TRUE/FALSE. Not every linear transformation from Rn to Rm is a matrix transformation.

Answer:

C. 8 * 1/9

Step-by-step explanation:

the answer is C because 8 * 1/9 = 8/9, and 8/9 is a division equal to 8:9

The composition R2(R1(x)) is a rotation about the center C with angle of rotation given by the angle between the vectors P-Q and R2(R1(P))-C.

Lemma 10.3.3 states that any rigid motion of the plane is either a translation a rotation about a fixed point or a reflection across a line.

To prove that the composition of two rotations with the same center is a rotation can use the following argument:

Let R1 and R2 be two rotations with the same center C and let theta1 and theta2 be their respective angles of rotation.

Without loss of generality can assume that R1 is applied before R2.

By Lemma 10.3.3 know that any rotation about a fixed point is a rigid motion of the plane.

R1 and R2 are both rigid motions of the plane and their composition R2(R1(x)) is also a rigid motion of the plane.

The effect of R1 followed by R2 on a point P in the plane. Let P' be the image of P under R1 and let P'' be the image of P' under R2.

Then, we have:

P'' = R2(R1(P))

= R2(P')

Let theta be the angle of rotation of the composition R2(R1(x)).

We want to show that theta is also a rotation about the center C.

To find a point Q in the plane that is fixed by the composition R2(R1(x)).

The angle of rotation theta must be the angle between the line segment CQ and its image under the composition R2(R1(x)).

Let Q be the image of C under R1, i.e., Q = R1(C).

Then, we have:

R2(Q) = R2(R1(C)) = C

This means that the center C is fixed by the composition R2(R1(x)). Moreover, for any point P in the plane, we have:

R2(R1(P)) - C = R2(R1(P) - Q)

The right-hand side of this equation is the image of the vector P-Q under the composition R2(R1(x)).

The composition R2(R1(x)) is a rotation about the center C angle of rotation given by the angle between the vectors P-Q and R2(R1(P))-C.

The composition of two rotations with the same center is a rotation about that center.

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The exact value of the integral ∫b0 (x^6/3 * 6x) dx is b^8.

The Fundamental Theorem of Calculus (FTC) is a theorem that connects the two branches of calculus: differential calculus and integral calculus. It states that differentiation and integration are inverse operations of each other, which means that differentiation "undoes" integration and integration "undoes" differentiation.

The first part of the FTC (also called the evaluation theorem) states that if a function f(x) is continuous on the closed interval [a, b] and F(x) is an antiderivative of f(x) on that interval, then:

∫ab f(x) dx = F(b) - F(a)

In other words, the definite integral of a function f(x) over an interval [a, b] can be evaluated by finding any antiderivative F(x) of f(x), and then plugging in the endpoints b and a and taking their difference.

The second part of the FTC (also called the differentiation theorem) states that if a function f(x) is continuous on an open interval I, and if F(x) is any antiderivative of f(x) on I, then:

d/dx ∫u(x) v(x) f(t) dt = u(x) f(v(x)) - v(x) f(u(x))

In other words, the derivative of a definite integral of a function f(x) with respect to x can be obtained by evaluating the integrand at the upper and lower limits of integration u(x) and v(x), respectively, and then multiplying by the corresponding derivative of u(x) and v(x) and subtracting.

Both parts of the FTC are fundamental to many applications of calculus in science, engineering, and mathematics.

Let's start by finding the antiderivative of the integrand:

∫ (x^6/3 * 6x) dx = ∫ 2x^7 dx = x^8 + C

Using the Fundamental Theorem of Calculus, we have:

∫b0 (x^6/3 * 6x) dx = [x^8]b0 = b^8 - 0^8 = b^8

Therefore, the exact value of the integral ∫b0 (x^6/3 * 6x) dx is b^8.

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Answer:

16 mm

Step-by-step explanation:

P = 2(L + W)

P = 2(2 mm + 6 mm)

P = 2(8 mm)

P = 16 mm

the answer is: f · dr = -30

To find f · dr for the line c from (3, 2, -2) to (6, 1, 7), we first need to parametrize the line in terms of a vector function r(t). We can do this as follows:

r(t) = <3, 2, -2> + t<3, -1, 9>

This gives us a vector function that describes all the points on the line c as t varies.

Next, we need to calculate f · dr for this line. We can use the formula:

f · dr = ∫c f · dr

where the integral is taken over the line c. We can evaluate this integral by substituting r(t) for dr and evaluating the dot product:

f · dr = ∫c f · dr = ∫[3,6] f(r(t)) · r'(t) dt

where [3,6] is the interval of values for t that correspond to the endpoints of the line c. We can evaluate the dot product f(r(t)) · r'(t) as follows:

f(r(t)) · r'(t) = <5y, 2, -1> · <3, -1, 9>

= 15y - 2 - 9

= 15y - 11

where we used the given expression for f and the derivative of r(t), which is r'(t) = <3, -1, 9>.

Plugging this dot product back into the integral, we get:

f · dr = ∫[3,6] f(r(t)) · r'(t) dt

= ∫[3,6] (15y - 11) dt

To evaluate this integral, we need to express y in terms of t. We can do this by using the equation for the y-component of r(t):

y = 2 - t/3

Substituting this into the integral, we get:

f · dr = ∫[3,6] (15(2 - t/3) - 11) dt

= ∫[3,6] (19 - 5t) dt

= [(19t - 5t^2/2)]|[3,6]

= (57/2 - 117/2)

= -30

Therefore, the answer is:

f · dr = -30

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The best lower bound for the volume is 24 cm³, and the best upper bound is 120 cm³ and the best lower bound for the surface area is 52 cm², and the best upper bound is 148 cm².

a. To determine the best upper and lower bounds for the volume of the rectangular parallelepiped, we can consider the extreme cases by rounding each side to the nearest centimeter.

Lower bound: If we round each side down to the nearest centimeter, we get a rectangular parallelepiped with sides 2 cm, 3 cm, and 4 cm. The volume of this parallelepiped is 2 cm * 3 cm * 4 cm = 24 cm³.

Upper bound: If we round each side up to the nearest centimeter, we get a rectangular parallelepiped with sides 4 cm, 5 cm, and 6 cm. The volume of this parallelepiped is 4 cm * 5 cm * 6 cm = 120 cm³.

Therefore, the best lower bound for the volume is 24 cm³, and the best upper bound is 120 cm³.

b. Similar to the volume, we can determine the best upper and lower bounds for the surface area of the parallelepiped by considering the extreme cases.

Lower bound: If we round each side down to the nearest centimeter, the dimensions of the parallelepiped become 2 cm, 3 cm, and 4 cm. The surface area is calculated as follows:

2 * (2 cm * 3 cm + 3 cm * 4 cm + 4 cm * 2 cm) = 2 * (6 cm² + 12 cm² + 8 cm²) = 2 * 26 cm² = 52 cm².

Upper bound: If we round each side up to the nearest centimeter, the dimensions become 4 cm, 5 cm, and 6 cm. The surface area is calculated as follows:

2 * (4 cm * 5 cm + 5 cm * 6 cm + 6 cm * 4 cm) = 2 * (20 cm² + 30 cm² + 24 cm²) = 2 * 74 cm² = 148 cm².

Therefore, the best lower bound for the surface area is 52 cm², and the best upper bound is 148 cm².

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The null and alternative hypotheses are: H0: σ21 = σ22 and Ha: σ21 ≠ σ22(C).

To find the critical value, we need to use the F-distribution with degrees of freedom (df1 = n1 - 1, df2 = n2 - 1) at a significance level of α/2 = 0.005 (since this is a two-tailed test).

Using a calculator or a table, we find that the critical values are F0.005(12,7) = 4.963 (for the left tail) and F0.995(12,7) = 0.202 (for the right tail).

The test statistic is calculated as F = s21/s22, where s21 and s22 are the sample variances and n1 and n2 are the sample sizes. Plugging in the given values, we get F = 5.7^2/5.1^2 = 1.707.

Since this value is not in the rejection region (i.e., it is between the critical values), we fail to reject the null hypothesis. Therefore, we do not have sufficient evidence to claim that the population variances are different at the 0.01 level of significance.

So C is correct option.

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The value of x is -sqrt(55)/8.

Let's use the Pythagorean theorem to find the value of x.

