A1.1.1.5.1 Mastery Check The three sides of a triangle have lengths of x units, (x-4) units, and (x² - 2x - 5) units for some value of x greater than 4. What is the perimeter, in units, of the triangle? ​

The change of the coordinate matrix is P = | -1  5 |  |  4 -3 | from B to L.

And the  [x]L for x=5b1+3b2 is   |-10| | 11 |

B={b1, b2} and L={c1, c2} are bases for a vector space V. We know that b1=-c1+4c2 and b2=5c1-3c2. We want to find the change of the coordinate matrix from B to L and find [x]L for x=5b1+3b2.

a.  the change of the coordinate matrix from B to L, we need to express each b vector in terms of the L basis. We are given that b1=-c1+4c2 and b2=5c1-3c2. Write these as a column matrix:

P = | -1  5 |
      |  4 -3 |

This matrix P is the change of the coordinate matrix from B to L.

b. To find [x]L for x=5b1+3b2, we first express x in terms of B:

x = 5b1 + 3b2

Now, we want to find the coordinates of x in the L basis. To do this, we multiply the given x's B-coordinates with the change of coordinate matrix P:
[x]L = P[x]B

[x]L = | -1  5 | | 5 |
           |  4 -3 | | 3 |

[x]L = |-10| | 11 |

So, the coordinates of x in the L basis are [x]L = (-10, 11).

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Therefore, the variance of X1 is (\sigma1)2 = k = 6.

We know that the variance of Y can be expressed as[tex]Var(Y) = E[(3X2 - X1)^2] - E[3X2 - X1]^2.[/tex]
Expanding this expression, we get[tex]Var(Y) = E[9X2^2 - 6X1X2 + X1^2] - [3E(X2) - E(X1)]^2.[/tex]
Since X1 and X2 are stochastically independent, we have[tex]E(X1X2) = E(X1)E(X2).[/tex]
Therefore, [tex]Var(Y) = 9E(X2^2) - 6E(X1)E(X2) + E(X1^2) - 9E(X2)^2 + 6E(X1)E(X2) - E(X1)^2.[/tex]

Simplifying this expression, we get [tex]Var(Y) = 8E(X2^2) - E(X1^2) - E(X1)^2 - 9E(X2)^2.[/tex]

Substituting the given values, we have[tex]Var(Y) = 8(2) - k - k - 9(2) = 25.[/tex]

Solving for k, we get k = 6.

Therefore, the variance of X1 is (\sigma1)2 = k = 6.

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The equation about the two angles must be true is  

D) cos 36 = sin 54.

What is complementary angles?

We know that when sum of two angles is add upto 90° then that is called as complementary angles and the equation must be cos A = sin B.

Then, [tex]\angle A+\angle B=90\textdegree[/tex]

Now solving the options then,

A) 54°+54°=108°≠90°

Then the equation is false.

B) Here sin 36=sin 54 is not correct equation.

C) 36°+36°=72°≠90°

Then the equation is false.

D) 36°+54° = 90°=90°

Then the equation is true.

Hence the equation about the two angles must be true is  

D) cos 36 = sin 54.

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The sum of the series [infinity] an n = 1 whose partial sums are given by sn = 4 − 3(0.7)n is 4.

To find the sum of the series [infinity] an n = 1, we need to take the limit as n approaches infinity of the partial sum formula. In this case, we have:

sn = 4 − 3(0.7)n

Taking the limit as n approaches infinity, we get:

lim n→∞ sn = lim n→∞ (4 − 3(0.7)n)

Since 0.7^n approaches zero as n approaches infinity, we have:

lim n→∞ sn = 4 - 0 = 4

Therefore, the sum of the series [infinity] an n = 1 whose partial sums are given by sn = 4 − 3(0.7)n is 4.

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The probability of pulling 2 green marbles from the bag is 3/29

From the question, there are a total of 30 marbles in the bag.

The probability of pulling a green marble on the first draw is 10/30.

After removing one green marble, there are now 9 green marbles left in the bag out of a total of 29 marbles.

The probability of pulling another green marble on the second draw is 9/29.

Therefore, the probability of pulling 2 green marbles from the bag is (10/30) * (9/29) = 3/29

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Answer:

the first one

Step-by-step explanation:

the first one is correct

Answer:

the first one

Step-by-step explanation:

the first one is correct

a) At least 5,675 adults.

b) if we use the results from the 2014 survey, we still need to survey at least 5,675 adults.

c) It does not have much of an effect on the sample size.

Sample size refers to the number of observations or participants included in a study or survey. In statistical analysis, the size of the sample is an important consideration as it can affect the accuracy and reliability of the results. A larger sample size generally leads to more precise estimates and increased statistical power, while a smaller sample size may be more susceptible to sampling errors and variability.

