What is an equation of a parabola with the given vertex and focus.

The collapse of a star can be a cataclysmic event, and in this case, the sudden decrease in radius from 1.00 x 10^8 m to 1.00 x 10^4 m indicates a significant change in the star's physical structure.

The period of 30.0 days suggests that the star is likely a main-sequence star, which has a predictable rate of energy output based on its size and temperature.

The collapse of the star could be caused by a number of factors, such as depletion of its nuclear fuel, or the sudden release of energy due to a supernova explosion.

Whatever the cause, the sudden decrease in radius would have a profound effect on the star's gravitational field, which could in turn affect the behavior of any planets or other bodies orbiting around it.

One way to estimate the effect of the collapse on the star's gravitational field is to use the equation for the gravitational force between two objects, which depends on the masses and distance between them. The star's mass is not given in this problem, but we can assume that it is still roughly the same as before the collapse.

Using this assumption and the given values for the initial and final radii, we can estimate that the gravitational force at the surface of the star would have increased by a factor of approximately (1.00 x 10^4 m / 1.00 x 10^8 m)^2, or 1.00 x 10^-12.

Overall, the collapse of a star is a complex process that involves a range of physical and astronomical factors. While the sudden decrease in radius may be dramatic, it is only one aspect of the many changes that occur during such an event.

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The correlation between x₁ + x₂ and x₂ + x₃ is 1

The correlation between x₁ +x₂ and x₃ + x₄ is 0

Correlation is a measure of the strength and direction of the linear relationship between two random variables.

It is a statistical concept that is widely used in data analysis and research to explore and quantify the association between two variables.

Here  we have

x₁ x₂ x₃ and x₄ are (pairwise) uncorrelated random variables, each having to mean of 0 and variance of 1,

(a) x₁ + x₂ and x₂ + x₃.

We have

Cov(x₁+ x₂, x₂ + x₃) = Cov(x₁, x₂) + Cov(x₁, x₃) + Cov(x₂, x₂) + Cov(x₂, x₃)

= 0 + 0 + Var(x₂) + 0 = 1.

Since, Var(x₁ + x₂) = Var(x₁) + Var(x₂) + 2 Cov(x₁, x₂) = 1 + 1 + 2 · 0 = 2.

Similarly Var(x₂ + x₃) = 0.

So the correlation between x₁ + x₂ and x₂+ x₃ is

ρ(x₁ + x₂, x₂ + x₃) = Cov(x₁ + x₂, x₂ + x₃)

p = Cov(x₁ + x₂, x₂ + x₃)/ √Var(x₁ + x₂) Var(x₂ + x₃) = 1/√2× 2 = 1/2

(b) x₁+ x₂ and x₃ + x₄.

Cov(x₁ + x₂, x₃+ x₄) = Cov(x₁, x₃) + Cov(x₁, x₄) + Cov(x₂, x₃) + Cov(x₂, x₄)

= 0 + 0 + 0 + 0 = 0

The correlation between x₁ +x₂ and x₃ + x₄ is 0

Therefore,

The correlation between x₁ + x₂ and x₂ + x₃ is 1

The correlation between x₁ +x₂ and x₃ + x₄ is 0

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The expressions are as follows:

A' = {0,2,6,8,9}

B' = {0,1,7,8,9}

C' = {1,3,5,7}

(A ∩ B)' = {0,1,2,6,7,8,9}

A' ∩ B' = {0,8,9}

A' U B' = {0,1,2,6,7,8,9}

A U (B ∩ C) = {1,2,3,4,5,6,7}

Set theory is a branch of mathematical logic that studies set, which informally are collections of objects. Although any type of object can be collected into a set, set theory is applied most often to objects that are relevant to mathematics. The language of set theory can be used to define nearly all mathematical objects.

Let's break down the given expressions using set theory and the provided sets:

U = {0,1,2,3,4,5,6,7,8,9} (Universe)

A = {1,3,4,5,7}

B = {2,3,4,5,6}

C = {0,2,4,6,8,9}

A' denotes the complement of A, which means all the elements that are not in set A but are in the universe U.

A' = {0,2,6,8,9}

B' denotes the complement of B, which means all the elements that are not in set B but are in the universe U.

B' = {0,1,7,8,9}

C' denotes the complement of C, which means all the elements that are not in set C but are in the universe U.

C' = {1,3,5,7}

(A ∩ B)' denotes the complement of the intersection of sets A and B, which means all the elements that are not common in sets A and B but are in the universe U.

(A ∩ B) = {3,4,5}

(A ∩ B)' = {0,1,2,6,7,8,9}

A' ∩ B' denotes the intersection of sets A' and B', which means all the elements that are in both set A' and set B'.

A' ∩ B' = {0,8,9}

A' U B' denotes the union of sets A' and B', which means all the elements that are in either set A' or set B' or both.

A' U B' = {0,1,2,6,7,8,9}

A U (B ∩ C) denotes the union of set A and the intersection of sets B and C, which means all the elements that are in either set A or in the intersection of sets B and C or both.

(B ∩ C) = {2,4,6}

A U (B ∩ C) = {1,2,3,4,5,6,7}

Therefore, the expressions are as follows:

A' = {0,2,6,8,9}

B' = {0,1,7,8,9}

C' = {1,3,5,7}

(A ∩ B)' = {0,1,2,6,7,8,9}

A' ∩ B' = {0,8,9}

A' U B' = {0,1,2,6,7,8,9}

A U (B ∩ C) = {1,2,3,4,5,6,7}

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c. The statement "The constant variance condition can be somewhat relaxed when the sample sizes are relatively consistent across groups" is generally false in ANOVA.

In ANOVA, the constant variance assumption, also known as homogeneity of variance, states that the population variances of the dependent variable are equal across all levels of the independent variable. Violation of this assumption can lead to biased or inefficient estimates of the treatment effects. While there are some methods that can be used to address violations of this assumption, such as using robust standard errors or transforming the dependent variable, relaxing this assumption based on sample sizes is generally not recommended.

d. The statement "The independence assumption can be relaxed when the total sample size is large" is false in ANOVA.

The independence assumption in ANOVA states that the observations within each group or level of the independent variable are independent of each other. This assumption is important because violations of independence can lead to increased Type I error rates or inaccurate estimates of the treatment effects. The total sample size, while important for the power of the analysis, does not affect the independence assumption. Each observation should still be independent of all other observations within each group, regardless of the total sample size.

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A numerical description of the outcome of an experiment is called a descriptive statistic.

Descriptive statistics are used to summarise and describe the data collected from an experiment, such as measures of central tendency (mean, median, mode) and measures of variability (range, standard deviation). These statistics help researchers understand the characteristics of their data and make inferences about the larger population from which the sample was taken. A random variable is a variable that takes on different values based on the outcome of a probability experiment. The probability function describes the likelihood of each possible outcome of the random variable. Variance measures how spread out the data is from the mean and is used in statistical analyses such as hypothesis testing and regression analysis.

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The period of the pendulum (t) is approximately 4.77 seconds.

The formula for a basic pendulum's period is

T = 2π√(L/g)

where L is the pendulum's length and g is its gravitational acceleration.

Substituting the given values, we get:

T = 2π√(5.64/9.8)

Simplifying the expression inside the square root, we get:

T = 2π√(0.5755)

Calculating the square root, we get:

T = 2π(0.759)

Multiplying by 2 and π, we get:

T = 4.77 seconds (rounded to two decimal places)

Therefore, the period of the pendulum is approximately 4.77 seconds.

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Part A: Sky View - median = 5.5, Riverside - median = 5.5

Part B: Sky View - range = 99, Riverside - range = 78

Part C: Sky View has a larger class size on average (12 vs 10), so it may be a better choice if a larger class size is desired.

Part A: Measures of Center

For Sky View School:

Mean: sum of values / number of values [tex]= (5 + 6 + 99 + 7 + 2 + 0) / 6 = 119 / 6 = 19.83[/tex]

Median: arrange the values in ascending order: 0, 2, 5, 6, 7, 99. The median is 6.5.

Mode: there is no mode as all values occur only once.

For Riverside School:

Mean: sum of values / number of values [tex]= (1 + 0 + 2 + 4 + 5 + 6 + 78 + 7 + 6 + 5 + 5 + 5 + 4 + 3 + 1 + 0) / 16 = 133 / 16 = 8.31[/tex]Median: The median is equal to the average of each of the middle values [tex](5 + 5 / 2 = 5)[/tex], which is 5.

Mode: the mode is 5 as it occurs most frequently.

Part B: Measures of Variability

For Sky View School:

Range: maximum value - minimum value = 99 - 0 = 99

Variance: [tex]((5-19.83)^2 + (6-19.83)^2 + (99-19.83)^2 + (7-19.83)^2 + (2-19.83)^2 + (0-19.83)^2) / (6-1) = 2134.4[/tex].

Standard deviation: approximately 46.2.

For Riverside School:

Range: maximum value - minimum value = 78 - 0 = 78

Variance: [tex]((1-8.31)^2 + (0-8.31)^2 + (2-8.31)^2 + (4-8.31)^2 + (5-8.31)^2 + (6-8.31)^2 + (78-8.31)^2 + (7-8.31)^2 + (6-8.31)^2 + (5-8.31)^2 + (5-8.31)^2 + (5-8.31)^2 + (4-8.31)^2 + (3-8.31)^2 + (1-8.31)^2 + (0-8.31)^2) / (16-1) = 422.3.[/tex]

Standard deviation: approximately 20.55.

Part C: Answer with Explanation

If you are interested in a larger class size, Riverside School may be a better choice. This is because the mean and median class sizes at Riverside School are both smaller than those at Sky View School, indicating that the typical class size is smaller at Riverside. Additionally, the range and standard deviation of class sizes at Riverside School are smaller than those

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The length of the curve is [tex]e^ \pi[/tex] - 1 units.

To find the length of the curve [tex]x = e^t cos(t), y = e^tsin(t)[/tex], where 0 ≤ t ≤ π.

In this case, the curve is defined by the equations [tex]x = e^t cos(t)[/tex] and [tex]y = e^t sin(t)[/tex], where t is the variable that represents the parameter along the curve.

To find the length of this curve, we can use a formula known as the arc length formula.

L = ∫[a,b] √〖[dx/dt]〗² + 〖[dy/dt]² dt

where L represents the length of the curve, a and b are the starting and ending values of the parameter, dx/dt and dy/dt are the derivatives of x and y with respect to t.

To find the derivatives dx/dt and dy/dt. Using the product rule and chain rule of differentiation, we get:

[tex]dx/dt = e^tcos(t) - e^t sin(t) dy/dt = e^t sin(t) + e^t cos(t)[/tex]

Substituting these expressions into the arc length formula and simplifying, we get: L = ∫[0,π] [tex]e^tdt[/tex]

Integrating this expression with respect to t, we get: L = [tex]e^\pi[/tex]- 1

So the length of the curve is [tex]e^ \pi[/tex] - 1 units.

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The margin of error associated with the 95% confidence interval for the population mean volume is: D. 5.62.

To calculate the 95% confidence interval for the population mean volume, we can use the formula:

CI = x ± (t * (s/√n))

Where CI represents the confidence interval, x is the sample mean, t is the t-score associated with the desired confidence level (95%), s is the sample standard deviation, and n is the sample size.

In this case, x = 64 cc, s = 12 cc, and n = 20 orangutans. We need to find the t-score for a 95% confidence interval with 19 degrees of freedom (n-1). Using a t-table, we find that the t-score is approximately 2.093.

Now we can calculate the margin of error:

Margin of Error = t * (s/√n) = 2.093 * (12/√20) ≈ 5.62

Therefore, the margin of error associated with the 95% confidence interval for the population mean volume is: D. 5.62.

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The missing coordinates are:

K = (10, 10)

L = (20, 10)

M = (30, 10)

Given the graph is a straight line on coordinate plane.

We know that in Cartesian Coordinate plane if the points are on a straight line parallel to any Axis that is X axis or Y axis then the ordinate or the y-value of the coordinates of that points are equal for all.

Here we can see that the given graph has a line parallel to X axis and it is 10 units upwards from the X axis.

And it is clear from the graph that the coordinates of the point on the graph are given by,

K = (10, 10)

L = (20, 10)

M = (30, 10)

Hence the missing coordinates are 10, 10, 10.

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The question is incomplete. The complete question will be -

"K = (10,?) L = (?,20) M = (30,?) are on that line, too. Write their missing coordinates."

The average value of the function [tex]f(x) = x^{(1/2)[/tex] on the interval [0, 25] is 50.

An input and an output are connected by a function. It functions similarly to a machine with an input and an output. Additionally, the input and output are somehow connected. The traditional format for writing a function is f(x) "f(x) =... "

To find the average value fave of the function [tex]f(x) = x^{(1/2)[/tex] on the interval [0, 25], we need to use the following formula:

fave = (1/(b-a)) * ∫(a to b) f(x) dx

where a and b are the endpoints of the interval [0, 25].

Substituting the values for a, b, and f(x), we get:

fave = (1/(25-0)) * ∫(0 to 25) [tex]x^{(1/2)[/tex] dx

Using the power rule of integration, we can simplify the integral:

fave = (2/50) * [[tex]x^{(3/2)/(3/2)[/tex]] from 0 to 25

fave = (4/50) * [[tex]25^{(3/2)[/tex] - [tex]0^{(3/2)[/tex]]

fave = (4/50) * ([tex]25^{(3/2)[/tex])

fave = 10√25

fave = 10(5)

fave = 50

Therefore, the average value of the function [tex]f(x) = x^{(1/2)[/tex] on the interval [0, 25] is 50.

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The slope-intercept form for Angela's total cost of a pedicure and a massage as per the given data is equal to y = $0.75x + $35.

The slope of the line that represents the cost of the massage as a function of the number of minutes.

We know that a 20 minute massage costs $50, so the slope is,

slope = change in cost / change in minutes

         = ($50 - $35) / (20 - 0)

         = $15 / 20

         = $0.75 per minute

Now, let us use point-slope form to write the equation of the line,

y - $35 = $0.75(x)

where y is the total cost of the pedicure and massage,

$35 is the cost of the pedicure alone,

x is the number of minutes for the massage,

and $0.75 is the slope of the line.

Simplify this equation to slope-intercept form by adding $35 to both sides.

y = $0.75x + $35

Therefore, the equation in slope-intercept form for Angela's total cost of a pedicure and a massage is y = $0.75x + $35.

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The above question is incomplete, the complete question is:

Angela is getting a pedicure at a spa that also offers massages where customers pay by the minute. If Angela only gets a pedicure, it will cost her $35. If she pays for a 20 minute massage, it will cost her $50.

Write an equation in slope-intercept form where x represents the number of minutes for a massage and y represents Angela's total cost of a pedicure and a massage.

As per the inequality -0.4 < 0 which indicates that the low tide on Wednesday is also less than the typical low tide on Monday.

In this case, we can use the symbol < to indicate that the low tide on Tuesday morning is less than the low tide on Monday morning. This can be written as:

-0.8 < 0

The left-hand side of this inequality represents the low tide on Tuesday morning (-0.8 feet) and the right-hand side represents the typical low tide level on Monday morning (0 feet). The inequality indicates that the low tide on Tuesday is less than the typical low tide on Monday.

Similarly, we can compare the low tide on Wednesday morning to the low tide on Monday morning using the same inequality:

-0.4 < 0

In summary, we can use inequalities to compare the low tides on different days relative to a reference point. By using the typical low tide on Monday morning as the reference point, we can see that the low tides on Tuesday and Wednesday mornings are both lower than the typical low tide.

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The standard deviation of the sampling distribution of the sample means will be equal to the standard deviation of the population divided by the square root of the sample size. Therefore, if the population standard deviation is 50 and the sample size is 25, then the standard deviation of the sampling distribution of the sample means will be 10.

