THIS ONE IS HARD SO PLEASE HELP ITS RSM....
AWNSER FOR EACH ONE (I WILL GIVE BRAINLIEST)

Y>0

Y<0

Y=0

A power series representation for the function f(x) =[tex]x/36 + x^2[/tex] is  Σ((1/36) * [tex]x^n[/tex]) from n=1 to infinity + Σ[tex](x^{(2n)})[/tex] from n=0 to infinity and its interval of convergence is -1 < x < 1.

To find a power series representation for f(x), we'll rewrite it as a sum of power series:

f(x) = [tex]x/36 + x^2[/tex]
f(x) = (1/36) * [tex]x + x^2[/tex]
f(x) = Σ((1/36) * [tex]x^n[/tex]) from n=1 to infinity + Σ[tex](x^{(2n)})[/tex] from n=0 to infinity

Now let's find the interval of convergence for the given power series. We'll use the Ratio Test:

For the first power series, let a_n = (1/36) * [tex]x^n[/tex]:
lim (n→∞) (|a_(n+1)/a_n|) = lim (n→∞) (|[tex](x^{(n+1)[/tex])/(36 * [tex]x^n[/tex])|) = |x|/36

For the second power series, let b_n = [tex]x^{2n[/tex]:
lim (n→∞) (|b_(n+1)/b_n|) = lim (n→∞) [tex](|(x^{(2(n+1)}))/(x^{(2n)})|) = |x|^2[/tex]

The interval of convergence is where both series converge. The first series converges when |x|/36 < 1, or -36 < x < 36. The second series converges when [tex]|x|^2[/tex] < 1, or -1 < x < 1. Therefore, the interval of convergence for f(x) is:

-1 < x < 1

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The percentage of the original ¹⁴c is still present is  28.5%.

To calculate the percentage of original ¹⁴C still present, we need to use the formula for                                             radioactive decay:
N = N₀(1/2)^(t/h)
Where:
N₀ = initial amount of ¹⁴C
N = final amount of ¹⁴C after time t
t = time elapsed
h = half-life of ¹⁴C

Substituting the given values:
N₀ = 100%
t = 1.190 × 10⁴ years
h = 5730 years

N = 100% x (1/2)^((1.190 × 10⁴)/5730)
N = 100% x (1/2)^(2.08)
N = 100% x 0.285
N = 28.5%

Therefore, after 1.190 × 10⁴ years, approximately 28.5% of the original ¹⁴C is still present in the tree trunk.

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(a) E[Sn] = n/λ.

(b) E[S4|N(1)=2] = 1/λ + 3/λ

(c) E[N(4) - N(2)|N(1)=3] = 2λ.


(a) The expected time of the nth event, E[Sn], is the sum of expected interarrival times. Since each interarrival time has an exponential distribution with mean 1/λ, we have E[Sn] = n/λ.

(b) Given N(1)=2, we know two events occurred in the first unit of time. So, we want the expected time for the next two events (i.e., 4th event). Each interarrival time has mean 1/λ, so E[S4|N(1)=2] = 1/λ + 3/λ.

(c) Given N(1)=3, we want the expected number of events in the interval (2, 4) independent of the events in the interval (0, 1). Since it's a Poisson process, we have E[N(4) - N(2)|N(1)=3] = (4-2)λ = 2λ.

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Answer: no polygon exists in which the ratio of the number of diagonals to the sum of the measures of the angles is 1 to 18, because the number of sides n cannot be equal to 23.

Step-by-step explanation: Let n be the number of sides of the polygon. The number of diagonals in a polygon of n sides is given by the formula:

d = n(n-3)/2

The sum of the measures of the angles in a polygon of n sides is given by the formula:

180(n-2)

The ratio of the number of diagonals to the sum of the measures of the angles is:

d / [180(n-2)] = [n(n-3)/2] / [180(n-2)] = (n-3) / 360

We want to show that this ratio cannot be equal to 1/18, or:

(n-3) / 360 ≠ 1/18

Multiplying both sides by 360, we get:

n-3 ≠ 20

Adding 3 to both sides, we get:

n ≠ 23

Therefore, no polygon exists in which the ratio of the number of diagonals to the sum of the measures of the angles is 1 to 18, because the number of sides n cannot be equal to 23.

Answer:

Step-by-step explanation:

the answer is d  why because is direct proportion i think i am not sure

Answer: Your answer is completely correct. It is just that when answering the question, you should assume that the 48 lb child is on the left, and the 72 lb child is on the right. Usually, I always assume that the first mentioned item is the left most one.

Step-by-step explanation:

This is how I will set up the problem: M1 = 48 lbs, M2 = 72 lbs, L = 10 ft

Since (M1 * 0 + M2 * 10)/(M1+M2) = equilibrium, we can use this equation to find the solution:

0 + 720 / (48+72) = 6 feet

Answer:

Yes they are congruent quadrilaterals.

And from the look of it, they possess the same shape and size; not to mention their length are also congruent.

Step-by-step explanation:

This furthet explains how PQR has the same angle as EFG and the length of DE is equal to the length of QR.

Answer:

So the three consecutive numbers are:

14,15, and 16.

Step-by-step explanation:

Let the three consecutive integers be = x , x+1,  x+ 2 sum = 45

then,

x + (x + 1) + (x +2)  = 45

-> 3x + 3 = 45

-> 3x = 45 - 3

-> x = 14

-> x = 14

-> x + 1 = 15

-> x + 2 = 16

So, three consecutive numbers are : 14, 15, and 16.

Answer:

4,261.4 engines

Step-by-step explanation:

To find the number of engines that minimize the unit cost, we need to find the minimum value of the function C(x) given by:

C(x) = (Cx - 0.6x)/(2156x + 16664)

where C is a constant representing the fixed costs of manufacturing the engines.

To find the minimum, we need to take the derivative of C(x) with respect to x and set it equal to zero:

C'(x) = (2156Cx - 0.6x(2156 + 16664)) / (2156x + 16664)^2 = 0

Simplifying the equation, we get:

2156Cx - 0.6x(2156 + 16664) = 0

2156Cx = 0.6x(2156 + 16664)

C = 0.6(2156 + 16664)/2156 = 2.2

So the unit cost is minimized when C = 2.2. Substituting this value back into the original equation, we get:

C(x) = (2.2x - 0.6x)/(2156x + 16664)

Simplifying, we get:

C(x) = (1.6x)/(2156x + 16664)

To find the number of engines that minimize the unit cost, we need to find the value of x that makes C(x) as small as possible. We can do this by finding the value of x that makes the derivative of C(x) equal to zero:

C'(x) = (1.6(2156x + 16664) - 2156(1.6x)) / (2156x + 16664)^2 = 0

Simplifying the equation, we get:

1.6(2156x + 16664) - 2156(1.6x) = 0

688x = 2,933,824

x = 4,261.4

Therefore, the number of engines that minimize the unit cost is approximately 4,261.4

Hope this helps!

The Cauchy-Schwarz inequality holds for the vectors u and v as 1 is indeed less than or equal to 41. The values for u-v, u and v are (-2, 9), [tex]\sqrt{(58)[/tex] and [tex]\sqrt{(29)[/tex] respectively.

First, let's calculate u-v:

u-v = (3, 7) - (5, -2) = (-2, 9)

Now, let's calculate the magnitudes of u and v:

|u| = [tex]\sqrt{(3^2 + 7^2) }= \sqrt{(58)[/tex]

|v| =[tex]\sqrt{(5^2 + (-2)^2)} = \sqrt{(29)[/tex]

Next, we can use the Cauchy-Schwarz inequality to find an upper bound for the dot product of u and v:

|u · v| ≤ |u| |v|

Substituting in the values we just calculated:

|u · v| ≤ [tex]\sqrt{(58)} \sqrt{(29)[/tex]

Now, let's calculate the dot product of u and v:

u · v = 35 + 7(-2) = 1

So, we have:

|1| ≤ \sqrt{(58)} \sqrt{(29)

Simplifying:

1 ≤ [tex]\sqrt{(58*29)[/tex]

1 ≤ [tex]\sqrt{(1682)[/tex]

1 ≤ 41

Since, 1 is indeed less than or equal to 41, the Cauchy-Schwarz inequality holds for the vectors u and v.