(a) To find the minimum sample size needed, we can use the formula:

n = (z² × p × (1-p)) / E²

where z is the z-score corresponding to the desired confidence level (99%), p is the estimated proportion of e-cigarette users (3.65% or 0.0365), and E is the desired margin of error (3 percentage points or 0.03).

Plugging in these values, we get:

n = (2.576² × 0.0365 × 0.9635) / 0.03²

n = 5,674.85

Rounding up to the nearest integer, we get:

n = 5,675

Therefore, we need to survey at least 5,675 adults to obtain today's e-cigarette usage rate with a 99% confidence level and a margin of error of 3 percentage points.

(b) If we use the results from the 2014 survey, we can estimate the population proportion of e-cigarette users as 0.0365. Using the same formula as above, we get:

n = (2.576² × 0.0365 × 0.9635) / 0.03²

n = 5,674.85

Rounding up to the nearest integer, we get:

n = 5,675

Therefore, even if we use the results from the 2014 survey, we still need to survey at least 5,675 adults to obtain today's e-cigarette usage rate with a 99% confidence level and a margin of error of 3 percentage points.

(c) The use of the results from the 2014 survey does not have much of an effect on the sample size. This is because the desired confidence level and margin of error are fixed, and the estimated proportion from the 2014 survey is relatively close to the true proportion (since e-cigarette use is still a relatively new phenomenon).

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Claire fed Folly at 2 pm, gave Folly to Max at 2:10 pm. Folly belonged to either Max or Claire at 2:05 pm. Neither Mar nor Claire fed Folly at 2 pm or 2:05 pm. The event occurred between 1:55 pm and 2:05 pm. At 2 pm, Max took Folly from Claire. Folly wasn't hungry at 2 pm but was at 3 pm.

1. student(Mar) ∧ ¬pet(Mar)2. fed(Claire, Folly, 2pm) ∧ gave(Claire, Folly, Max, 2:10pm)3. (belongs(Folly, Max, 2:05pm) ∨ belongs(Folly, Claire, 2:05pm))4. ¬(fed(Mar, Folly, 2pm) ∨ fed(Claire, Folly, 2pm) ∨ fed(Mar, Folly, 2:05pm) ∨ fed(Claire, Folly, 2:05pm))5. between(2pm, 1:55pm, 2:05pm)6. ¬hungry(Folly, 2pm) ∧ hourLater(Folly, 2pm, 3pm)

1. Student(Mar) ∧ ¬Pet(Mar)2. Fed(Claire, Folly, 2pm) ∧ Gave(Claire, Folly, Max, 2:10pm)3. BelongsTo(Folly, Max, 2:05pm) ∨ BelongsTo(Folly, Claire, 2:05pm)4. ¬(Fed(Mar, Folly, 2pm) ∨ Fed(Claire, Folly, 2pm) ∨ Fed(Mar, Folly, 2:05pm) ∨ Fed(Claire, Folly, 2:05pm))

5. Between(2:00pm, 1:55pm, 2:05pm)6. Gave(Max, Folly, Claire, 2pm) ∧ ¬Hungry(Folly, 2pm) ∧ Hungry(Folly, 3pm)

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The standard rotation matrix for a clockwise rotation of 135 degrees about the origin is:
  | cos(-(3π) / 4)  -sin(-(3π) / 4) |
  | sin(-(3π) / 4)   cos(-(3π) / 4) |

To find the standard matrix of the given linear transformation from R2 to R2, which involves a clockwise rotation through 135 degrees about the origin, we can follow these steps,

1. Convert the angle to radians: 135 degrees = (135 * π) / 180 = (3π) / 4 radians.

2. Since the rotation is clockwise, the angle should be negative: -135 degrees = -(3π) / 4 radians.

3. Compute the cosine and sine values for the angle: cos(-135°) = cos(-(3π) / 4) and sin(-135°) = sin(-(3π) / 4).

4. Fill in the standard rotation matrix with the computed values:
  | cosθ  -sinθ |
  | sinθ   cosθ |

In our case, the standard rotation matrix for a clockwise rotation of 135 degrees about the origin is:
  | cos(-(3π) / 4)  -sin(-(3π) / 4) |
  | sin(-(3π) / 4)   cos(-(3π) / 4) |

This is the standard matrix for the given linear transformation involving a matrix and a clockwise rotation through 135 degrees about the origin.

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The number of bit strings of length 9 that either begin with two 0s, have eight consecutive 0s, or end with a 1 bit is 321.

Let A be the set of bit strings of length 9 that begin with two 0s, B be the set of bit strings of length 9 that have eight consecutive 0s, and C be the set of bit strings of length 9 that end with a 1 bit.

