D|T), the probability that the person has the disease given that they test positive.

Using Bayes' theorem, we have

P(D|T) = P(T|D) * P(D) / P(T)

where P(T|D) is the probability of testing positive given that the person has the disease, P(D) is the prior probability of having the disease, and P(T) is the total probability of testing positive, which can be calculated as

P(T) = P(T|D) * P(D) + P(T|D') * P(D')

where P(T|D') is the probability of testing positive given that the person does not have the disease, and P(D') is the complement of P(D), which is the probability of not having the disease.

Substituting the given values, we get

P(D|T) = (0.99 * 0.004) / [(0.99 * 0.004) + (0.03 * 0.996)]

= 0.116

Therefore, the probability that the person has the disease given that they test positive is 0.116 or about 11.6%.

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Answer: (-4,0)

Step-by-step explanation: