What is the name of the point located at (4, 3)?
A. Point M
B. Point P
C. Point W
D. Point X

Answer:

Może być odpowiedź c ja ne wiem

Given that the product has a 0 in the thousands place, the value of k is C. 4.

The product is the result of multiplying two or more numbers together.

The product is the result of multiplication, which is one of the mathematical operators, including addition, subtraction, division, exponentiation, and modulus operations.

Product of 13,462 and 798k = 13,462 x 798 x k

= 10,742,676k

K = variable

If k = 1, the product of 10,742,676k = 10,742,676, the nearest thousand = 10,743,000

If k = 2, the product of 10,742,676k = 21,485,352, the nearest thousand = 21,485,000.

If k = 4, the product of 10,742,676k = 42,970,704, the nearest thousand = 42,970,000.

If k = 7, the product of 10,742,676k = 75,198,732, the nearest thousand = 75,199,000.

If k = 9, the product of 10,742,676k = 96,684,084, the nearest thousand = 96,684,000.

Thus, given that the product has a 0 in the thousands place, the value of k is C. 4.

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Answer:

\(2.0 \times {10}^{4} \)

Step-by-step explanation:

\( \frac{2.8 \times {10}^{7} }{1.4 \times {10}^{3} } \\ 2 \times {10}^{7 - 3} \\ 2 \times {10}^{4} \)

Answer:

24 is the answer

Step-by-step explanation:

To solve this problem, we first do two thirds of 180, and then we do one fifth of the solution you got for "two thirds of 180"

\(\mathrm{Two\:thirds\:of\:180 = (\frac{2}{3}) 180\:\:or\:\:\frac{2}{3}\times180}\)

\(\mathrm{Turn\:\frac{2}{3}\:into\:a\:decimal,\:by\:dividing\:2\:by\:3}\)

\(\mathrm{0.6666666666666667\times180}\)

\(\mathrm{Multiply\:0.6666666666666667\:and\:180}\)

\(\mathrm{120}\)

Now we do one fifth of 120

\(\mathrm{One\:fifth\:of\:120 = (\frac{1}{5})120\:or\:\frac{1}{5}\times120}\)

\(\mathrm{Turn\:\frac{1}{5}\:into\:a\:decimal,\:by\:dividing\:1\:by\:5}\)

\(\mathrm{0.2\times120}\)

\(\mathrm{Multiply\:0.2\:and\:120}\)

\(24\)

So the answer to "What is one fifth of two thirds of 180", would be 24

By multiplying the number by the corresponding fractions, we can see that the fifth part of two-thirds of 180 is 24.

The fifth part of two-thirds of 180 is 24.

To calculate it:

Step 1: Find two-thirds of 180, Just multiply the fraction 2/3 by the number

(2/3) * 180 = 2 * 180 / 3 = 360 / 3 = 120

Step 2: Find the fifth part of the result from Step 1, similar like we did above, multiply the number by the fraction 1/5.

(1/5) * 120 = 120 / 5 = 24

So, the fifth part of two-thirds of 180 is 24.

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The experiment compared the fracture toughness of high-purity 18 Ni maraging steel with commercial-purity steel of the same type. For 32 high-purity specimens, the sample average toughness was X=65.5, while for 38 commercial-purity specimens, the sample average toughness was y=59.8.

The high-purity steel is more expensive, and its use for a certain application can be justified only if its fracture toughness exceeds that of commercial-purity steel by more than 5. Both toughness distributions are assumed to be normal with σ1 = 1.2 and σ2 =1.1. Using α=.001, the relevant hypotheses are tested. β is then computed for the test when μ1 – μ2 = 6.
In the experiment, the fracture toughness of high-purity 18 Ni maraging steel (X = 65.5, m = 32, σ1 = 1.2) was compared to commercial-purity steel (Y = 59.8, n = 38, σ2 = 1.1). The goal is to justify the use of high-purity steel if its toughness exceeds commercial steel by more than 5. Both toughness distributions are assumed to be normal.

a. To test the relevant hypotheses using α = .001, we perform a two-sample t-test. The null hypothesis (H0) is that the difference in means (μ1 - μ2) is less than or equal to 5, and the alternative hypothesis (H1) is that the difference is greater than 5.

b. To compute β for the test conducted in part (a) when μ1 - μ2 = 6, we need to determine the probability of a Type II error, which is the likelihood of failing to reject the null hypothesis when it is false. Calculating β requires knowledge of the sampling distributions and the specific alternative value (μ1 - μ2 = 6).

In summary, to justify the use of high-purity steel, a two-sample t-test can be conducted using the given parameters. Additionally, calculating β helps understand the likelihood of a Type II error in this hypothesis test.

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B. the proportion of the variation of the dependent variable explained by the independent variable. R^2, also known as the coefficient of determination, measures the goodness of fit of a regression model.

It represents the proportion of the total variation in the dependent variable that is explained by the independent variable(s) in the model. In other words, R^2 indicates how well the independent variable(s) account for the observed variation in the dependent variable. The correct answer, choice B, states that R^2 represents the proportion of the variation of the dependent variable explained by the independent variable.

It quantifies the strength of the relationship between the independent and dependent variables and provides an assessment of how well the regression model fits the observed data. A higher R^2 value indicates a better fit, as it indicates that a larger proportion of the variation in the dependent variable can be attributed to the independent variable(s).

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The exterior angle of ΔTYP is ∠5. Option C

An exterior angle of a triangle is an angle formed by one side of a triangle and the extension of an adjacent side. This means that, if you extend one side of a triangle, the angle formed between the extension and the adjacent side is the exterior angle.

Another simple way of identifying it in the diagram is to look for straight line that branches out of a triangle . If you look closely at the diagram, you would see that the T and P straight line is the one that branch out of the triangle.

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If B is row-equivalent to a nonsingular matrix A, then B is also nonsingular.

Suppose that A is a nonsingular matrix, which means that A has an inverse denoted by A\(^{-1}.\)

Now let B be a matrix that is row-equivalent to A. This means that we can obtain B from A by applying a finite sequence of elementary row operations.

Since elementary row operations do not change the row space of a matrix, the row space of B is the same as the row space of A. This means that B has the same rank as A.

Since A is nonsingular, it has full rank (i.e., rank(A) = n, where n is the number of rows or columns in A). Therefore, B also has full rank, which means that B is also a nonsingular matrix.

To see this more explicitly, suppose that B is singular, which means that there exists a non-zero vector x such that Bx = 0.

Since B is row-equivalent to A, we have that Ax = 0 (since the row space of B is the same as the row space of A).

But this contradicts the fact that A is nonsingular, since if Ax = 0 then x = \(A^{-1}Ax = A^{-1}0 = 0.\)

Therefore, B cannot be singular and must be nonsingular.

In summary, if B is row-equivalent to a nonsingular matrix A, then B is N also nonsingular.

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In the first question, the statement "Using logarithmic differentiation we obtain that the derivative of the function y = x² satisfies the equation y = 4x log x + 2x" is true.

In the first question, using logarithmic differentiation on the function y = x², we differentiate both sides, apply the product rule and logarithmic differentiation, and simplify to obtain the equation y = 4x log x + 2x, which is correct.

In the second question, the statement is false. When using logarithmic differentiation on the function y = (1+x²)²(1 + sin x)²/(1-x²), the derivative is calculated correctly, but the equation given is incorrect. The correct equation after logarithmic differentiation should be y' = (4x/(1 + x²)(1 + sin x))(1-x²) - (2x(1+x²)²(1 + sin x)²)/(1-x²)².

In the third question, the product z²w is calculated correctly as 30-10%.

It is important to accurately apply logarithmic differentiation and perform the necessary calculations to determine the derivatives and products correctly.

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Answer:

A= 33 and B = 18

Step-by-step explanation:

B that is equal to 11:5. We can multiply both quantities of this proportion by some number to find two values that satisfy A - B = 18.

The simplest case would be to think A = 11 and B = 5, but 11-5 is not equal to 18 ⇒ 11 - 5 = 6  which does not satisfy A - B = 18.

Another option to find an answer is to multiply the ratio by two: 2 (11: 5) = 22:10, but it turns out that is A = 22 and B = 10 ⇒22-10 is not equal to 18 either.

Thus we arrive at the one that is the correct answer, multiplying the proportion by three: 3 (11: 5) = 33 - 15, and in this case we would have A = 33 and B = 15, which meets the condition A - B = 18, because 33 - 15 = 18

Yes, it is true that an OLS (ordinary least squares) estimator meets all three small sample properties (unbiasedness, efficiency, and minimum variance) under certain conditions, in addition to being consistent.

These conditions include the assumption that the error term has a zero mean and constant variance, and that the errors are independent and identically distributed (IID). When these assumptions hold, the OLS estimator is considered to be BLUE (Best Linear Unbiased Estimator) and is a reliable tool for estimating the unknown parameters in a linear regression model. However, it is important to note that these assumptions may not always hold in practice, and alternative estimation methods may need to be considered.

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Answer:

Proven.

Step-by-step explanation:

Answer:

e is 9x D is 4x c is 1× and a is 5× and b is 2×

Answer:

This is a false statement

Step-by-step explanation:

75.7-9=66.7

7-4=3

66.7 is not equal yo three therefor it is false

The equation to solve the height of the trapezoid is 45h = 1,575

Given data ,

Let the area of the trapezoid be A

Now , the value of A = 1,575 cm²

And , the Top(base2) = 63cm and  Bottom(base1) = 27 cm

Area of Trapezoid = ( ( a + b ) h ) / 2

where , a = shorter base of trapezium

b = longer base of trapezium

h = height of trapezium

On simplifying , we get

1,575 = (63 + 27) / 2 x h

1575 = 45h

Hence , the equation is 1575 = 45h

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The complete question is attached below :

The trapezoid has an area of 1,575 cm2, Which equation could you solve to find the height of the trapezoid?

A 850.5h = 1,575

B 1,701h = 1,575

C 90h = 1,575

D 45h = 1,575

Top(base2) = 63 cm

Bottom(base1) = 27 cm

Answer:

B cause me just use logic

We have

First we will multiply 3x by 4x, then 3x by 7, then -8 by 4x and then -8 by 7

then we sum similar terms and we obtain the answer

Answer:

i don't know do you play free fire

The set of all diagonal n × n matrices is a subspace of Mnn3.

Given, we need to use the Subspace Test to determine which of the sets are subspaces of Mnn3 and the sets are: The set of all diagonal n × n matrices.

The set of all n x n matrices A such that det(A) = 0.The set of all n x n matrices A such that tr(A) = 0.The set of all symmetric n x n matrices.

Subspace Test: A nonempty subset H of a vector space V is a subspace of V if for every u and v in H and every scalar c, the vector cu + v is in H.

The set of all diagonal n × n matrices.Here, we have to prove that the set of all diagonal matrices is a subspace of Mnn3.

Let A and B be two diagonal matrices. Then, A + B is also a diagonal matrix. Since the diagonal elements of A + B are equal to the sums of the corresponding diagonal elements of A and B. So, the set of all diagonal matrices is closed under addition. Let A be a diagonal matrix and c be a scalar.

Then, cA is also a diagonal matrix. Since the diagonal elements of cA are equal to the product of c and corresponding diagonal elements of A. So, the set of all diagonal matrices is closed under scalar multiplication.

Therefore, the set of all diagonal matrices is a subspace of Mnn3. Hence, the main answer is: a. The set of all diagonal n × n matrices is a subspace of Mnn3.

We have used the subspace test to prove that the set of all diagonal n × n matrices is a subspace of Mnn3. The subspace test is used to verify whether a given subset of a vector space is a subspace or not.

We have proved that the set of all diagonal matrices is closed under addition and scalar multiplication.

The diagonal elements of A + B are equal to the sums of the corresponding diagonal elements of A and B. And the diagonal elements of cA are equal to the product of c and corresponding diagonal elements of A.

Therefore, the set of all diagonal matrices satisfies all the three properties required for a subset to be a subspace.

Hence, the set of all diagonal n × n matrices is a subspace of Mnn3.

In conclusion, we can say that the set of all diagonal n × n matrices is a subspace of Mnn3 as it satisfies the subspace test.