The Central Limit Theorem (CLT) states that the sampling distribution of the sample means will approach a normal distribution as the sample size increases, regardless of the shape of the population distribution. This means that even if the population distribution is not normal, the distribution of the sample means will still be approximately normal as long as the sample size is sufficiently large (usually, a sample size greater than or equal to 30 is considered large enough).

Additionally, according to the CLT, the mean of the sampling distribution of the sample means will be equal to the mean of the population from which the samples are drawn. In this case, since the population mean is 150, the mean of the sampling distribution of the sample means will also be 150.

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A 60,000 cubic millimeter box contains rubber balls with a radius of 15 millimeters. A maximum of 4 balls will fit in rubber box.

For finding the maximum number of rubber balls, firstly we will need the volume of the box. We have been given that the volume of the box is 60,000 mm³.

Now, we will find the volume of the rubber balls which have to be fit in the box. We know that the radius of one ball is 15 mm.

Volume of ball = 4/3 πr³

= 4/3 × 22/7 × 15³

= 4/3 × 22/7 × 3375

= 99,000/7

To find the maximum number of balls, we will divide the volume of box by volume of sphere.

Maximum number of balls = volume of box / volume of balls

= 60,000 / (99,000 / 7)

= (60,000 × 7) / 99,000

= 420 / 99

= 4.24

So, rounding up maximum 4 balls can be fit into the box.

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Correct question:

Rubber balls with a radius of 15 millimeters are stored in a 60,000 cubic millimeter box. What is the maximum number of rubber balls that will fit in the box?

(i) T-interval

(ii) F. Because I don't have a large number of professors and I don't know the standard deviation of all FSU professors' heights.

What is standard deviation?

Standard deviation is a measure of the amount of variation or dispersion of a set of data values from the mean value.

When constructing a confidence interval for the mean of a population using a sample, we use either a Z-interval or a T-interval based on the sample size and whether we know the population standard deviation.

If the sample size is large (usually taken to be greater than or equal to 30) and/or we know the population standard deviation, then we can use a Z-interval.

However, if the sample size is small (usually less than 30) and/or we don't know the population standard deviation, we should use a T-interval.

In this case, we don't have a large sample size (just the professors the student has this term), and we don't know the standard deviation of all FSU professors' heights, so we would use a T-interval.

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The approximate area of the trapezoid is determined as  13.95 unit².

The approximate area of the trapezoid is calculated as follows;

Area = ¹/₂(b₁ + b₂)h

Where;

The y-coordinates of the points on the curve at x=3/2 and x=4 is calculated as follows;

y(3/2) = - (3/2)²/2 + 3/2 + 5

y(3/2) = -9/8 + 3/2 + 5

y(3/2) = 5.375

y(4) = -4²/2 + 4 + 5

y(4) = -8 + 9

y(4) = 1

h = 5.375 - 1 = 4.375

The approximate area of the trapezoid is calculated as;

Area = ¹/₂(5.375 + 1) x 4.375

Area = 13.95 unit²

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the approximation of the number of people who leave the building during the first 15 minutes of the evacuation drill using a right Riemann sum with three subintervals is 375 people.

To approximate the number of people who leave the building during the first 15 minutes of the evacuation drill using a right Riemann sum with three subintervals, we can divide the interval [0, 15] into three subintervals of equal width:

[0, 5], [5, 10], [10, 15]

The right Riemann sum is then given by:

Δt [f(5) + f(10) + f(15)]

where Δt is the width of each subinterval (Δt = 5), f(t) is the rate of people leaving the building at time t (in people per minute), and the values of f(t) are given in the table.

Plugging in the values, we get:

Δt [f(5) + f(10) + f(15)]

= 5 [20 + 25 + 30]

= 5 [75]

= 375

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The mode, on the other hand, would not be a useful measure in this case, as it represents the most commonly occurring salary value.

In statistics, the mean (also known as the arithmetic mean or average) is a measure of central tendency that represents the sum of a set of numbers divided by the total number of numbers in the set.

For the salary of players on a professional baseball team, I would be more interested in looking at the mean.