We want to find the number of bit strings that are in at least one of these sets. We can use the inclusion-exclusion principle to calculate this number as follows:

|A ∪ B ∪ C| = |A| + |B| + |C| - |A ∩ B| - |A ∩ C| - |B ∩ C| + |A ∩ B ∩ C|

|A| = 2^7 = 128, since there are 7 remaining bits after the first two bits are fixed at 0.

|B| = 2 = 2^1, since there are only two possible strings with eight consecutive 0s (000000000 and 100000000).

|C| = 2^8 = 256, since there are 8 remaining bits after the last bit is fixed at 1.

To calculate |A ∩ B|, we fix the first two bits as 0 and the next 7 bits as 1. This gives us one string that is in both A and B: 000000011.

Therefore, |A ∩ B| = 1.

To calculate |A ∩ C|, we fix the last bit as 1 and the first two bits as 0. This gives us 2^6 = 64 strings that are in both A and C.

Therefore, |A ∩ C| = 64.

To calculate |B ∩ C|, we fix the last bit as 1 and the next 7 bits as 0. This gives us one string that is in both B and C: 000000001.

Therefore, |B ∩ C| = 1.

To calculate |A ∩ B ∩ C|, we fix the first two bits as 0, the last bit as 1, and the remaining 6 bits as 0. This gives us one string that is in all three sets: 000000001.

Therefore, |A ∩ B ∩ C| = 1.

Substituting all these values into the inclusion-exclusion formula, we get:

|A ∪ B ∪ C| = 128 + 2 + 256 - 1 - 64 - 1 + 1

= 321

Therefore, the number of bit strings of length 9 that either begin with two 0s, have eight consecutive 0s, or end with a 1 bit is 321.

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The data set that shows greater variability is Data set B.

Mean Absolute Deviation, abbreviated as M.A.D, quantifies the variability in a dataset by measuring how much its data points deviate from their mean.

This deviation delivers an accurate measure of spread, based on which one can determine if the information is clustered or dispersed relative to the mean. Supposing M.A.D yields a small value, it reflects that data points are closely grouped around the average, implying there is low dispersion; conversely, large values signify widespread distribution from the mean indicating high variation among data points.

Data set B has a larger variability as a result, because it has a larger value of MAD.

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For 4 decimal places (0.0001), the minimal degree Taylor polynomial is of degree 9. For 7 decimal places (0.0000001), the minimal degree Taylor polynomial is of degree 13

To calculate sin(1) to 4 decimal places, we need to find the minimal degree Taylor polynomial about x=0. The Taylor series for sin(x) is:

sin(x) = x - (x^3/3!) + (x^5/5!) - (x^7/7!) + ...

To find the minimal degree polynomial that gives sin(1) to 4 decimal places, we need to find the first few terms of the series that contribute to the first 4 decimal places of sin(1).

If we evaluate sin(1) using the first two terms of the series, we get:

sin(1) ≈ 1 - (1^3/3!) = 0.83333

This is accurate to only one decimal place. If we evaluate sin(1) using the first three terms of the series, we get:

sin(1) ≈ 1 - (1^3/3!) + (1^5/5!) = 0.84147

This is accurate to 4 decimal places. Therefore, the minimal degree Taylor polynomial about x=0 that we need to calculate sin(1) to 4 decimal places is degree 3.

To calculate sin(1) to 7 decimal places, we need to find the first few terms of the series that contribute to the first 7 decimal places of sin(1). If we evaluate sin(1) using the first four terms of the series, we get:

sin(1) ≈ 1 - (1^3/3!) + (1^5/5!) - (1^7/7!) = 0.8414710

This is accurate to 7 decimal places.

Therefore, the minimal degree Taylor polynomial about x=0 that we need to calculate sin(1) to 7 decimal places is degree 4.

To approximate sin(1) using a Taylor polynomial with x = 0, you'll need to determine the minimal degree required to achieve the desired accuracy.

For 4 decimal places (0.0001), the minimal degree Taylor polynomial is of degree 9. This is because the Taylor series for sin(x) contains only odd degree terms, and using a 9th-degree polynomial will give you the required precision.

For 7 decimal places (0.0000001), the minimal degree Taylor polynomial is of degree 13. Similarly, this is because the Taylor series for sin(x) contains only odd degree terms, and using a 13th-degree polynomial will give you the required precision.

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Rounded to four decimal places, the answer is 0.7595, which is closest to option (a) 0.7598.

To find the total area between z=-0.75 and z=2.21, we need to find the area under the standard normal curve between these two z-values.

Using the standard normal table, we can find the area under the curve to the left of z=2.21 and subtract the area under the curve to the left of z=-0.75, as follows:

Area between z=-0.75 and z=2.21 = Area to the left of z=2.21 - Area to the left of z=-0.75

From the standard normal table, we can find that the area to the left of z=2.21 is 0.9861, and the area to the left of z=-0.75 is 0.2266.

