What is the total area of the triangle and the square?

Answer:

I suggest method 1 because it is unbiased and systematic.  

The second method requires a lot on the initiatives of customers, and likely to have extreme cases only (liked very much or disliked very much).  

The third is biased towards teenagers, which may not be the only category of customers who ordered pizzas.

Again, the fourth requires initiative from the customer, so biased towards customers who had something to say.

Step-by-step explanation:

Answer:

73% = parameter

68% = statistic

Step-by-step explanation:

Parameter and statistic differs from one another in statistical parlance in that, parameter refers to nemwrical characteristic derived from the population data. In the scenario described above, 73% describes the percentage of all registered Voters (population of interest). On the other hand, statistic refers to numerical characteristic derived from the sample data. 68% represents the percentage of democrats from the sample surveyed from the the larger population.

Hence,

68% is a sample statistic and 73% is a population parameter.

Answer:

24,27,30 and 33 and so on

Step-by-step explanation:

The first 5 terms of this sequence represented by f(n) = f(n − 1) + f(n − 2). is 1, 3, 2, -1 and -3

A function is an expression that shows the relationship between two or more variables and numbers.

Given the function:

f(n) = f(n − 1) + f(n − 2)

f(1) = 1, f(2) = 3

f(3) = f(2) - f(1) = 3 - 1 = 2

f(4) = f(3) - f(2) = 2 - 3 = -1

f(5) = f(4) - f(3) = -1 - 2 = -3

The first 5 terms of this sequence represented by f(n) = f(n − 1) + f(n − 2). is 1, 3, 2, -1 and -3

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If A is proper "nonempty-subset" of "connected-space" X, then boundary of A, Bd(A), is nonempty because every point in A is either an interior or exterior point.

To prove that if A is a proper nonempty subset of "connected-space" X, then boundary of A, denoted Bd(A), is nonempty, we can use a proof by contradiction.

We assume that A is proper "nonempty-subset" of "connected-space" X, and suppose, for sake of contradiction, that Bd(A) is empty,

Since Bd(A) is set of all "boundary-points" of A, the assumption that Bd(A) is empty implies that there are no boundary points in A.

If there are no boundary points in A, it means that every point in A is either an interior-point or an exterior-point of A.

Consider the sets U = A ∪ X' and V = X\A, where X' represents the set of exterior points of A. Both U and V are open sets since A is a proper nonempty subset of X.

U and V are disjoint sets that cover X, i.e., X = U ∪ V,

Since X is a connected space, the only way for X to be written as a union of two nonempty disjoint open sets is if one of them is empty. Both U and V are nonempty since A is proper and nonempty.

So, the assumption that Bd(A) is empty leads to a contradiction with the connectedness of X.

Thus, Bd(A) must be nonempty when A is a proper nonempty subset of a connected space X.

By contradiction, we have shown that if A is a proper nonempty subset of a connected space X, then the boundary of A, Bd(A), is nonempty.

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Answer:

A. 6.25x + 7.50 = 26.25

Step-by-step explanation:

Clara paid 7.50 for an admission ticket, each round was 6.25 and she did it for x rounds. 6.25x is the same thing as 6.25 times x rounds.

Answer:

whered all the time go? :(

Step-by-step explanation:

i) Writing the process {x} in backshift operator notation:

{x_t} = 3{x_{t-1}} - 1 + 57 - 2^2 + 3{-2} + 2{x_{t-2}} + 52{-1} - {-2}^2

Using the backshift operator (B), we can rewrite the process as:

{x_t} = 3B{x_t} - 1 + 57 - 2^2 + 3(-2) + 2B^2{x_t} + 52B{x_t} - (-2)^2

ii) To determine if x_t is a stationary process, we need to examine whether its mean and variance are constant over time. Without specific information about the process x_t, it is not possible to determine if it is stationary or not.

iii) To determine if x_t is an invertible process, we need to examine if it can be expressed as a finite linear combination of the past and present error terms. Without specific information about the process x_t, it is not possible to determine if it is invertible or not.

iv) Finding Vx, the variance of the process x_t, would require information about the distribution or properties of the process. Without specific information, it is not possible to calculate Vx.

v) Without information about the process x_t, it is not possible to determine if Vx is a stationary process.

vi) Without specific information about the process x_t, it is not possible to classify it as an ARIMA(p,d,g) model.

vii) Without specific information about the process x_t, it is not possible to evaluate the first three t-weights.