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Answer:

no cause the graph dosen't cross the 0

Step-by-step explanation:

The general solution of the system of differential equations is given by:

[x1(t); x2(t)] = c1 [2t; t] e^(5t) + c2 [t; t] e^(9t)

where c1 and c2 are constants.

Let's first find the eigenvalues of the coefficient matrix. The characteristic polynomial is given as:

λ^2 - 14λ + 65 = 0

We can factor this as:

(λ - 5)(λ - 9) = 0

So, the eigenvalues are λ = 5 and λ = 9.

Now, let's find the eigenvectors corresponding to each eigenvalue:

For λ = 5:

(A - 5I)x = 0

where A is the coefficient matrix and I is the identity matrix.

Substituting the values, we get:

[3-5 1; 1 -5] [x1; x2] = [0; 0]

Simplifying, we get:

-2x1 + x2 = 0

x1 - 4x2 = 0

Taking x2 = t, we get:

x1 = 2t

So, the eigenvector corresponding to λ = 5 is:

[2t; t]

For λ = 9:

(A - 9I)x = 0

Substituting the values, we get:

[-1 1; 1 -3] [x1; x2] = [0; 0]

Simplifying, we get:

-x1 + x2 = 0

x1 - 3x2 = 0

Taking x2 = t, we get:

x1 = t

So, the eigenvector corresponding to λ = 9 is:

[t; t]

Therefore, the general solution of the system of differential equations is given by:

[x1(t); x2(t)] = c1 [2t; t] e^(5t) + c2 [t; t] e^(9t)

where c1 and c2 are constants.

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Answer:

No.

Step-by-step explanation:

They are not because the left side is 52, while the right side is 0.

Answer:

mm,,,,,,,,,,,   m

Step-by-step explanation:

The central angle is the angle made at the center of the polygon by any two adjacent vertices of the polygon.

The central angle is the angle made at the center of the polygon by any two adjacent vertices of the polygon. If you were to draw a line from any two adjacent vertices to the center, they would make the central angle. Because the polygon is regular, all central angles are equal. It does not matter which side you choose.

All central angles would add up to 360° (a full circle), so the measure of the central angle is 360 divided by the number of sides. Or, as a formula:

\(central \ angle = \frac{360}{n}\) degrees

where n  is the number of sides

The measure of the central angle thus depends only on the number of sides. The angle depends only on the number of sides, not the size of the polygon. If you change the number of sides, you will see that as the number of sides gets larger, the cenral angle gets smaller.

Therefore, The central angle is the angle made at the center of the polygon by any two adjacent vertices of the polygon.

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The central angle is the angle made at the center of the polygon by any two adjacent vertices of the polygon.

The central angle is the angle made at the center of the polygon by any two adjacent vertices of the polygon. If you were to draw a line from any two adjacent vertices to the center, they would make the central angle. Because the polygon is regular, all central angles are equal. It does not matter which side you choose.

All central angles would add up to 360° (a full circle), so the measure of the central angle is 360 divided by the number of sides. Or, as a formula:

midpoint = \(\frac{360}{9}\)degrees

where n  is the number of sides

The measure of the central angle thus depends only on the number of sides. The angle depends only on the number of sides, not the size of the polygon. If you change the number of sides, you will see that as the number of sides gets larger, the cenral angle gets smaller.

Therefore, The central angle is the angle made at the center of the polygon by any two adjacent vertices of the polygon.

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The value of the Confidence interval will be 3.787

The number of standard deviations from the t-mean distribution is equal to a t-score. The test statistic used in t-tests and regression testing is the t-score. When the data follow a t-distribution, it may also be used to represent how distant an observation is from the mean.

The t-score formula is written as follows:t=¯¯¯x−μS√n t = x ¯ − μ S n , where ¯¯¯x, is the sample mean, is the population mean, S n is the sample size, and x is the standard deviation of the sample. Square root n must be included in the formula.

using tables of t distribution we have

t-score for 99.8%

Confidence Interval (alpha) =1-0.998=0.002

Sample size (n)=15

df=n-1=14

t-score for a 99.8% Confidence Interval will be

t(0.002,14)=3.787

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