Find the unit rate. Round your answer to the nearest hundredth.
3500 calories for 6 servings of pie

The bias score, which is also known as the mean squared error, is a measure of the difference between the predicted values and the actual values.

A bias score of 0.8 means that, on average, the model's predictions are off by 0.8. This could indicate that the model is biased, but it is difficult to say without more context. There are many factors that can contribute to a model being biased, including the quality of the training data and the complexity of the model. It is important to carefully evaluate the bias score and other performance metrics when assessing the effectiveness of a model.

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Answer:

D. 29

Step-by-step explanation:

just did the test and got it correct. Edmentum, Plato.

Answer:

r² = (9 - 4)² + (6 - 4)² = 5² + 2² = 25 + 4 = 29

So the equation of this circle is

(x - 4)² + (y - 4)² = 29

In an observational study, the statement that a cause and effect can be determined is false.

Observational studies simply establish associations between predictor and outcome variables. Observational studies cannot confirm that an association contemplates cause and effect.

In observational studies, confounding variables may explain an observed relationship between predictor and outcome variables.

In an observational study, a cause and effect cannot be determined. Observational studies are used to gather data about a particular population or phenomenon, but they do not allow for the determination of cause-and-effect relationships.

This is because observational studies do not control the variables that are being studied and, therefore, cannot determine the relationship between two variables.

In order to determine cause and effect, a controlled experiment is needed in which the variables are manipulated, and their effects are observed.

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A 50 percent increase in Earth's albedo, which refers to the reflectivity of its surface, would lead to a decrease in average surface temperatures.

Albedo plays a crucial role in determining how much of the sun's energy is absorbed or reflected by the Earth. The given information states that approximately 30 percent of the sun's energy is currently reflected back into space. If Earth's albedo increases by 50 percent, meaning more energy is reflected, it would result in less energy being absorbed by the Earth's surface and atmosphere.

The increased albedo would cause a higher percentage of the incoming solar radiation to be reflected and scattered back into space. With less energy being absorbed, the average surface temperatures would decrease. This is because less solar energy would be available to warm the Earth's surface and drive atmospheric processes that contribute to temperature regulation. Therefore, a 50 percent increase in Earth's albedo would likely lead to a cooling effect and lower average surface temperatures on our planet.

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The point prevalence of brilliance at the end of Week 1 is 0.08 or 8%.

The point prevalence of brilliance at the end of Week 2 is 0.17 or 17%.

The point prevalence of brilliance at the end of Week 3 is 0.33 or 33%.

Using person-weeks as denominator, the incidence of brilliance over the course of the 10-week course is 0.017 or 1.7%

In epidemiology context, brilliance can be calculated through calculating point prevalence, cumulative incidence, and incidence rate. The provided data table can be used to determine the point prevalence, incidence, and incidence rate of brilliance among PHE 450 students. So, the calculations of point prevalence, cumulative incidence, and incidence rate based on the provided data are as follows:

The point prevalence of brilliance at the end of Week 1 can be calculated by the following formula; Point prevalence = Total number of existing cases at a given time ÷ Total population at that time

Student #8 was the only existing case of brilliance at the beginning of Week 1, so the point prevalence of brilliance at the end of Week 1 is; Point prevalence = 1 ÷ 12 = 0.08 or 8%.

The point prevalence of brilliance at the end of Week 2 can be calculated by the following formula; Point prevalence = Total number of existing cases at a given time ÷ Total population at that time

Student #3 and Student #8 were existing cases of brilliance at the beginning of Week 2, so the point prevalence of brilliance at the end of Week 2 is; Point prevalence = 2 ÷ 12 = 0.17 or 17%.

The point prevalence of brilliance at the end of Week 3 can be calculated by the following formula; Point prevalence = Total number of existing cases at a given time ÷ Total population at that time

Student #3, #4, #6, and #8 were existing cases of brilliance at the beginning of Week 3, so the point prevalence of brilliance at the end of Week 3 is; Point prevalence = 4 ÷ 12 = 0.33 or 33%.