Since P is on the unit circle, we know that the distance from the origin to P is 1. Let's call the x-coordinate of P "x".

We can use the Pythagorean theorem to write:

x^2 + (-3/8)^2 = 1^2

Simplifying, we get:

x^2 + 9/64 = 1

Subtracting 9/64 from both sides, we get:

x^2 = 55/64

Taking the square root of both sides, we get:

x = ±sqrt(55)/8

Since P is in quadrant III, we know that x is negative. Therefore,

x = -sqrt(55)/8

So the value of x is -sqrt(55)/8.

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The correlation between two scores X and Y equals 0.75. If both scores were converted to z-scores, then the correlation between the z-scores for X and z-scores for Y would be the same as the original correlation between X and Y, which is 0.75.

To determine the correlation between z-scores of X and Y, the formula for correlation coefficient (r) is used, which is as follows:

r = covariance of (X, Y) / (SD of X) (SD of Y). We have a given correlation coefficient of two scores, X and Y, which is 0.75. To find out the correlation coefficient between the z-scores of X and Y, we can use the formula:

r(zx,zy) = covariance of (X, Y) / (SD of X) (SD of Y)

r(zx, zy) = r(X,Y).

We know that correlation is invariant under linear transformations of the original variables.

Hence, the correlation between the original variables X and Y equals the correlation between their standardized scores zX and zY. Therefore, the correlation between the z-scores for X and z-scores for Y would be the same as the original correlation between X and Y.

Therefore, the correlation between two scores, X and Y, equals 0.75. If both scores were converted to z-scores, then the correlation between the z-scores for X and z-scores for Y would be the same as the original correlation between X and Y, which is 0.75. Therefore, the answer to the given question is 5) 0.75.

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The rationale behind the F test is that if the null hypothesis is true, by imposing the null hypothesis restrictions on the OLS estimation the per restriction sum of squared errors falls by an insignificant amount. The correct answer is: e.

The F test in statistical hypothesis testing is used to compare the goodness-of-fit of two nested models, typically one with more restrictions (null hypothesis) and the other with fewer restrictions (alternative hypothesis). The test statistic follows an F-distribution.

The rationale behind the F test is to assess whether the additional restrictions imposed by the null hypothesis significantly improve the model's fit. If the null hypothesis is true, meaning that the additional restrictions are valid, then the per restriction sum of squared errors should decrease.

However, if the null hypothesis is false, and the additional restrictions are not valid, then the sum of squared errors may not decrease significantly.

Therefore, the correct statement is that if the null hypothesis is true, the per restriction sum of squared errors falls by an insignificant amount.

The correct answer is option e.

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If we diagonalize the matrix [3 -5; -9 0] as [6 -3; 0 -2] and raise it to the power of n, then [3 -5 -9 -12]n is given by the formula [6n(-3)n; 0 (-2)n].

The problem asks us to find a formula for the matrix [3 -5; -9 0]^n, where n is a positive integer. This formula involves powers of the eigenvalues and can be expressed using complex numbers in integers.

To do this, we first diagonalize the matrix by finding its eigenvalues and eigenvectors.

We obtain two eigenvalues λ1 = (3 + i√21)/2 and λ2 = (3 - i√21)/2, and corresponding eigenvectors v1 and v2.

Finally, we can substitute all the matrices and simplify to get the formula for [3 -5; -9 0]^n as a function of n. This formula involves powers of the eigenvalues and can be expressed using complex numbers in integers.

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The 95% confidence interval is 1.23 to 1.51

From the question, we have the following parameters that can be used in our computation:

Sample, n = 22

Mean, x = 1.37 oz

Standard deviation, s = 0.33 oz

Start by calculating the margin of error using

E = s/√n

So, we have

E = 0.33/√22

E = 0.07

The 95% confidence interval is

CI = x ± zE

Where

z = 1.96 i.e. z-score at 95% CI

So, we have

CI = 1.37 ± 1.96 * 0.07

Evaluate

CI = 1.37 ± 0.14

This gives

CI = 1.23 to 1.51

Hence, the 95% confidence interval is 1.23 to 1.51

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The rejection region is given by: {F(x) ≤ c} ∪ {F(x) ≥ 1 - c} which is of the form {x ≤ x0} ∪ {x ≥ x1}, where x0 and x1 are determined by c.