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Answer:

height = 10 m

lengths of bases = 5 m and 10 m

[tex] \frac{1}{2} (10)(5 + 10) = 5(15) = 75[/tex]

So the area of this trapezoid is 75 square meters.

Check the picture below.

[tex]\textit{area of a trapezoid}\\\\ A=\cfrac{h(a+b)}{2}~~ \begin{cases} h~~=height\\ a,b=\stackrel{parallel~sides}{bases~\hfill }\\[-0.5em] \hrulefill\\ a=5\\ b=10\\ h=10 \end{cases}\implies A=\cfrac{10(5+10)}{2}\implies A=75~m^2[/tex]

Answer:

A

Step-by-step explanation:

Answer:

13/85

Step-by-step explanation:

The sin of an angle is the opposite side over the hypotenuse.

sin B = opp/ hyp

sin B = 13/85

Answer:

sin B = 0.1529

Step-by-step explanation:

To find the Sin B angle we have to use the below formula.

[tex]\sf Sin\:B = \frac{Opposite}{Hypotenuse}[/tex]

Let us solve this now.

[tex]\sf Sin\:B = \frac{Opposite}{Hypotenuse} \\\\\sf Sin\:B = \frac{13}{85} \\\\Sin \:B =0.1529[/tex]

Additionally, To Remove sin, look at the inverse of the sin value and find the exact value of B

[tex]\sf B = sin^-^10.1529\\B=8.79\\\\[/tex]

Answer:

the ans is 6.4

Step-by-step explanation:

using the distance formula

d^2= (x2-x1)^2 + (y2-y1)^2

d^2= (8-4)^2 + (8-3)^2

d^2= (4)^2 + (5)^2

d^2= 16+ 25

d^2= 41

d= sqrt of 41*

d= 6.4units

The series ∑3ke − k/28 is a divergent series.

To determine whether the series ∑3ke − k/28 converges or diverges, we can use the ratio test.

The ratio test states that if lim┬(n→∞)⁡|an+1/an|<1, then the series converges absolutely; if lim┬(n→∞)⁡|an+1/an|>1, then the series diverges; and if lim┬(n→∞)⁡|an+1/an|=1, then the test is inconclusive.

Let's apply the ratio test to our series:

|a(n + 1)/a(n)| = |3(n + 1) [tex]e^(^-^(^n^+^1^)/28) / (3n e^(^-^n^/^2^8^))|[/tex]

= |(n+1)/n| * |[tex]e^(^-^1^/^2^8^)[/tex]| * |3/3|

= (1 + 1/n) * [tex]e^(^-^1^/^2^8^)[/tex]

As n approaches infinity, the expression (1 + 1/n) approaches 1, and [tex]e^(^-^1^/^2^8^)[/tex] is a constant. Therefore, the limit of the ratio is 1.

Since the limit of the ratio test is equal to 1, the test is inconclusive. We need to use another method to determine convergence or divergence.

One possible method is to use the fact that [tex]e^x > x^2^/^2[/tex] for all x > 0. This implies that [tex]e^(^-^k^/^2^8^)[/tex] < [tex](28/k)^2^/^2[/tex] for all k > 0.

Therefore,

|a(k)| = 3k [tex]e^(^-^k^/^2^8^)[/tex] < 3k[tex](28/k)^2^/^2[/tex]

= 42k/k²

= 42/k

Since ∑1/k is a divergent series, we can use the comparison test to conclude that ∑|a(k)| diverges.

Therefore, the series ∑3ke − k/28 also diverges.

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The determinant of the given matrix a is: det(a) = b2c2 + a2c2 + a2b2 - 2a2b2 - 2a2c2 + 2abc.

The determinant of a 3x3 matrix can be found using the formula:

det(A) = a11(a22a33 - a32a23) - a12(a21a33 - a31a23) + a13(a21a32 - a31a22)

Substituting the given matrix values, we get:

det(a) = 1(b2c2 - c(b2) + a2(c2) - c(a2) + a(b2) - a(b2)) - a(1c2 - c1 + a2c - c(a2) + a - a(a2)) + a(1b2 - b1 + a(b2) - b(a2) + a - a(b2))

Simplifying this expression, we get:

det(a) = b2c2 + a2c2 + a2b2 - a2b2 - b2c - a2c - a2b + a2c + abc - abc - a2c + ac2 + ab2 - ab2 - abc

Simplifying further, we get:

det(a) = b2c2 + a2c2 + a2b2 - 2a2b2 - 2a2c2 + 2abc

Thus, the determinant of the given matrix a is:

det(a) = b2c2 + a2c2 + a2b2 - 2a2b2 - 2a2c2 + 2abc.

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The linear equation of the plane through the origin and the points (5, 4, 2) and (3, -1, 1) is 6x + 1y - 17z = 0.

To find the linear equation of the plane through the origin and the points (5, 4, 2) and (3, -1, 1), you need to find a normal vector to the plane by taking the cross product of the position vectors of the two given points.

Position vector of point A(5, 4, 2): a = <5, 4, 2>
Position vector of point B(3, -1, 1): b = <3, -1, 1>

The cross product of a and b (normal vector to the plane): n = a × b
n = <(4*1 - 2*-1), (2*3 - 5*1), (5*-1 - 3*4)>
n = <4+2, 6-5, -5-12>
n = <6, 1, -17>

Now, the equation of the plane with normal vector n = <6, 1, -17> and passing through the origin (0, 0, 0) is given by: 6x + 1y - 17z = 0

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Given Set S is S spans P_2.

The set S = {1, x², 4 + x²} spans P_2 if every polynomial in P_2 can be expressed as a linear combination of 1, x², and 4 + x².

Let's consider a general polynomial in P_2, which has the form ax^2 + bx + c, where a, b, and c are constants. We need to determine if there exist constants k1, k2, and k3 such that:

ax² + bx + c = k1(1) + k2(x²) + k3(4 + x²)

Simplifying the right-hand side gives:

ax² + bx + c = (k2 + k3)x² + 4k3

For this equation to hold for all values of x, we must have a = k2 + k3, b = 0, and c = 4k3. Therefore, every polynomial in P_2 can be expressed as a linear combination of the elements in S if and only if we can find constants k1, k2, and k3 that satisfy these equations.

Solving the equations, we get:

k1 = 4k3 - a

k2 = a - k3

k3 is free

Since k3 is a free variable, we can choose it to be any value we like. This means that we can always find constants k1, k2, and k3 that satisfy the equations, and so S spans P_2.

Therefore, the answer is S spans P_2.

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We can assume that the sampling distribution of the sample mean is normally distributed and the probability that the sample mean falls between 75 and 77 is 0.4582 or 45.82%.

Sampling distribution of the sample mean is normally distributed

Use the standard normal distribution to evaluate the probability that the sample mean falls between 75 and 77.

First, lets calculate standard error of the mean:

SE = σ/√n

Since we are not given the population standard deviation (σ), we will use the sample standard deviation (s) as an estimate:

SE = s/√n

Next, we need to calculate the z-scores corresponding to 75 and 77:

z1 = (75 - x) / SE
z1 = (75 - x) / (s/√n)

z2 = (77 - x) / SE
z2 = (77 - x) / (s/√n)

Since the sampling distribution is normal, we can use a standard normal distribution table or a calculator to find the probabilities associated with these z-scores.