The incidence of brilliance can be calculated by the following formula; Incidence = Total number of new cases ÷ Total person-weeks of observation

Student #5 and Student #7 developed brilliance during the 10-week course, so the incidence of brilliance over the course of the 10-week course is; Incidence = 2 ÷ 120 = 0.017 or 1.7%.

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Answer:

3/8

Step-by-step explanation:

T = tails

H = heads

The possibilities of the coin flip are as follows: TTT, TTH, THH, HHH, HHT, HTT, HTH, THT

Out of these eight possibilities, three involve two heads and one tail (HHT, HTH, and THH).

That means that the probability of landing two heads and one tail is 3/8.

I hope this helps! Have a great day!

If we're tossing three coins that all have a 50% chance of getting tails or head, all we have to do is...

2 * 2 * 2 = 8

Now we divide it by 3...(The two heads and one tail)

3 * 8 = 0.375

0.375 * 100 = 37.5% or 3/8

Your answer is 3/8, I hope this helps!

The mean (μ) for the given binomial distribution is 0.50.

To calculate the mean (μ) of a binomial distribution, we multiply the number of trials (n) by the probability of success in a single trial (π). Let's examine each scenario in detail:

a. When n = 5 and π = 0.10:

μ = 5 * 0.10

  = 0.50

For this binomial distribution, with 5 trials and a success probability of 0.10, the mean (μ) is 0.50. This means that, on average, we would expect to have 0.50 successes per trial.

b. When n = 3 and π = 0.40:

μ = 3 * 0.40

  = 1.20

In this case, the mean (μ) of the binomial distribution is 1.20. It indicates that, on average, there would be 1.20 successes per trial when there are 3 trials and a success probability of 0.40.

c. When n = 5 and π = 0.50:

μ = 5 * 0.50

  = 2.50

For a binomial distribution with 5 trials and a success probability of 0.50, the mean (μ) is 2.50. This means that, on average, we would expect to have 2.50 successes per trial.

d. When n = 3 and π = 0.80:

μ = 3 * 0.80

  = 2.40

In this scenario, the mean (μ) of the binomial distribution is 2.40. It suggests that, on average, we would expect to have 2.40 successes per trial when there are 3 trials and a success probability of 0.80.

The mean (μ) provides a measure of the central tendency or the average number of successes in a binomial distribution based on the given parameters.

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Answer:0.35

Step-by-step explanation:you will have to multiply 70% by 50% and that would give you your answer

Step-by-step explanation:

Parallel lines cut by a transversal coloring activity is an activity that helps students understand the pattern of angles when parallel lines are cut by a transversal. The activity involves coloring the angles formed by the parallel lines and the transversal in different colors. This helps students identify the different types of angles formed and their relationships with each other.

Based on the October 2020 election poll of 1,000 people, where 49 percent favored Joe Biden and 51 percent favored Donald Trump, with a 2 percent margin of error, we can identify statements that could potentially be true.

These statements would need to account for the margin of error and the inherent uncertainty in polling data.

Given a margin of error of 2 percent, we can consider statements that fall within this range of uncertainty. For example, it could be true that the actual support for Joe Biden is between 47 percent and 51 percent, considering the margin of error. Similarly, the actual support for Donald Trump could be between 49 percent and 53 percent.

Additionally, it could be true that the actual support for both candidates is equal, as the difference of 2 percentage points is within the margin of error. This means that the true level of support for Joe Biden and Donald Trump might be statistically tied, considering the margin of error and the inherent variability in polling data.

In summary, the statements that could be true based on the given information include the range of support for each candidate within the margin of error and the possibility of a statistical tie between the two candidates.

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Given a 2% margin of error in the poll, it could be true that Biden or Trump had the highest actual percentage of voter preference or there might be a tie. The margin of error indicates the range within which the true percentage (within the total population) is likely to fall.

When dealing with polling data, given here is an October 2020 election poll of 1,000 people that indicates 49 percent of voters favored Joe Biden and 51 percent favored Donald Trump, with a 2 percent margin of error. The margin of error means that if the same poll were conducted many times, the true percentage (within the total population) favoring each candidate could fall within 2 points of the percentages reported in this poll; so, anywhere from 47%-51% for Biden and 49%-53% for Trump. Therefore, it could be true that, in reality, more people within the total population favored Biden than Trump, more people favored Trump than Biden, or that there was essentially a tie. As an example, if we had other information like demographic data showing that 57 percent of women and 60 percent of under-thirty voters favored Biden, it could help to understand the dynamics of the overall vote.