To show that the rejection region is of the form {x ≤ x0} ∪ {x ≥ x1}, we can use the fact that the critical value c divides the sampling distribution of the test statistic into two parts, the rejection region and the acceptance region.

Let F(x) be the cumulative distribution function (CDF) of the test statistic. By definition, the rejection region consists of all values of the test statistic for which F(x) ≤ c or F(x) ≥ 1 - c.

Since the sampling distribution is symmetric about the mean under the null hypothesis, we have F(-x) = 1 - F(x) for all x. Therefore, if c is the critical value, then the rejection region is given by:

{F(x) ≤ c} ∪ {1 - F(x) ≤ c}

= {F(x) ≤ c} ∪ {F(-x) ≥ 1 - c}

= {F(x) ≤ c} ∪ {F(x) ≥ 1 - c}

This shows that the rejection region is of the form {x ≤ x0} ∪ {x ≥ x1}, where x0 and x1 are determined by c. Specifically, x0 is the value such that F(x0) = c, and x1 is the value such that F(x1) = 1 - c.

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If one score in a correlational study is numerical and the other is non-numerical, the non-numerical variable can be used to organize the scores into separate groups which can then be compared with a (d) chi-square hypothesis test.

A chi-square hypothesis test can be used to analyze the relationship between a numerical and a non-numerical variable in a correlational study where the non-numerical variable is used to group the scores.

This test is used to determine whether there is a significant association between the two variables.

The other options, t-test, mixed-design analysis of variance, and single factor analysis of variance, are statistical tests that are used for different types of research designs and are not appropriate for analyzing the relationship between a numerical and non-numerical variable in a correlational study.

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The equation of the parabola that intersects the x-axis at points (-1, 0) and (3,0) is y = 0.

Given that a parabola intersects the x-axis at points (-1, 0) and (3,0).We know that, when a parabola intersects the x-axis, the y-coordinate of the point on the parabola is 0. Therefore, the two x-intercepts tell us two points that are on the parabola.Thus the vertex is given by:Vertex is the midpoint of these x-intercepts=(x_1+x_2)/2=(-1+3)/2=1The vertex is the point (1,0).Since the vertex is at (1,0) and the parabola intersects the x-axis at (-1,0) and (3,0), the axis of symmetry is the vertical line passing through the vertex, which is x=1.We also know that the parabola opens upwards because it intersects the x-axis at two points.To find the equation of the parabola, we can use the vertex form:y = a(x - h)^2 + kwhere (h, k) is the vertex and a is a constant that determines how quickly the parabola opens up or down.We have h=1 and k=0.Substituting in the x and y values of one of the x-intercepts, we get:0 = a(-1 - 1)^2 + 0Simplifying, we get:4a = 0a = 0Substituting in the x and y values of the other x-intercept, we get:0 = a(3 - 1)^2 + 0Simplifying, we get:4a = 0a = 0Since a = 0, the equation of the parabola is:y = 0(x - 1)^2 + 0Simplifying, we get:y = 0Hence the equation of the parabola that intersects the x-axis at points (-1, 0) and (3,0) is y = 0.

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What is the standard form of the parabola?

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To find out how many applications can be made with the 26-gram container, we need to divide the total amount of cream in the container by the average amount of cream used per application.

Total amount of cream (container) = 26 grams
Average amount of cream per application = 1 6/7 grams

First, let's convert the mixed fraction 1 6/7 to an improper fraction:
(1 * 7) + 6 = 13/7 grams

Now, divide the total amount of cream by the average amount of cream per application:

26 grams ÷ 13/7 grams

To divide by a fraction, you multiply by its reciprocal (the fraction flipped):

26 * 7/13

Now, cancel out the common factor (13):

(26/13) * (7/1)

2 * 7 = 14

So, you can make 14 applications with the 26-gram container.

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This is the Taylor series representation of the function f centered at x=6.