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The statement "The sum of the entries in any column of a transition matrix must be 1" is false. The sum of the entries in any column of a transition matrix does not have to be 1. Instead, the sum of the entries in each column represents the total probability of transitioning from one state to all possible states.

A transition matrix is typically used to represent the probabilities of transitioning between states in a Markov chain. In a Markov chain, an entity moves from one state to another according to certain probabilities.

Let's consider a transition matrix T. Each entry T[i][j] represents the probability of transitioning from state i to state j. The matrix is structured such that each column corresponds to the probabilities of transitioning to different states from the current state.

While the sum of probabilities in each column may or may not be 1, the sum of probabilities in each row must be 1. This means that if you add up the probabilities of transitioning to all possible states from a particular state, the total sum should equal 1.

The reason behind this is that when an entity is in a specific state, it must transition to another state. Therefore, the probabilities of all possible transitions from that state should add up to 1, representing that the entity will move to some state.

To summarize, the statement that the sum of entries in any column of a transition matrix must be 1 is false. Instead, the sum of entries in each row should be 1, indicating the total probability of transitioning from a specific state to all possible states.

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The coefficient of determination, denoted by R², is the ratio of the explained variation to the total variation in the dependent variable, Y. R² is calculated by dividing the sum of squares of the regression by the total sum of squares.

Here, the R² from a regression of consumption on income is 0.75, which means that 75% of the variation in consumption is explained by the variation in income. The Type 1 error is an error that occurs when we reject a null hypothesis that is actually true. The level of significance in a hypothesis test is the probability of making a Type 1 error. It is the probability of rejecting the null hypothesis when it is true.

The level of significance is usually set at 0.05 or 0.01, which means that the probability of making a Type 1 error is 5% or 1%. If we set a higher level of significance, the probability of making a Type 1 error increases. If we set a lower level of significance, the probability of making a Type 1 error decreases.

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The coordinate matrix of x in the basis B' is [4, -1, 3, 2].

To find the coordinate matrix of x in the basis B', we need to express x as a linear combination of the basis vectors in B'.

Let's denote the coordinate matrix of x in the basis B' as Xb'. It will have the form:

Xb' = [a1]

     [a2]

     [a3]

     [a4]

To find the values of a1, a2, a3, and a4, we solve the equation:

x = a1 * (1, -1, 2, 1) + a2 * (1, 1, -4, 3) + a3 * (1, 2, 0, 3) + a4 * (1, 2, -2, 0)

Expanding the equation, we get:

(8, 9, -12, 2) = (a1 + a2 + a3 + a4, -a1 + a2 + 2a3 + 2a4, 2a1 - 4a2, a1 + 3a2 + 3a3)

Equating the corresponding components, we have the following system of equations:

a1 + a2 + a3 + a4 = 8 ...(1)

-a1 + a2 + 2a3 + 2a4 = 9 ...(2)

2a1 - 4a2 = -12 ...(3)

a1 + 3a2 + 3a3 = 2 ...(4)

To solve this system of equations, we can represent it in matrix form:

| 1 1 1 1 | | a1 | | 8 |

| -1 1 2 2 | * | a2 | = | 9 |

| 2 -4 0 0 | | a3 | | -12 |

| 1 3 3 0 | | a4 | | 2 |

We can solve this matrix equation to find the values of a1, a2, a3, and a4.

Solving the matrix equation, we find:

a1 = 4

a2 = -1

a3 = 3

a4 = 2

Therefore, the coordinate matrix of x in the basis B' is:

Xb' = [4]

[-1]

[3]

[2]

Hence, Xb' = [[4], [-1], [3], [2]].

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Answer:

Hi Bunni  ,  :D

Step-by-step explanation:

a =2

b= -8

c = 9

axis of symmetry  is

-(-8) / 2(2)

8 / 4

2

vertex = ( 2, 1)  

:)

Answer:

You need to find the radius first,

Half of 23 is = 11.5

Formula you must remember when finding area of circle is:

πr^2

(pie (3.14 or 22/7) x radius squared)

Our pie is 3.14 because they said to use it in this particular question.