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Answer:

not linear

Step-by-step explanation:

Answer:

Perimeter = 10

Step-by-step explanation:

Horizontally 3 units; vertically 2 units.

If h is horizontal measure, and v is vertical measure, then perimeter is 2(h+v) and area is hv.

[4] The Perimeter of the rectangle is how many units?

Perimeter formula ; 2(h+v)

2(3+2) = 10

~Learn with Lenvy~

In the graph of the simple linear regression equation, the parameter ß1 is the slope of the true regression line.

The simple linear regression equation represents a linear relationship between a dependent variable and an independent variable. It can be written as y = ß0 + ß1x, where ß0 is the intercept and ß1 is the slope of the regression line.

The slope (ß1) determines the rate of change in the dependent variable (y) for each unit change in the independent variable (x). It represents the steepness or inclination of the regression line. The sign of ß1 indicates whether the line has a positive or negative slope, indicating the direction of the relationship between the variables.

Thus, in the context of the simple linear regression equation, the parameter ß1 is the slope of the true regression line.

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Answer:

Years 3-4 and the percentage change was by 8%. Please vote Brainliest!

Step-by-step explanation:

Answer:

C the greatest growth was between 3 and 4 and about 8%

Step-by-step explanation:

The value of h(-5) in the given function, h(x) = -3|x - 1| + 4, is h(-5) = -14

From the question, we are to evaluate the given function for the given value

The given function is

h(x) = -3|x - 1| + 4

We are to determine the value of h(-5).

To determine the value of h(-5), we will substitute -5 for x in the given function.

That is,

h(x) = -3|x - 1| + 4

h(-5) = -3|(-5) - 1| + 4

h(-5) = -3|-5 - 1| + 4

h(-5) = -3|-6| + 4

h(-5) = -3(6) + 4

h(-5) = -18 + 4

h(-5) = -14

Hence, the value of h(-5) is -14

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Answer: I do not understand

Step-by-step explanation:

The missing side length for the two similar triangle is (x = 7/3).

In the given question, two triangle are given.

As, both triangles are similar. Then, the ratio of their corresponding sides are equal.

Thus,

7/12 = x/4

x = 3/7

Therefore, the missing side length x for the two similar triangles is 7/3.

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Answer:

5

Step-by-step explanation:

all of the others are lower than 0

Answer: yes I do believe

Answer:

16

Step-by-step explanation:

distance formula:

d=√((x_2-x_1)²+(y_2-y_1)²)

Answer:

It is A

Step-by-step explanation:

You have 4 muffins or 4m with a 2 dollar off coupon so therefore it is 4m-2

Answer:

4m-2

Step-by-step explanation:

The cost, m, is subtracted by 2. There are 4 muffins being bought, so the term would be 4m, making the equation 4m-2.

So, Antti must maintain an average speed of 8 kilometers per hour for the last 8 kilometers of the race in order to finish in one hour.

To finish the 10 kilometer race in one hour, Antti must maintain an average speed of 10 kilometers per hour for the entire race. Since he has already completed 2 kilometers at an average speed of 12 kilometers per hour, he must make up for that extra speed by running the last 8 kilometers at a slower pace.

To find out what average speed he must maintain for the last 8 kilometers to finish in one hour, we can use the formula:

(distance) / (time) = (speed)

So, 8 / 1 = 8 kilometers per hour

Antti must maintain an average speed of 8 kilometers per hour for the last 8 kilometers of the race in order to finish in one hour.

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\(d = \frac{d(10 {}^{k + p} - 10 {}^{k}) }{(10 {}^{k + p} - 10 {}^{k})} \)

where

Step-by-step explanation:

Greetings !

use the above formula to change any decimal into fraction form

Thus, plug in the value and solve

Hope it helps !

To test the difference between two independent population means with two samples, you need to calculate the degrees of freedom (df). Here's a step-by-step explanation:

1. Identify the sample sizes: The first sample has a size of 28 (n1 = 28), and the second sample has a size of 27 (n2 = 27).