To find the Taylor series for f centered at 6, we need to use the formula:
f(x) = Σn=0 to infinity (f^(n)(a) / n!) (x - a)^n
where f^(n)(a) denotes the nth derivative of f evaluated at x = a.
In this case, we know that f^(n)(6) = (-1)^n * n! * 5^n * (n^3). So, we can substitute this into the formula above:
f(x) = Σn=0 to infinity ((-1)^n * n! * 5^n * (n^3) / n!) (x - 6)^n
Simplifying, we get:
f(x) = Σn=0 to infinity (-1)^n * 5^n * n^2 * (x - 6)^n
This is the Taylor series for f centered at 6.
This is the Taylor series representation of the function f centered at x=6.

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Answer:

the answer is B 25 calories/1 ounce

explanation:

6 ounce/150 calories = X/ 1 calories

= 25/1

(a) Cov(X, Y) = 1/2, (b) E(Y|X) = X/2, (c) Cov(X,E(Y|X)) = Cov(X, Y) = 1/2, and the identity Cov(X,E(Y|X)) = Cov(X, Y) holds true for any joint distribution of X and Y.

(a) To compute Cov(X, Y), we need to first find the marginal density of X and the marginal density of Y.

The marginal density of X is:

f_X(x) = ∫[0,x] f(x,y) dy

= ∫[0,x] 2e^(-2x) / x dy

= 2e^(-2x)

The marginal density of Y is:

f_Y(y) = ∫[y,∞] f(x,y) dx

= ∫[y,∞] 2e^(-2x) / x dx

= -2e^(-2y)

Next, we can use the formula for covariance:

Cov(X, Y) = E(XY) - E(X)E(Y)

To find E(XY), we can integrate over the joint density:

E(XY) = ∫∫ xyf(x,y) dxdy

= ∫∫ 2xye^(-2x) / x dxdy

= ∫ 2ye^(-2y) dy

= 1

To find E(X), we can integrate over the marginal density of X:

E(X) = ∫ xf_X(x) dx

= ∫ 2xe^(-2x) dx

= 1/2

To find E(Y), we can integrate over the marginal density of Y:

E(Y) = ∫ yf_Y(y) dy

= ∫ -2ye^(-2y) dy

= 1/2

Substituting these values into the formula for covariance, we get:

Cov(X, Y) = E(XY) - E(X)E(Y)

= 1 - (1/2)*(1/2)

= 3/4

Therefore, Cov(X, Y) = 3/4.

(b) To find E(Y | X), we can use the conditional density:

f(y | x) = f(x, y) / f_X(x)

For 0 ≤ y ≤ x, we have:

f(y | x) = (2e^(-2x) / x) / (2e^(-2x))

= 1 / x

Therefore, the conditional density of Y given X is:

f(y | x) = 1 / x, 0 ≤ y ≤ x

To find E(Y | X), we can integrate over the conditional density:

E(Y | X) = ∫ y f(y | x) dy

= ∫[0,x] y (1 / x) dy

= x/2

Therefore, E(Y | X) = x/2.

(c) To compute Cov(X,E(Y | X)), we first need to find E(Y | X) as we have done in part (b):

E(Y | X) = x/2

Next, we can use the formula for covariance:

Cov(X, E(Y | X)) = E(XE(Y | X)) - E(X)E(E(Y | X))

To find E(XE(Y | X)), we can integrate over the joint density:

E(XE(Y | X)) = ∫∫ xyf(x,y) dxdy

= ∫∫ 2xye^(-2x) / x dxdy

= ∫ x^2 e^(-2x) dx

= 1/4

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Based on the crocodile skeleton found with a head length of 62 cm and a body length of 380 cm, it is likely that the species was a Saltwater Crocodile (Crocodylus porosus).

According to the given measurements, it is likely that the species was a Saltwater Crocodile (Crocodylus porosus).  This is because Saltwater Crocodiles are known to have larger sizes compared to other species.

To explain why, let's consider the following steps:

1. Compare the head length and body length to average sizes of different crocodile species.
2. Identify the species whose average size is closest to the given measurements.

Saltwater Crocodiles are the largest living species of crocodiles, with males reaching lengths of over 6 meters (20 feet). The head length of 62 cm and body length of 380 cm (3.8 meters) would likely be within the size range for an adult male Saltwater Crocodile. Other species, such as the Nile Crocodile or the American Alligator, typically do not reach such large sizes, making the Saltwater Crocodile a more plausible candidate based on the given measurements.