The reason for this is that salaries of professional baseball players are typically not evenly distributed, with a few highly paid players at the top end and many players with lower salaries. The mean salary would provide an average value that takes into account the full range of salaries on the team, including the highly paid players.

The median salary would also be a reasonable measure to use in this case, as it represents the middle value of the distribution when the salaries are arranged in order from lowest to highest. However, it may not be as informative as the mean in capturing the full range of salaries and the distribution of highly paid players.

The mode, on the other hand, would not be a useful measure in this case, as it represents the most commonly occurring salary value, and it is unlikely that there would be many identical salaries among the players.

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Complete question is

For the following type of data set, would you be more interested in looking at the mean, median, or mode? state your reasoning.

The salary of players on a professional baseball team.

The probability of rolling a higher number on the second roll is 15/36 or approximately 0.42.

When rolling a die, each roll has an equal chance of landing on any of the six possible outcomes. Therefore, the probability of rolling any specific number on the first roll is 1/6, and the probability of rolling a number higher than the first on the second roll is also 1/6.

To find the probability of both events happening, we can use the multiplication rule of probability, which states that the probability of two independent events occurring together is equal to the product of their individual probabilities.

So, the probability of rolling a number on the first roll and then rolling a higher number on the second roll is:

P = (1/6) x (1/6)

However, since the question doesn't specify a particular number for the first roll, we need to consider all the possible outcomes for the first roll. These outcomes are mutually exclusive and have an equal chance of happening, so we can add their probabilities to find the overall probability of rolling a higher number on the second roll:

P = (1/6) x (5/6) + (1/6) x (4/6) + (1/6) x (3/6) + (1/6) x (2/6) + (1/6) x (1/6) + (1/6) x 0

Simplifying this expression, we get:

P = 15/36

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Answer:

84

Step-by-step explanation:

A= Bh

Base is 12

Height is 7

= 84

Answer:

84

Step-by-step explanation:

The best description of the shape and center of the dotplot is that distribution of math classes is unimodal symmetric with a center around 4 classes. The Option C is correct.

A dot plot shows the frequency of each value in a dataset. To identify if the distribution of classes is unimodal symmetric, we will check if the dots are roughly evenly distributed around a central line which is the 4 classes.

This indicates the distribution is symmetric. We have a single peak in the data. If there is only one prominent cluster of dots, then, the distribution is unimodal. So, the distribution of classes is unimodal symmetric on the dot plot.

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Answer:

c

Step-by-step explanation:

took the test

It takes the seagull less time to travel a longer distance.

The owl has a speed of 11 1/9 miles per hour.

The seagull has a speed of 18 3/4 miles per hour.

18 3/4 miles per hour is greater than 11 1/9 miles per hour, so the seagull is faster.

In Mathematics and Science, speed is the distance covered by a physical object per unit of time. In Mathematics and Science, the speed of any a physical object can be calculated by using this formula;

Speed = distance/time

Next, we would determine the speed of the owl as follows;

Speed of owl = (8 1/3)/(3/4)

Speed of owl = (25/3)/(3/4)

Speed of owl = 25/3 × 4/3

Speed of owl = 100/9 or 11 1/9 miles per hour.

For the speed of the seagull, we have:

Speed of seagull = (12 1/2)/(2/3)

Speed of seagull = (25/2)/(2/3)

Speed of seagull = 25/2 × 3/2

Speed of seagull = 75/4 or 18 3/4 miles per hour.

In conclusion, we can reasonably infer and logically deduce that the seagull is faster because it took less time to travel a longer distance.

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Missing information:

The question is incomplete and the complete question is shown in the attached picture.

Answer:

It takes the seagull LESS time to travel a LONGER distance.

According to the Centers for Disease Control and Prevention (CDC), lung cancer is the leading cause of smoking-attributable deaths in the United States.

The estimated annual number of smoking-attributable deaths in the United States is approximately 480,000. This includes deaths caused by lung cancer, as well as other smoking-related illnesses such as heart disease, stroke, and chronic obstructive pulmonary disease (COPD).

The CDC reports that about 80% of all lung cancer deaths in the United States are caused by smoking. This means that approximately 136,000 of the 170,000 annual lung cancer deaths in the United States can be attributed to smoking.