P(75 ≤ x ≤ 77) = P(z1 ≤ Z ≤ z2)

We find that:

P(-0.71 ≤ Z ≤ 0.71) = 0.4582

Therefore, the probability that the sample mean falls between 75 and 77 is 0.4582 or 45.82% (rounded to 4 decimal places).

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Hi! The value of MD for these data taken from a repeated-measures is 3.

To find the value of MD (Mean Difference) for the data from a repeated-measures research study, you need to follow these steps:
1. Calculate the difference between the 1st and 2nd scores for each subject.
2. Calculate the average of these differences.
Here are the steps applied to your data:

Subject  1st  2nd  Difference (2nd - 1st)
#1       10    15          5
#2        4     8          4
#3        7     5         -2
#4        6    11          5

Now, calculate the average of the differences:
(5 + 4 - 2 + 5) / 4 = 12 / 4 = 3

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For the function f(x) = -4x^3 + 5x^2 + 2x, the end behavior can be determined by looking at the degree and leading coefficient of the polynomial. Since the degree is odd and the leading coefficient is negative, the end behavior of the function will be downward in both the left and right quadrants. Therefore, the graph would be D) the arrow points downwards in the lower left and lower right quadrants.

For the function f(x) = (2x-3)(x+1), the end behavior can be determined by looking at the degree of the polynomial. Since the degree is 2, the end behavior will be the same as that of a quadratic function, which means that the graph will either be an upward or downward parabola. In this case, the graph would be A) the arrow points upwards in the upper left quadrant and downwards in the lower right quadrant, because the leading coefficient is positive.

For the function f(x) = 3x - 1, the end behavior is a straight line with a slope of 3. The arrow would be pointing upwards in both the left and right quadrants, so the graph would be B) the arrow points upwards in the upper left quadrant as well as in the upper right quadrant.

C) the arrow points upwards in the upper right quadrant and downwards in the lower left quadrant

This is because the function f(x) = -5x^2 (x+1) (x+3) is a cubic function with a leading coefficient of -5, which means that the end behavior of the function will be downward in the lower left quadrant and upward in the upper right quadrant.

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To use the integral test to determine the convergence of the series an = [tex]\frac{x+1}{x^{2} }[/tex], we need to check if the corresponding improper integral converges or diverges.

The integral test states that if f(x) is a positive, continuous, and decreasing function on the interval [1,inf], and if the series an = f(n) for all n in the interval [1,inf], then the series and the integral from 1 to infinity of f(x) both converge or both diverge.

In this case, we have f(x) = [tex]\frac{x+1}{x^{2} }[/tex]. First, we need to check if f(x) is positive, continuous, and decreasing on the interval [1,inf]. f(x) is positive for all x > 0. f'(x) =[tex]\frac{-2x-1}{x^{3} }[/tex] , which is negative for all x > 0. Therefore, f(x) is decreasing on the interval [1,inf].

Next, we need to evaluate the improper integral from 1 to infinity of f(x): integral from 1 to infinity of [tex]\frac{x+1}{x^{2} }[/tex] dx = lim t->inf integral from 1 to t of [tex]\frac{x+1}{x^{2} }[/tex] dx = lim t->inf [tex][\frac{-1}{t}-\frac{1}{t^{2}+t }][/tex] = 0

Since the improper integral converges to 0, the series an also converges by the integral test. Therefore, the series an [tex]\frac{x+1}{x^{2} }[/tex] is convergent on the interval [1,inf].

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Answer:

Have a Nice Best Day : ) i'm sorry there where no Answer

In Mathematics and Geometry, the rotation of a point 180° about the origin in a clockwise or counterclockwise direction would produce a point that has these coordinates (-x, -y).

Furthermore, the mapping rule for the rotation of a geometric figure about the origin is given by this mathematical expression:

(x, y)                                            →            (-x, -y)

Coordinates of point A (2, 1)  →  Coordinates of point A' = (-2, -1)

Coordinates of point B (4, -5)  →  Coordinates of point B' = (-4, 5)

In conclusion, this transformation rule (x, y) → (-x, -y) is used for the rotation of a geometric figure about the origin in a clockwise or counterclockwise (anticlockwise) direction.