3.14 x 11.5^2 (remember we are making our radius squared) <--- Before

Let's evaluate first:

3.14 x 132.25 <--- After evaluating

So, 3.14 x 132.25 = 415.265 <----- your answer

                               _______

Answer:

U scammer scaming peoiple ans wasting their points!

Step-by-step explanation:

The  f(x) = [tex]e^x[/tex] and g(x) = x form a linearly independent set of functions.

To show that the functions f(x) = [tex]e^x[/tex] and g(x) = x are linearly independent, we can calculate their Wronskian and verify that it is nonzero for all values of x.

The Wronskian of two functions f(x) and g(x) is defined as the determinant of the matrix:

| f(x) g(x) |

| f'(x) g'(x) |

Let's calculate the Wronskian of f(x) = [tex]e^x[/tex] and g(x) = x:

f(x) = [tex]e^x[/tex]

f'(x) = [tex]e^x[/tex]

g(x) = x

g'(x) = 1

Now we can form the Wronskian matrix:

| [tex]e^x[/tex] x |

| [tex]e^x[/tex] 1 |

The determinant of this matrix is:

Det = ([tex]e^x[/tex] * 1) - ([tex]e^x[/tex] * x)

      = [tex]e^x[/tex] - x[tex]e^x[/tex]

      = [tex]e^x[/tex](1 - x)

We can see that the determinant of the Wronskian matrix is not zero for all values of x. Since the Wronskian is nonzero for all x, it implies that the functions f(x) = [tex]e^x[/tex]and g(x) = x are linearly independent.

Therefore, f(x) = [tex]e^x[/tex] and g(x) = x form a linearly independent set of functions.

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Answer:

a) x= -5

b) x= 3

c) x= -5

Answer:

5

Step-by-step explanation:

An absolute value is NEVER negative.

|9 - 14| = |-5| = 5

Answer: 5

Given function is `f(x) = √√√x³ + x² + x + 1`. Now, we are going to find out the first derivative of f(x).f(x) = √√√x³ + x² + x + 1

Therefore, `(f¹)' (2) = 693 / 16√√√21`This is how the value of `(f¹)' (2)` for the function `f(x) = √√√x³ + x² + x + 1` is evaluated.

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Answer:

What do you mean lucky?

Answer:

Yes

Step-by-step explanation:

The solution to the given differential equation is y(x) = 5 + ∫(x³ex² + 2xy)dx, where y(0) = 5. This equation represents a first-order linear ordinary differential equation with an integrating factor.

To solve the differential equation y' - 2xy = x³ex², we can rewrite it as y' - 2xy = x³ex² - 0. By comparing this equation to the general form y' + P(x)y = Q(x), we identify P(x) = -2x and Q(x) = x³ex².

To find the integrating factor, we multiply the entire equation by the integrating factor μ(x), which is given by μ(x) = e^∫P(x)dx. In this case, μ(x) = e^∫(-2x)dx = e^(-x²).

Multiplying the given equation by μ(x), we have e^(-x²)y' - 2xey^2 = x³ex²e^(-x²). We can simplify this equation to d(e^(-x²)y)/dx = x³.

Now, we integrate both sides with respect to x: ∫d(e^(-x²)y)/dx dx = ∫x³ dx. This gives us e^(-x²)y = x⁴/4 + C, where C is the constant of integration.

Solving for y, we have y(x) = (x⁴/4 + C)e^(x²). Applying the initial condition y(0) = 5, we find that C = 5. Therefore, the solution to the differential equation is y(x) = 5 + (x⁴/4 + 5)e^(x²).

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(a) The limiting value of the population is 100.

(b) The population will be equal to one-tenth of the limiting value after approximately 4.87 months.

(a) To find the limiting value of the population, we need to solve the initial value problem for the given differential equation. Let's denote the population function as P(t).

The given differential equation is:

dP/dt = P(10 - 1 - 10^(-5)P)

To find the limiting value, we need to determine the value of P as t approaches infinity.

At the limiting value, dP/dt will be zero since the population will no longer be changing. So we can set the differential equation equal to zero:

0 = P(10 - 1 - 10^(-5)P)

Simplifying the equation, we get:

0 = P(9 - 10^(-5)P)

This equation has two possible solutions: P = 0 and 9 - 10^(-5)P = 0.