To calculate the percentage of U.S. annual deaths attributable to smoking that are lung cancer deaths, we can use the following formula:

(Lung cancer deaths attributable to smoking / Total smoking-attributable deaths) x 100

Substituting the values from above, we get:

(136,000 / 480,000) x 100 = 28.3%

Therefore, approximately 28.3% of U.S. annual deaths attributable to smoking are lung cancer deaths.

Lung cancer is a serious health problem in the United States, and smoking is the leading cause of lung cancer. According to the CDC, smoking is responsible for about 80% of all lung cancer deaths in the United States. This means that smoking is responsible for a significant proportion of all cancer deaths in the country.

In addition to lung cancer, smoking is also a major cause of other types of cancer, including throat, mouth, esophageal, pancreatic, kidney, and bladder cancer. Smoking is also a leading cause of heart disease, stroke, and COPD.

The estimated annual number of smoking-attributable deaths in the United States is approximately 480,000. This represents a staggering toll on human life, and highlights the importance of effective smoking prevention and cessation efforts.

To reduce the number of smoking-attributable deaths, it is important to implement evidence-based tobacco control policies and programs. This includes measures such as increasing the price of tobacco products, implementing smoke-free laws, and providing access to effective smoking cessation treatments. By taking action to reduce smoking rates, we can help to prevent thousands of deaths each year and improve the health and well-being of millions of Americans.

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Let's call the greater number "x" and the lesser number "y". According to the problem, we know that:

x - y = 48  (since the difference between the two numbers is 48)

y = (1/3)x   (since the lesser number is one third of the greater number)

Now we can substitute the second equation into the first equation:

x - (1/3)x = 48

Simplifying this equation, we get:

(2/3)x = 48

Multiplying both sides by 3/2, we get:

x = 72

Now that we know x, we can use the second equation to find y:

y = (1/3)x = (1/3)(72) = 24

So the two positive numbers are 72 and 24.

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An equation to describe the relationship between a and b is b = (3/8)a.

In Mathematics and Geometry, a proportional relationship refers to a type of relationship that produces equivalent ratios and it can be modeled or represented by the following mathematical equation:

y = kx

Where:

Next, we would determine the constant of proportionality (k) by using various data points as follows:

Constant of proportionality, k = y/x

Constant of proportionality, k = 3/8 = 9/24 = 15/40

Constant of proportionality, k = 3/8.

Therefore, the required linear equation is given by;

y = kx

y = 3/8(x) ≡ b = 3/8(a)

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Missing information:

The question is incomplete and the complete question is shown in the attached picture.

Answer:

b= 3/8a

Step-by-step explanation:

Answer:

3:1

Step-by-step explanation:

Step-by-step explanation:

Every year you get 3 % of 1800 pounds added to the account

  what is 3% of 1800 ?         3 % is .03 in decimal form

     1800 * .03 = 54  pounds interest per year

in TWO years you will have   54 * 2   added to 1800 = 1908 pounds

Answer:

A). increase by 54  per year.

B). After two years the account has 1908

Step-by-step explanation:

A). 800 * 3% * 1 = 54

B). 1800 + 1800 * 3% * 2  = 1908

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The total cost for the glass needed to replace the circular window with a diameter of 5 ft using double strength glass costing $3 per square foot will be $58.89.

The total cost for the glass needed to replace the circular window with a diameter of 5 ft can be calculated by finding the area of the circular window first. The formula for the area of a circle is A=πr^2, where r is the radius of the circle. In this case, the diameter is given as 5 ft, so the radius will be half of that, which is 2.5 ft.

Using the formula, we can calculate the area of the circular window as follows:

A = πr^2
A = π(2.5 ft)^2
A = 19.63 sq ft

Therefore, the total cost of double strength glass for the circular window will be:

Total cost = Cost per sq ft x Area
Total cost = $3 x 19.63 sq ft
Total cost = $58.89

So, the total cost for the glass needed to replace the circular window with a diameter of 5 ft using double strength glass costing $3 per square foot will be $58.89.

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