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The cubic polynomial in standard form with zeros 5, 3, and –4 is `x³ - 4x² - 17x + 60`.

The cubic polynomial in standard form with zeros 5, 3, and –4 is obtained by multiplying the three factors: (x - 5), (x - 3) and (x + 4) and then simplifying it to standard form. Here's how:Given zeros: 5, 3, -4Using zero product property: (x - 5)(x - 3)(x + 4) = 0Multiplying the three factors using distributive property:x(x - 3)(x + 4) - 5(x - 3)(x + 4) = 0x(x² + x - 12) - 5(x² + x - 12) = 0Expanding: x³ + x² - 12x - 5x² - 5x + 60 = 0Combining like terms:x³ - 4x² - 17x + 60 = 0The cubic polynomial in standard form with zeros 5, 3, and –4 is `x³ - 4x² - 17x + 60`. The standard form of a cubic polynomial is ax³ + bx² + cx + d where a, b, c, d are constants.

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The number of students that are science majors can be thought of as a binomial random variable because:

1. There are a fixed number of trials (students) in the sample.
2. Each trial (student) has only two possible outcomes: being a science major or not being a science major.
3. The probability of success (being a science major) remains constant for each trial (student).
4. The trials (students) are independent of each other, meaning the outcome for one student does not affect the outcomes of the other students.

These four characteristics satisfy the conditions of a binomial random variable, which is why the number of science majors among a group of students can be modeled using a binomial distribution.

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Mr. Baral has to pay Rs 64000 as an annual income tax at an interest of 10% for his stationary shop.

From the question, we have given that if he is unmarried and his income is between Rs 5,00,001 to Rs 7,00,000, he has to pay an annual interest of 10%.

Given annual income in Rs = 640000.

The annual income tax rate he has to pay at = 10%

So, to find out the income tax from the annual income we have to find out the 10% of 640000.

Income tax = 640000/100 * 10 = 64000

From the above analysis, we can conclude that Mr. Baral has to pay 64000 rs of income tax annually.

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Given question is not having enough information, I am writing the complete question below:

Use it to calculate the income taxes. For an individual Income slab Up to Rs 5,00,000 0% Rs 5,00,001 to Rs 7,00,000 10% Rs 7,00,001 to Rs 10,00,000 20% Rs 10,00,001 to Rs 20,00,000 30% Tax rate For couple Tax rate 0% Income slab Up to Rs 6,00,000 Rs 6,00,001 to Rs 8,00,000 Rs 8,00,001 to Rs 11,00,000 20% Rs 11,00,001 to Rs 20,00,000 30%

a) Mr. Baral has a stationery shop. His annual income is Rs 6,40,000. If he is unmarried, how much income tax should he pay? 10%​

Answer:

k = [tex]\frac{12}{5}[/tex]

Step-by-step explanation:

[tex]\frac{12}{5}[/tex] = [tex]\frac{1}{6k}[/tex] ( cross- multiply )

72k = 5 ( divide both sides by 72 )

k = [tex]\frac{5}{72}[/tex]

Answer: k=8.4 or 42/5

Step-by-step explanation: to find k you take 1 2/5 and divide it by 1/6. When I did it I got 8.4. To check my work I replaced the variable in the equation and it was correct.

In long-run equilibrium in perfect competition, economic profit is zero and firms are producing at their efficient scale.

In the long-run equilibrium of perfect competition, we know that firms operate efficiently and economic forces balance supply and demand. In this market structure, numerous firms produce identical products, with no barriers to entry or exit.

Due to free entry and exit, firms cannot maintain any long-term economic profit. In the long-run equilibrium, economic profit is zero and firms earn a normal profit.

This outcome occurs because if firms were to earn positive economic profits, new firms would enter the market, increasing competition and driving down prices until profits are eliminated.

Conversely, if firms experience losses, some will exit the market, reducing competition and allowing prices to rise until the remaining firms reach a break-even point.

As a result, resources are allocated efficiently, and consumer and producer surpluses are maximized.

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The distance from the plane 10x y z=90 to the plane 10x y z=70, we need to find the distance between a point on one plane and the other plane. The distance from the plane 10x y z=90 to the plane 10x y z=70 is 10sqrt(2) units.