2. Calculate the degrees of freedom for each sample: For each sample, subtract 1 from the sample size. For sample 1, df1 = n1 - 1 = 28 - 1 = 27. For sample 2, df2 = n2 - 1 = 27 - 1 = 26.

3. Combine the degrees of freedom: Add the degrees of freedom from each sample together to get the total degrees of freedom: df = df1 + df2 = 27 + 26 = 53.

In this case, you will use 53 degrees of freedom to find the critical value for testing the difference between the two independent population means.

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The standard deviation of the sampling distribution of X is approximately 0.0704.

The standard deviation of the sampling distribution of X can be calculated using the formula:

\(\sigma = \sqrt{((p * (1 - p)) / n)}\)

Where:

σ is the standard deviation of the sampling distribution of X

p is the proportion of voters that would vote for the incumbent (46% or 0.46)

n is the sample size (50)

Plugging in the values:

\(\sigma = \sqrt{((0.46 * (1 - 0.46)) / 50)} \\\sigma = \sqrt{(0.2484 / 50)} \\\sigma = \sqrt{(0.004968)} \\\sigma = 0.0704\)

The standard deviation of the sampling distribution of X is approximately 0.0704.

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Answer:

48.5 lbs

Step-by-step explanation:

lkg = 2.205 lbs

22kgs = 2.205 x 22

= 48.51 lbs

= 48.5 lbs (to the nearest tenth)

22 kilograms is equivalent to 48.5 pounds.

Given that we need to convert 22 kilograms to pounds.

We have,

1 lb = 0.4536 kg

1 kg = 2.205 lbs

To convert kilograms to pounds, you can use the conversion factor that 1 kilogram is equal to 2.205 pounds.

Therefore, to convert 22 kilograms to pounds, you can multiply 22 by 2.205:

22 kg x 2.205 lbs/kg = 48.51 lbs

Rounded to the nearest tenth, 22 kilograms is equivalent to 48.5 pounds.

Hence 22 kilograms is equivalent to 48.5 pounds.

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The least positive number n that satisfies all of the conditions is n = 60.

To find the least positive number n that satisfies all of these conditions, we need to find the least common multiple (LCM) of the numbers 1, 2, 3, 4, and 5. The LCM is the smallest positive number that is divisible by all of these numbers.

To find the LCM, we can list the prime factors of each number and then take the highest power of each prime factor that appears in any of the numbers. The prime factorization of each number is:

1: 1

2: 2

3: 3

4: 2 x 2

5: 5

The highest power of each prime factor that appears in any of the numbers is:

2: 2 x 2

3: 3

5: 5

So the LCM is:

\(2 \times 2 \times 3 \times 5$ = 60\)

Therefore, the least positive number n that satisfies all of the conditions is n = 60.

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The probabilities of having 0, 1, 2, and 3 access lines in use are approximately 0.000048, 0.001636, 0.011072, and 0.047368, respectively. These probabilities are calculated using the Poisson distribution formula based on the given mean arrival rate of 34 calls per hour and a service rate of 18 calls per hour.

To determine the probabilities of having 0, 1, 2, and 3 access lines in use, we can use the Poisson distribution formula. Given a mean arrival rate of 34 calls per hour and a service rate of 18 calls per hour, we can calculate the probabilities as follows:

For 0 access lines in use, the probability can be calculated using the formula \(P(X = 0) = \frac {e^{-\lambda} * \lambda^0}{0!}\) where λ is the mean arrival rate. Substituting the values, we have \(P(X = 0) = e^{-34} * (34^0) / 0! = 0.000048\).

Similarly, for 1, 2, and 3 access lines in use, we can calculate the probabilities using the same formula. The probabilities are:

\(P(X = 1) = e^{-34} * (34^1) / 1! = 0.001636\)
\(P(X = 2) = e^{-34} * (34^2) / 2! = 0.011072\)
\(P(X = 3) = e^{-34} * (34^3) / 3! = 0.047368\)

Therefore, the probabilities of having 0, 1, 2, and 3 access lines in use are approximately 0.000048, 0.001636, 0.011072, and 0.047368, respectively.

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