Is △pmr similar to △smn? if so, which postulate or theorem proves these two triangles are similar? responses ​△pmr​ ​is similar to ​△smn​ ​ by the ​​​ ​ssa similarity theorem​. ​, triangle p m r, ​, , ​, , is similar to , ​, , , triangle s m n, ​, , ​, , , by the , ​, ​, , ​, , ​, s s a similarity theorem, ​, , . ​△pmr​ ​is similar to ​△smn​ ​by the ​​ ​sas similarity theorem​. ​, , triangle p m r, ​, , ​, , is similar to , ​, , , triangle s m n, ​, , ​, , by the , ​, ​, , , ​, s a s theorem, ​, . ​△pmr​ ​is similar to ​ ​ ​△smn​ ​by the​ ​sss similarity theorem​​. ​, triangle p m r, ​, , ​, , is similar to , ​, , ​, , ​, triangle s m n, ​, , ​, , by the, ​, , , , ​, s s s similarity theorem, ​, ​, . ​△pmr​ ​is not similar to△smn​​. ​, , triangle p m r, ​, , ​, , is not similar to, , , , triangle s m n, ​, , ​, . a triangle with vertices p m r. segment s n is inside the triangle. point s is on side p m. point n is on side m r. p s is equal to 8 feet. s m is equal to 14 feet. m n is equal to 21 feet. n r is equal to 12 feet.

(a) A basis for the subspace is s = (-2, 1) and t = (1, 0).

(b) The dimension of the subspace is 2.

To find the basis for the subspace, we need to determine a set of linearly independent vectors that span the subspace. In this case, the subspace is defined as s - 2t, s + s, and 2t, where s and t are vectors in R.

By simplifying the expressions, we can rewrite them as (-2, 1), (1, 1), and (0, 2), respectively. These vectors form a basis for the subspace since they are linearly independent and span the subspace.

Therefore, a basis for the subspace is s = (-2, 1) and t = (1, 0).

The dimension of the subspace is determined by the number of linearly independent vectors in the basis. In this case, we have two linearly independent vectors, so the dimension of the subspace is 2.

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The expression d/dx [∫x³(8/p²)dp] can be simplified by integrating with respect to p, differentiating with respect to x using the product rule, and then factoring out common terms.

The expression d/dx [∫x³(8/p²)dp] involves differentiation and integration. To simplify it, we can first integrate x³(8/p²) with respect to p, which gives us -8x³/p + C, where C is the constant of integration. Then, we differentiate this expression with respect to x using the product rule of differentiation, which involves taking the derivative of x³ and multiplying it by (-8/p), and adding the derivative of (-8/p) multiplied by x³.

Simplifying this expression gives us 8x²(1 - 3/p) / p². This final expression can be further simplified by factoring out 8x^2/p², which leaves us with 1 - 3/p in the numerator. We can also write the expression as (8x²/p²) - (24x²/p³), which shows that the expression is the difference of two terms.

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(i) The null hypothesis is that the mean living area of all single-family homes in the county is equal to or less than 2400 square feet. The alternative hypothesis is that the mean living area of all single-family homes in the county is greater than 2400 square feet.

(ii) The test statistic is calculated using the formula: (sample mean - hypothesized mean) / (standard deviation / square root of sample size). In this case, the test statistic is [tex]\frac{(2540 - 2400)}{\frac{472}{\sqrt{50} } } =2.44[/tex]

(iii) The p-value is the probability of obtaining a sample mean as extreme or more extreme than the one observed, assuming the null hypothesis is true. Using a t-distribution with 49 degrees of freedom (since we are using a sample size of 50 and estimating the population standard deviation), we can find the p-value to be 0.009.

(iv) Using a significance level of 0.05, we can conclude that the real estate agent's claim is not true, since the p-value is less than 0.05. We reject the null hypothesis and accept the alternative hypothesis that the mean living area of all single-family homes in the county is greater than 2400 square feet. If we use a significance level of 0.01 instead, we still reject the null hypothesis since the p-value is less than 0.01.

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Answer:

Step-by-step explanation:

To find the range of the function g(x) = -4x + 2, we need to determine the set of all possible output values for the given domain.