Take the point (0,0,9) on the plane 10x y z=90.
The distance between a point and a plane can be found using the formula:
distance = | ax + by + cz - d | / sqrt(a^2 + b^2 + c^2)
where a, b, and c are the coefficients of the x, y, and z variables in the plane equation, d is the constant term, and (x, y, z) is the coordinates of the point.
For the plane 10x y z=70, the coefficients are the same, but the constant term is different, so we have:
distance = | 10(0) + 0(0) + 10(9) - 70 | / sqrt(10^2 + 0^2 + 10^2)
distance = | 20 | / sqrt(200)
distance = 20 / 10sqrt(2)
distance = 10sqrt(2)
Therefore, the distance from the plane 10x y z=90 to the plane 10x y z=70 is 10sqrt(2) units.

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The test statistic for the difference between the means is 2.22.

To determine the test statistic for the difference between the means of two independent populations, use the two-sample t-test:

t = (x₁ - x₂) / √[(σ₁² /n₁) + (σ₂² /n₂)]  

where x₁ and x₂ = sample means, σ₁ and σ₂ = sample standard deviations, and n₁ and n₂ = sample sizes.

Using the given values:

x₁ = $15.80

x₂ = $15.00

σ₁ = $3.00

σ₂ = $2.25

n₁ = 81

n₂ = 64

Calculate the test statistic as:

t = ($15.80 - $15.00) / √[($3.00²/81) + ($2.25²/64)]  

t = 2.22

Therefore, the test statistic for the difference between the means is 2.22.

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Musk is 12 years old, Abu is 18 years old and the sum of their ages is 30.

Let's find out the current ages of Musk and Abu from the given information.

Musk's age is 2/3 of Abu's age.

We can express it as; Musk's age = 2/3 × Abu's age Also, the sum of their age is 30.

So we can express it as: Musk's age + Abu's age = 30

Substitute the first equation into the second one:2/3 × Abu's age + Abu's age = 30

Simplify the equation and solve for Abu's age:5/3 × Abu's age = 30Abu's age = 18

Substitute Abu's age into the first equation to find Musk's age:

Musk's age = 2/3 × 18Musk's age = 12

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Given the stock is purchased for $72.50 and it is expected that each day the stock will decrease by $0.05.

Let x = time (in days) and

P(x) = stock price (in $).

To find how many days it will take for the stock price to be equal to $65, we need to solve for x such that P(x) = 65.So, the equation of the stock price is

: P(x) = 72.50 - 0.05x

We have to solve the equation P(x) = 65. We have;72.50 - 0.05

x = 65

Subtract 72.50 from both sides;-0.05

x = 65 - 72.50

Simplify;-0.05

x = -7.50

Divide by -0.05 on both sides;

X = 150

Therefore, it will take 150 days for the stock price to be equal to $65

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The identity holds true for all nonnegative integers n by mathematical induction.

To prove the given identity, we can use mathematical induction.

Base case: When n = 0, we have:

j2(0) + (-1)^0 Σ(3)3·2^0 j=0 = j0 + 1(3·1) = 1 + 3 = 4

So the identity holds true for n = 0.

Inductive step: Assume that the identity holds true for some arbitrary value of n = k, i.e.,

j2k+1 + (-1)^k Σ(3)3·2^k j=0

We need to show that the identity holds true for n = k + 1, i.e.,

j2(k+1)+1 + (-1)^(k+1) Σ(3)3·2^(k+1) j=0

Expanding the above expression, we get:

j2k+3 + (-1)^(k+1) (3·2^(k+1) + 3·2^k + ... + 3·2^0)

= j2k+1 · j2 + j2k+1 + (-1)^(k+1) (3·2^k+1 + 3·2^k + ... + 3)

= j2k+1 (j2+1) + (-1)^(k+1) (3·(2^k+1 - 1)/(2-1))

= j2k+1 (j2+1) - 3·2^k+2 (-1)^(k+1)

= j2k+1 (j2+1 - 3·2^k+2 (-1)^k+1)

= j2k+1 (j2+1 + 3·2^k+2 (-1)^k)

= j2(k+1)+1 + (-1)^(k+1) Σ(3)3·2^(k+1) j=0

Therefore, the identity holds true for all nonnegative integers n by mathematical induction.

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