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To multiply powers with the same base, add the exponents.

[tex] {a}^{8} {a}^{7} = {a}^{15} [/tex]

Let x be a discrete random variable. If Pr(x < 6) = 3/9, and Pr(x ≤ 6) = 7/18, then P(X = 6) is 0.06.

A discrete random variable is a variable that can take on only a countable number of values. Examples of discrete random variables include the number of heads when flipping a coin, the number of cars passing through an intersection in a given hour, or the number of students in a classroom.

Let x be a discrete random variable.

Pr(x < 6) = 3/9, and Pr(x ≤ 6) = 7/18

P(X ≤ 6) = P(X < 6) + P(X = 6)

Subtract P(X < 6) on both side, we get

P(X = 6) = P(X ≤ 6) - P(X < 6)

Substitute the values

P(X = 6) = 7/18 - 3/9

First equal the denominator

P(X = 6) = 7/18 - 6/18

P(X = 6) = 1/18

P(X = 6) = 0.06

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Therefore, the value of derivatives are-

[tex](a) If x = 10, dy/dt = -20\\(b) If x = 25, dy/dt = -8\\(c) If x = 50, dy/dt = -4[/tex]

To solve this problem, we need to use implicit differentiation. Taking the derivative of both sides with respect to time, we get:

[tex]\frac{d(xy)}{dt} = d(100)/dt[/tex]

Using the product rule and the fact that d(xy)/dt = x(dy/dt) + y(dx/dt), we can rewrite this as:
[tex]x(\frac{dy}{dt} + y\frac{dx}{dt} = 0[/tex]

Substituting in the given value for xy, we get:

[tex]10\frac{dy}{dt} + (100/x)\frac{dx}{dt} = 0[/tex]

Simplifying this equation, we get:

[tex]\frac{dy}{dt} = -(10/x)\frac{dx}{dt}[/tex]

Now we can use this equation to find dy/dt for different values of x:

[tex](a) If x = 10, \frac{dy}{dt} = -(10/10)(20) = -20\\(b) If x = 25, dy/dt = -(10/25)(20) = -8\\(c) If x = 50, dy/dt = -(10/50)(20) = -4[/tex]
Therefore, the answers are:

[tex](a) If x = 10, dy/dt = -20\\(b) If x = 25, dy/dt = -8\\(c) If x = 50, dy/dt = -4[/tex]

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Answer:

y=4

Step-by-step explanation:

3×−4y=8(−2−4)

Multiply 3 and −4 to get −12.

−12y=8(−2−4)

Subtract 4 from −2 to get −6.

−12y=8(−6)

Multiply 8 and −6 to get −48.

−12y=−48

Divide both sides by −12.

y=

−12

−48

​

Divide −48 by −12 to get 4.

y=4

Answer:

X= - 12

Step-by-step explanation:

3x-4*3=-16-32

3x-12= - 48

3x= - 48+12

3x= - 36

X= - 36:3

X = - 12

The statement is true. The point estimate of a population parameter is always at the centre of the confidence interval for the parameter.

To elaborate:
- "Point estimate" refers to a single value used as an estimate of a population parameter.
- "Population parameter" is a numerical value that characterizes a specific attribute of a population, such as its mean or proportion.
- "Confidence interval" is a range of values within which we are reasonably confident that the true population parameter lies.
In this context, when we construct a confidence interval for a population parameter, the point estimate is used as the central value, and the interval is built around it based on a specified level of confidence (e.g., 95%). False. The point estimate of a population parameter is not always at the centre of the confidence interval for the parameter. The confidence interval is a range of values that is likely to contain the true value of the parameter with a certain level of confidence. The point estimate is a single value that is calculated from a sample and used to estimate the population parameter. The centre of the confidence interval is determined by the level of confidence and the variability of the data, not necessarily the point estimate.

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