We are given the domain: {-6, 1, 4}.

Let's evaluate the function for each value in the domain:

For x = -6:

g(-6) = -4(-6) + 2 = 24 + 2 = 26

For x = 1:

g(1) = -4(1) + 2 = -4 + 2 = -2

For x = 4:

g(4) = -4(4) + 2 = -16 + 2 = -14

The corresponding outputs for the given domain are {26, -2, -14}.

Therefore, the range of the function g(x) = -4x + 2, for the given domain {-6, 1, 4}, is {26, -2, -14}.

(a) To estimate the behavior of the expression 7x + 17 as x→±[infinity], we focus on the term with the highest degree, which is 7x. So, the monomial expression that best estimates 7x + 17 as x→±[infinity] is 7x.

(b) Similarly, to estimate the behavior of the expression 3x - 12 as x→±[infinity], we focus on the term with the highest degree, which is 3x. So, the monomial expression that best estimates 3x - 12 as x→±[infinity] is 3x.

(c) Now, using the results from parts (a) and (b), we write a ratio of monomial expressions to estimate the behavior of (7x + 17)/(3x - 12) as x→±[infinity]. The ratio is (7x)/(3x). Simplifying, we get 7/3.

(d) Based on the answer to part (c), as x→±[infinity], f(x) approaches the constant value 7/3.

(e) Since f(x) approaches a constant value as x→±[infinity], the horizontal asymptote of f exists. The horizontal asymptote is y = 7/3.

Your answer:
a) 7x
b) 3x
c) 7/3
d) 7/3
e) y = 7/3

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The composite function f(g(x)) consists of an inner function g and an outer function f. When doing a change of variables, the likely choice for a new variable u is: b) u = g(x)

The composite function f(g(x)) consists of an inner function g and an outer function f. When doing a change of variables, the likely choice for a new variable u is: b) u = g(x).
This is because when you choose u = g(x), you can substitute u into the outer function f, making it easier to work with and solve the problem.

A composite function, also known as a function composition, is a mathematical operation that involves combining two or more functions to create a new function.

Given two functions, f and g, the composite function f(g(x)) is formed by first evaluating the function g at x, and then using the result as the input to the function f.

In other words, the output of g becomes the input of f. This can be written as follows:

f(g(x)) = f( g( x ) )

The composite function can be thought of as a chaining of functions, where the output of one function becomes the input of the next function.

It is important to note that the order in which the functions are composed matters, and not all functions can be composed. The domain and range of the functions must also be compatible in order to form a composite function.

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The expression given 5g times 7h as required to be rewritten in the task content is; 35gh.

It follows from the task content that the rewritten form of the expression 5g times 7h is to be determined.

Since the given expression can be written algebraically as; 5g × 7h

i.e 5 × 7 × g × h

= 35gh.

Consequently, the rewritten form using the fewest number of symbols and characters is; 35gh.

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The x-coordinate of the new point is 3/2 but we cannot calculate the exact value of the new y-coordinate.

The new coordinate for the transformation of f(x) under the function g(x) = f((1/2)x) - 7, we'll start with the given point (3, 6) and apply the transformation.

First, let's substitute x = 3 into the transformation equation:

g(3) = f((1/2)(3)) - 7

= f(3/2) - 7

Now, to determine the new y-coordinate, we need to know the value of f(x) at x = 3/2.

Without specific information about the function f(x), we cannot calculate the exact value of f(3/2) or the new y-coordinate.

We can still provide a general representation of the new coordinate for any function f(x).

Let's denote the new coordinate as (x', y'):

x' = 3/2

y' = f(3/2) - 7

The value of y' will depend on the function f(x) and its behavior at x = 3/2. If you provide the specific function f(x), we can substitute it into the equation to determine the exact value of y' and provide the coordinates (x', y').

The function f(x), we can determine the new x-coordinate as 3/2, but we cannot calculate the exact value of the new y-coordinate or provide the specific new coordinate (x', y') without additional information.

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The speed of the river's current is 0.4 miles per hour.

To determine the speed of the river's current, we can set up a system of equations based on the information given.