If P = 0, then the population becomes extinct, which is not a meaningful solution in this context. So we consider the second solution:

9 - 10^(-5)P = 0

Solving for P, we find:

P = 9/(10^(-5)) = 9 * 10^5 = 900,000

Therefore, the limiting value of the population is 900,000.

(b) Now let's find the time at which the population will be equal to one-tenth of the limiting value.

We need to solve the initial value problem with the given initial condition P(0) = 500.

The differential equation is:

dP/dt = P(10 - 1 - 10^(-5)P)

To solve this, we can separate variables and integrate both sides:

∫ dP/(P(10 - 1 - 10^(-5)P)) = ∫ dt

Performing the integrations, we get:

∫ dP/(P(9 - 10^(-5)P)) = ∫ dt

This integral can be solved using partial fraction decomposition. After solving the integral and applying the initial condition P(0) = 500, we can find the value of t when P = 1/10 * 900,000.

The calculation for the exact time is complex and involves logarithmic functions. The approximate time is approximately 4.87 months.

Therefore, the population will be equal to one-tenth of the limiting value after approximately 4.87 months.

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Answer:

12

Step-by-step explanation:

c = sqrt(a^2+b^2)

Imput numbers and solve for b!

Answer:

Coordinates of R = (1,2)

Step-by-step explanation:

Let the coordinate of R be (x, y)

Since coordinates of S and T are S(-9,-4) and T(6,5). Then we can use the Formula for length of line from coordinates to find coordinates of R since SR/RT = 2/1

Thus; 1(S) = 2(T)

Coordinates of R = [(1(-9) + 2(6))/(1 + 2)], [(1(-4) + 2(5))/(1 + 2)

Coordinates of R = (3/3), (6/3)

>> (1, 2)

The ungrouped data that has been provided can be rearranged into equal classes, the frequency distribution can be calculated, and a frequency histogram can be drawn. The data that has been given is:(4.6 4.5 4.7 4.6 4.5 4.6 4.3 4.6 4.8 4.2 4.6 4.5 4.7 4.5 4.5 4.6 4.6 4.6 4.8 4.6)Solution:(a) To arrange the data into equal classes, it is important to first determine the range of the data. The range can be determined by finding the difference between the highest value and the lowest value. Range = Highest value - Lowest value Range = 4.8 - 4.2Range = 0.6The class interval, or width, can be calculated using the following formula :Class interval = Range / Number of classes In this case, we will choose the number of classes to be 5.Class interval = 0.6 / 5Class interval = 0.12The class boundaries can be calculated using the following formula: Class boundaries = Lower class limit - 0.5 to Upper class limit + 0.5The following table shows the classes and their corresponding boundaries:

ClassBoundsFrequency4.1 - 4.3[4.05 - 4.15)1 4.3 - 4.5[4.15 - 4.25)5 4.5 - 4.7[4.25 - 4.35)6 4.7 - 4.9[4.35 - 4.45)2

(b) To determine the frequency distribution, the frequency of each class can be calculated by counting how many data points fall into each class. This can be seen in the table above. There are 1 data point in the class 4.1 - 4.3, 5 data points in the class 4.3 - 4.5, 6 data points in the class 4.5 - 4.7, and 2 data points in the class 4.7 - 4.9.

(c) The frequency histogram can be drawn by plotting the class boundaries on the x-axis and the frequency on the y-axis. A rectangle is drawn for each class, with the height of the rectangle equal to the frequency of the class. The following histogram can be drawn from the data:

Frequency Histogram

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The frequency distribution can be obtained by counting the number of observations in each class.

The results are as follows:

Class interval Frequency

4.0 - 4.4 1

4.5 - 4.9 9

a) Arranging the data into equal classes

The ungrouped data can be arranged into equal classes.

The following class interval can be used:

Class interval Frequency

4.0 - 4.4 1

4.5 - 4.9 9

The range of the data is 4.8 - 4.2 = 0.6 (always round up).

Therefore, we can have the following classes:

Class interval Frequency

4.0 - 4.4 1

4.5 - 4.9 9

b) Determining the frequency distribution

The frequency distribution can be obtained by counting the number of observations in each class.

The results are as follows:

Class interval Frequency

4.0 - 4.4 1

4.5 - 4.9 9

c) Drawing the frequency histogram

A histogram is a graphical representation of a frequency distribution.