Let's denote the speed of the river's current as v miles per hour.

During the downstream leg of the triathlon, the participant swims with the current, so their effective speed is the sum of their swimming speed and the current's speed:

Effective speed downstream = 2 + v miles per hour

During the upstream leg, the participant swims against the current, so their effective speed is the difference between their swimming speed and the current's speed:

Effective speed upstream = 2 - v miles per hour

We are given that the total swim time is 1.25 hours. Since the participant swims the same distance both downstream and upstream, we can set up the following equation based on the time and distance relationship:

Time downstream + Time upstream = Total swim time

(1.2 miles) / (Effective speed downstream) + (1.2 miles) / (Effective speed upstream) = 1.25 hours

Substituting the expressions for the effective speeds, we have:

(1.2 miles) / (2 + v) + (1.2 miles) / (2 - v) = 1.25

To solve this equation, we can clear the denominators by multiplying both sides by (2 + v)(2 - v):

(1.2 miles)(2 - v) + (1.2 miles)(2 + v) = 1.25(2 + v)(2 - v)

Simplifying the equation:

2.4 - 1.2v + 2.4 + 1.2v = 1.25(4 - [tex]v^2[/tex])

4.8 = 5 - 1.25[tex]v^2[/tex]

Rearranging terms:

1.25[tex]v^2[/tex] = 5 - 4.8

1.25[tex]v^2[/tex] = 0.2

Dividing both sides by 1.25:

[tex]v^2[/tex] = 0.2 / 1.25

[tex]v^2[/tex] = 0.16

Taking the square root of both sides:

v = ± √0.16

Since the speed of the river's current cannot be negative, we take the positive square root:

v = 0.4

Therefore, the speed of the river's current is 0.4 miles per hour.

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The combination of side lengths that is possible for the triangle Marco creates is C: 12 in., 3 in., 3 in.

To determine if a triangle can be formed using the given side lengths, we need to apply the triangle inequality theorem, which states that the sum of any two side lengths of a triangle must be greater than the length of the third side.

In combination A (1 in., 9 in., 8 in.), the sum of the two smaller sides (1 in. + 8 in.) is 9 in., which is not greater than the length of the remaining side (9 in.). Therefore, combination A is not possible.

In combination B (3 in., 5 in., 10 in.), the sum of the two smaller sides (3 in. + 5 in.) is 8 in., which is not greater than the length of the remaining side (10 in.). Hence, combination B is not possible.

In combination C (12 in., 3 in., 3 in.), the sum of the two smaller sides (3 in. + 3 in.) is 6 in., which is indeed greater than the length of the remaining side (12 in.). Thus, combination C is possible.

In combination D (2 in., 8 in., 8 in.), the sum of the two smaller sides (2 in. + 8 in.) is 10 in., which is equal to the length of the remaining side (8 in.). This violates the triangle inequality theorem, which states that the sum of any two sides must be greater than the length of the third side. Therefore, combination D is not possible.

Therefore, the only combination of side lengths that is possible for the triangle Marco creates is C: 12 in., 3 in., 3 in.

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A. The probability that a pet is male, given that it is a dog, is 0.5833.

B. The probability that a pet is a dog, given that it is female, is 0.8889.

C. The probability that a pet is female, given that it is a cat, is 0.6667.

D. The species and gender of the animals are independent.

To find the conditional probabilities, we can use the following formulas:

A. The probability that a pet is male, given that it is a dog:

P(Male | Dog) = P(Male and Dog) / P(Dog)

= 8/24

= 1/3.

Also, there are a total of 24 dogs.

So, P(Dog) = 24/42 = 4/7.

Now, we can calculate the conditional probability:

P(Male | Dog) = (1/3) / (4/7) = 7/12 ≈ 0.5833

B. The probability that a pet is a dog, given that it is female:

P(Dog | Female) = P(Dog and Female) / P(Female)

= (24 - 8) / 42 = 16/42 = 8/21.

Also, there are a total of 42 animals (24 dogs + 18 cats).

So, P(Female) = 18/42 = 3/7.

Now, we can calculate the conditional probability:

P(Dog | Female) = (8/21) / (3/7) = 8/9 ≈ 0.8889

C. The probability that a pet is female, given that it is a cat:

P(Female | Cat) = P(Female and Cat) / P(Cat)

= (18 - 6) / 42 = 12/42 = 2/7.

Also, there are a total of 18 cats.

So, P(Cat) = 18/42 = 3/7.

Now, we can calculate the conditional probability:

P(Female | Cat) = (2/7) / (3/7) = 2/3 ≈ 0.6667

D. To determine if the species and gender of the animals are independent, we need to check

P(Male) x P(Dog) = P(Male and Dog).

P(Male) = (8 + 6) / 42 = 7/21.

P(Dog) = 24 / 42 = 4/7.

P(Male and Dog) = 8/42 = 4/21.

Now, let's check if the product of the probabilities is equal to P(Male and Dog):

P(Male) x P(Dog) = (7/21) x (4/7) = 4/21.

Since P(Male and Dog) = 4/21, the species and gender of the animals are independent.

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The time constant term determines the steady-state response of the system in this first-order equation, for t>0.

In a first-order equation with t>0, the steady-state response of the system is determined by the time constant term.

The time constant is a measure of the time required for a system to reach a steady-state condition after a change in input. It is the ratio of the system's resistance or capacitance to its reactance.

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Answer:

Step-by-step explanation:

3x-5-(4x+1) =

3x-5-4x-1 =

Now combine like terms

-x-6

equation of an ellipse with the center ( 2, -4 ), and with a vertical major axis of length 14, and a minor axis of length 6 is [tex]\frac{(x-2)^{2} }{49 } +\frac{(y+4)^{2} }{9 } = 1[/tex]

The standard form for an ellipse with a vertical major axis

[tex]\frac{(x-h)^{2} }{a^{2} } +\frac{(y-k)^{2} }{b^{2} } = 1[/tex]

where (h, k) represents the center of the ellipse, a is the semi-major axis length, and b is the semi-minor axis length.

Center: (2, -4)

Vertical major axis length: 14

Minor axis length: 6

The center of the ellipse is (h, k) = (2, -4).

The semi-major axis length a is half of the major axis length,

a = 14 / 2

a = 7.

The semi-minor axis length b is half of the minor axis length,

b = 6 / 2

b = 3.

Putting these values into the standard form equation, we get

[tex]\frac{(x-2)^{2} }{7^{2} } +\frac{(y+4)^{2} }{3^{2} } = 1[/tex]

Simplifying the equation gives the final equation of the ellipse

[tex]\frac{(x-2)^{2} }{49 } +\frac{(y+4)^{2} }{9 } = 1[/tex]

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The series 1 + 12√2 + 13√3 + 14√4 + 15√5 + ... is convergent.

To determine whether the series 1 + 12√2 + 13√3 + 14√4 + 15√5 + ... is convergent or divergent, we can use the comparison test.

Note that for n ≥ 2, we have: n√n > n√(n-1)

This is because n√n - (n-1)√(n-1) = n(√n - √(n-1)) > 0. Therefore, we can write: n√n > (n-1)√n

Multiplying both sides by n and simplifying, we get:

n^2√n > (n-1)n√n

n^2√n > n^2√(n-1)

Taking the square root of both sides, we get: n√n > √(n-1)n

Using this inequality, we can compare the given series to the series:

1 + 12√2 + 13√3 + 14√4 + 15√5 + ...

1 + 12√2 + 13√3 + 14√4 + 15√5 + ...

1 + 12√2 + 13√3 + 14√4 + 15√5 + ...

1 + 2√2 + 3√3 + 4√4 + 5√5 + ...

Notice that the series on the right-hand side is a p-series with [tex]p = \frac{3}{2}[/tex], which we know converges. Therefore, the series on the left-hand side, which is greater than the convergent series on the right-hand side, must also converge by the comparison test.

Hence, the series 1 + 12√2 + 13√3 + 14√4 + 15√5 + ... is convergent.

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In this scenario, the process of "regressing" refers to analyzing the relationship between college GPA, high school GPA, and study time for a sample of 59 students.

The "slope coefficient" is a measure that shows how much the dependent variable (in this case, college GPA) changes when the independent variable (high school GPA) changes by one unit, while holding the other variable (study time) constant.

Now, if the population slope coefficient for high school GPA equals 0, it means that there is no significant relationship between high school GPA and college GPA when considering any given value for study time. In other words, high school GPA does not predict college GPA for students, regardless of their study time.

To put it in simpler terms, this finding suggests that for all students, their high school GPA does not provide any reliable information about their college GPA, no matter how much they study. The relationship between the two variables is essentially non-existent, and other factors may be more important in determining a student's college GPA.

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The answer to the given problem P([tex]A^{c}[/tex]) is option C) 0.59

In the Venn diagram, event A represents the set of students who drove, and event B represents the set of students who went to the movies in the past month. The intersection of A and B, denoted by A and B, represents the set of students who both drove and went to the movies in the past month. The complement of A, denoted by [tex]A^{c}[/tex], represents the set of students who did not drive, and the complement of B, denoted by [tex]B^{c}[/tex], represents the set of students who did not go to the movies in the past month.

From the given values, we know that the probability of A and [tex]B^{c}[/tex]  is 0.06, the probability of A and B is 0.35, the probability of [tex]A^{c}[/tex] and B is 0.22, and the probability of  [tex]A^{c}[/tex] and [tex]B^{c}[/tex]   is 0.37. We need to find the probability of    P([tex]A^{c}[/tex]), which is the probability that the student did not drive or go to the movies in the past month.

To find P([tex]A^{c}[/tex]), we can use the formula P([tex]A^{c}[/tex]) = P([tex]A^{c}[/tex]and B) + P([tex]A^{c}[/tex] and [tex]B^{c}[/tex] ). Substituting the given values, we get P([tex]A^{c}[/tex]) = 0.22 + 0.37 = 0.59.

Therefore, the answer to P([tex]A^{c}[/tex]) is option C) 0.59

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The distance that the box has to travel to move from point A to point C is the length of the hypotenuse, which is 12 feet.

To find the distance that the box has to travel to move from point A to point C, we need to find the length of the hypotenuse of the right triangle formed by the ramp.

From the diagram, we see that the vertical height of the ramp is 12 sin 65° and the horizontal length of the ramp is 12 cos 65°. Using the Pythagorean theorem, we can find the length of the hypotenuse:

[tex]hypotenuse^2[/tex] = (12 cos 65°[tex])^2[/tex] + (12 sin 65°[tex])^2[/tex]

[tex]hypotenuse^2[/tex] = 144 [tex]cos^2[/tex] 65° + 144 [tex]sin^2[/tex] 65°

[tex]hypotenuse^2[/tex] = 144 ([tex]cos^2[/tex] 65° + [tex]sin^2[/tex]65°)

[tex]hypotenuse^2[/tex] = 144

hypotenuse = 12

Therefore, the distance that the box has to travel to move from point A to point C is the length of the hypotenuse, which is 12 feet.

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A regular expression for the language of all binary strings containing an odd number of 1's can be constructed using the principle of concatenation and the Kleene star. The regular expression for this language is:
R = (0*10*1)*0*

This regular expression captures all binary strings with an odd number of 1's. Here's a breakdown of the expression:

1. 0*: This matches any number of 0's (including zero occurrences).
2. 10*: This matches a single occurrence of 1 followed by any number of 0's.
3. (0*10*1)*: By concatenating 0*1 to the 10* expression and enclosing the result in parentheses, we create a pattern that matches a sequence of alternating 0's and 1's where the number of 1's is even. The Kleene star applied to the whole expression allows for repeating this pattern any number of times, including zero occurrences.
4. 0*: This final part of the expression matches any remaining 0's after the last odd 1.

This regular expression effectively describes the language of all binary strings containing an odd number of 1's.

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The mean of the test scores is 90.

We can use the formula for converting a raw score (x) to a standard score (z) given the mean (μ) and standard deviation (σ):

z = (x - μ) / σ

In this case, we know that x = 84, z = -1.5, and σ = 4. We can solve for μ as follows:

-1.5 = (84 - μ) / 4

Multiplying both sides by 4, we get:

-6 = 84 - μ

Subtracting 84 from both sides, we get:

μ = 84 - (-6) = 90

Therefore, the mean of the test scores is 90.

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To use the Bonferroni-Holm correction for pairwise comparisons between three groups (A, B, and C), we must adjust the p-value threshold to account for multiple comparisons. First, we calculate the p-value for each pairwise comparison. Then, we rank the p-values from smallest to largest and compare them to the adjusted threshold, which is calculated by dividing the significance level (0.05) by the number of comparisons (3). If the p-value for a comparison is less than or equal to the adjusted threshold, we reject the null hypothesis for that comparison. Otherwise, we fail to reject the null hypothesis.

To apply the Bonferroni-Holm correction to this experiment, we first need to calculate the mean and standard deviation for each dataset. We can then perform pairwise comparisons using a t-test, assuming equal variance.

The calculations for part a are as follows:

- t-value for comparison between A and B = 3.88
- t-value for comparison between A and C = 5.16
- p-value for comparison between A and B = 0.0035
- p-value for comparison between A and C = 0.0002

Since both p-values are less than 0.05, we reject the null hypothesis and conclude that there is a significant difference between the control group and both experimental groups.
To apply the Bonferroni-Holm correction, we must adjust the significance level for multiple comparisons. In this case, we are making three comparisons (A vs. B, A vs. C, and B vs. C), so we divide the significance level by three: 0.05/3 = 0.0167.
Next, we rank the p-values in ascending order:
1. A vs. B (p = 0.0035)
2. A vs. C (p = 0.0002)
3. B vs. C (p = 0.3)
We compare each p-value to the adjusted threshold:

1. A vs. B (p = 0.0035) is less than or equal to 0.0167, so we reject the null hypothesis.
2. A vs. C (p = 0.0002) is less than or equal to 0.0083, so we reject the null hypothesis.
3. B vs. C (p = 0.3) is greater than 0.005, so we fail to reject the null hypothesis.

Using the Bonferroni-Holm correction, we found that there is a significant difference between the control group (A) and both experimental groups (B and C). However, there is no significant difference between groups B and C. This suggests that both experimental drugs have a similar effect on the physiological variable being measured.

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Answer:

1/9

(1/3)2 = (1/3) × (1/3) = 1/9

There will be about an 18% chance that a student participates in student council, that the student participates in after-school sports.

A = Student participates in student council

B = Student participates in after-school sports

To P(A | B) = P(A ∩ B)/P(B). P(A | B) literally means "probability of event A, given that event B has occurred."

P(A ∩ B) is the probability of events A and B happening, and P(B) is the probability of event B happening.

so:

P(A | B) = P(A ∩ B)/P(B)

P(A | B) = 11% / 62%

P(A | B) = 0.11 / 0.62

P(A | B) = 0.18

There will be about an 18% chance, that the student participates in after-school sports.

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The sum of the first 7 terms of the sequence 4, 16, 64, ... is 87380.

The given sequence is a geometric sequence with a common ratio of 4. To find the sum of the first 7 terms using the partial sum formula, we can use the formula:
Sn = a(1 - r^n) / (1 - r)
Where Sn is the sum of the first n terms, a is the first term of the sequence, r is the common ratio, and n is the number of terms being added.
Using the formula with a = 4, r = 4, and n = 7, we get:
S7 = 4(1 - 4^7) / (1 - 4)
Simplifying this expression, we get:
S7 = 87380

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The value of the integral is 3.

To evaluate the integral, we first need to consider the absolute value of sin(x) over the given interval. The function sin(x) oscillates between -1 and 1 as x increases from 0 to 3. Therefore, we can break up the integral into two parts:

∫[0, π/2] 3/2 (sin(x)) dx + ∫[π/2, 3π/2] 3/2 (-sin(x)) dx

Using the formula for the integral of sin(x) and the constant multiple rule of integration, we get:

= [-3/2 cos(x)] from 0 to π/2 + [3/2 cos(x)] from π/2 to 3π/2

= [-3/2 cos(π/2) + 3/2 cos(0)] + [3/2 cos(3π/2) - 3/2 cos(π/2)]

= 3

Therefore, the value of the integral is 3.

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The approximate value of b is 40.

The slope of the line of best fit is 4/3.

We have,

From the scatter plot,

The y-intercept is (0, b).

This means,

The y-values when x = 0.

We can see that,

y = 40 when x = 0.

Now,

There are two points on the scatter plot.

B = (20, 70) and C = (35, 90)

So,

The slope.

= (90 - 70) / (35 - 20)

= 20/15

= 4/3

Thus,

The approximate value of b is 40.

The slope of the line of best fit is 4/3.

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Answer:

There cannot be a triangle with sides a = 3, b = 4, and c = 100 because it would violate the triangle inequality, which states that the sum of any two sides of a triangle must be greater than the third side.

Step-by-step explanation:

In this case, we have a + b = 3 + 4 = 7, which is less than c = 100. This violates the triangle inequality and therefore, a triangle cannot be formed with sides of length 3, 4, and 100.

To understand why the triangle inequality holds, consider drawing a triangle with sides a, b, and c. Then, we can use the Pythagorean theorem to relate the lengths of the sides:

a^2 + b^2 = c^2

We can rearrange this equation to get:

c^2 - a^2 = b^2

Now, since b is a side of the triangle, it must be positive. Therefore, we can take the square root of both sides of the equation to get:

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

But we also know that b + a > c, so we can substitute b = c - a into this inequality to get:

c - a + a > c

which simplifies to:

a > 0

Therefore, we can conclude that c^2 - a^2 > 0, or equivalently, c > a. By a similar argument, we can also show that c > b. This proves the triangle inequality: c > a and c > b, which implies that a + b > c.

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False. Exponential smoothing with α = 0.2 and a moving average with n = 5 do not put the same weight on the actual value for the current period. Exponential smoothing and moving averages are two different forecasting techniques that use distinct weighting schemes.

Exponential smoothing uses a smoothing constant (α) to assign weights to past observations. With an α of 0.2, the weight of the current period's actual value is 20%, while the remaining 80% is distributed exponentially among previous values. As a result, the influence of older data decreases as we go further back in time.On the other hand, a moving average with n = 5 calculates the forecast by averaging the previous 5 periods' actual values. In this case, each of these 5 values receives an equal weight of 1/5 or 20%. Unlike exponential smoothing, the moving average method does not use a smoothing constant and does not exponentially decrease the weight of older data points.In summary, while both methods involve weighting schemes, exponential smoothing with α = 0.2 and a moving average with n = 5 do not put the same weight on the actual value for the current period. This statement is false.

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The vector X in [tex]R^{2}[/tex] whose coordinates with respect to the basis B are [6, -1] is X = [4, -35]

An ordered basis B in [tex]R^{2}[/tex] is a pair of linearly independent vectors that can be used to uniquely represent any vector in the 2-dimensional space.

In this case, the ordered basis B consists of the vectors [1, -6] and [2, -1].
A vector X in [tex]R^{2}[/tex] can be written as a linear combination of the basis vectors. To find the vector X whose coordinates with respect to basis B are [6, -1], we can represent it as follows:
X = 6 × [1, -6] + (-1) × [2, -1]
Now, we just need to perform the linear combination:
X = 6 × [1, -6] + (-1) × [2, -1]
X = [6 × 1, 6 × (-6)] + [(-1) × 2, (-1) × (-1)]
X = [6, -36] + [-2, 1]
Next, add the corresponding components of the two resulting vectors:
X = [(6 + -2), (-36 + 1)]
X = [4, -35]

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A/an database schema diagram can be used to show how the tables in a database are defined and related.

This type of diagram provides a visual representation of the structure and organization of the database. It illustrates the tables ,and  their attributes, and the relationships between them.

The database schema diagram helps in the  understanding the logical design of the database, including primary keys, for  foreign keys, and the connections between different tables. It allows developers, database administrators, and stakeholders to visualize the database structure and serves it as a reference for in  designing, modifying, and querying the database effectively.

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