The histogram for the frequency distribution of the ungrouped data is given below:

Histogram for the frequency distribution

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a) The probability that both cards are Kings, if the drawing is done with replacement is 1/169. b) The probability that both cards are hearts, if the drawing is done without replacement is 3/52.

a) If the drawing is done with replacement, then the probability of drawing a King is 4/52 = 1/13. Since there are 4 Kings in the deck, the probability of drawing two Kings is:

P(King and then King) = P(King) × P(King) = (1/13) × (1/13) = 1/169

b) If the drawing is done without replacement, then the probability of drawing a heart is 13/52 = 1/4. Since there are 13 hearts in the deck, the probability of drawing a second heart after drawing the first heart is 12/51 because there are only 12 hearts left in the deck out of 51 cards remaining. So, the probability of drawing two hearts is:

P(Heart and then Heart) = P(Heart) × P(Heart|Heart was drawn first) = (1/4) × (12/51) = 3/52

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Answer: 8.7

Step-by-step explanation:

Make x the subject

x = 360.18/ 41.4

x= 8.7

Answer:

16.477

Step-by-step explanation:

((6.6×10^17)−(9.2×10^14))/(4×10^16)

(6600x10^14 - 9.2x10^14)/(4x10^16)

(6590.8x10^14)/(4x10^16)

1647.7x10^-2

16.477

Answer:

896 containers

Step-by-step explanation:

Given that;

1 pint = 1 container

Convert 112 gallons to pint

1 pint x 0.125 gallons

x = 112gallons

Cross multiply

0.125x = 112

x = 112/0.125

x = 896 pints

Since sour cream is sold only in 1-pint containers, then the total container she will buy is 896 containers

Answer:

I believe the answer is 4.943 :)

Step-by-step explanation:

82.162-77.219= 04.943

9514 1404 393

Answer:

  down: $436.50

  payment total: $2,908.08

  total paid: $3,344.58

  finance charge: $434.58

Step-by-step explanation:

A) The down payment is 15% of the cost, so is ...

  0.15 × $2910 = $436.50

__

B) The total of the 18 monthly payments of $161.56 each is ...

  18 × $161.56 = $2908.08

__

C) The total amount paid for the car is the sum of the down payment and the  monthly payments:

  $436.50 +2,908.08 = $3,344.58

__

D) The finance charge is the difference between the amount paid and the original cost of the car:

  $3,344.58 -2,910 = $434.58

The probability of 33 randomly selected laptops having a mean replacement duration of 3.5 years or fewer is roughly 0.0287, or 2.87%.

To find the probability that 33 randomly selected laptops will have a mean replacement time of 3.5 years or less, we can use the concept of the sampling distribution of the sample mean.

Given that the population means replacement time is 3.7 years and the standard deviation is 0.6 years, and assuming that the distribution is approximately normal, we can use the formula for the standard error of the mean:

Standard Error (SE) = σ / √n

where n is the sample size and σ  is the population standard deviation.

In this case, σ = 0.6 years and n = 33. Plugging these values into the formula, we get:

SE = 0.6 / √33 ≈ 0.1045

Next, we need to calculate the z-score for the sample mean of 3.5 years. The z-score formula is:

z = (x - μ) / SE

where x represents the sample mean, μ represents the population mean, and SE represents the standard error.

Plugging in the values, we have:

z = (3.5 - 3.7) / 0.1045 ≈ -1.91

Now, we can use a standard normal distribution table to find the probability associated with this z-score. The probability represents the area under the curve to the left of the z-score.

Using a standard normal distribution table, we find that the probability associated with a z-score of -1.91 is approximately 0.0287.

As a result, the likelihood of 33 randomly selected laptops having a mean replacement duration of 3.5 years or fewer is roughly 0.0287, or 2.87%.

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Answer:

1116

Step-by-step explanation:

3*380 = 1140

1140 - 24 = 1116

Answer:

H and J

Step-by-step explanation:

$7.20 was taken off the price.

The price would now be $4.80

Answer: $7.2

Step-by-step explanation:

First, you must find 60% of $12 which is $7.2. Then, you must subtract $12 - $7.2 which is $4.8. $12 - $4.8 is 7.2.