Therefore, the total area between z=-0.75 and z=2.21 is:

Area between z=-0.75 and z=2.21 = 0.9861 - 0.2266 = 0.7595

Rounded to four decimal places, the answer is 0.7595, which is closest to option (a) 0.7598.

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The series ∑n=1[infinity]n!(x−4)n converges for all values of x except x=4.

This is because when x=4, each term in the series becomes n! * 0ⁿ, which equals 0. Therefore, the series fails the nth term test for divergence and does not converge at x=4. For all other values of x, the series converges by the ratio test.

The ratio test states that if the limit of the absolute value of the ratio of consecutive terms of a series is less than 1, then the series converges. Applying the ratio test to our series, we get:

| (n+1)! * (x-4ⁿ⁺¹ / n!(x-4)ⁿ | = (n+1) |x-4|

Taking the limit as n approaches infinity, we see that this approaches infinity if |x-4| > 1 and approaches 0 if |x-4| < 1. Therefore, the series converges if |x-4| < 1, which means the values of x that make the series converge are x ∈ (3,5).

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Step-by-step explanation:

One out of six chance of rolling a '2'    = 1/6

one out of two chance of landing on tails    = 1/2

1/6 * 1/2 = 1/12  

Solution to the initial-value problem with the given initial condition y(0) = 5 and differential equation [tex]dy/dt = e^{7t[/tex].

We are given the following:

1. Initial condition: y(0) = 5
2. Differential equation: dy/dt = e^(7t)

Here's a step-by-step solution:

Step 1: Integrate both sides of the differential equation with respect to t.
∫(dy/dt) dt = ∫[tex]e^{7t[/tex] dt

Step 2: Integrate the right side.
y(t) = (1/7)[tex]e^{7t[/tex] + C, where C is the integration constant.

Step 3: Apply the initial condition, y(0) = 5.
5 = (1/7)[tex]e^{7*0[/tex] + C

Step 4: Solve for the integration constant, C.
5 = (1/7)[tex]e^0[/tex] + C
5 = (1/7)(1) + C
C = 5 - 1/7
C = 34/7

Step 5: Write the final solution for y(t).
y(t) = (1/7)[tex]e^{7t[/tex] + 34/7

This is the solution to the initial-value problem with the given initial condition y(0) = 5 and differential equation [tex]dy/dt = e^{7t[/tex].

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The equation you provided is:

8x - 6y + z = 4

The cylindrical coordinates of ta given equation is 8r * cos(θ) - 6r * sin(θ) + z = 4

To convert this equation into cylindrical coordinates, we'll use the following conversions:

x = r * cos(θ)
y = r * sin(θ)
z = z

Substitute these conversions into the equation:

8(r * cos(θ)) - 6(r * sin(θ)) + z = 4

Now, simplify the equation:

8r * cos(θ) - 6r * sin(θ) + z = 4

So, the given equation in cylindrical coordinates is:

8r * cos(θ) - 6r * sin(θ) + z = 4

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The correct option: B. 8.19 X 10⁹ dollars. Thus, spending on mangers each year by national restaurant chain is  8.19 X 10⁹ dollars.

With scientific notation, one can express extremely big or extremely small values. When one number between 1 and 10 was multiplied by a power of 10, the result is represented in scientific notation.

Exponents but a base of 10 are used in this technique to write very big or extremely tiny numbers. You can simplify arithmetic processes and record quantities that are difficult to represent in decimal form by becoming familiar with writing in scientific notation.

Given data:

Number of managers in national restaurant  =  2.1 x 10⁵ .

Earning of each manager = $39,000 per year.

Spending on mangers each year = Number of managers in national restaurant  x Earning of each manager

Spending on mangers each year = 2.1 x 10⁵ x 39,000

Spending on mangers each year = 8.19 X 10⁹ dollars

Thus, spending on mangers each year by national restaurant chain is  8.19 X 10⁹ dollars.

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Complete question:

A national restaurant chain has 2.1 x 10⁵ managers. Each manager makes $39,000 per year. How much does the restaurant chain spend on mangers each year?

A. 2.49 X 10⁸ dollars

B. 8.19 X 10⁹ dollars

C. 6 x 10⁹ dollars

D. 8.19 X 10²⁰ dollars

For a point P(x,y) on the terminal side of an angle θ in standard position, we let r=[tex]\sqrt{(x^2+y^2).}[/tex] Then sin θ= y/r, [tex]cos θ= x/r[/tex], and [tex]tan θ= y/x[/tex].

When we have a point P(x,y) on the terminal side of an angle θ in standard position, we can define r as the distance from the origin to P, which can be calculated using the Pythagorean theorem as r=[tex]\sqrt{(x^2+y^2)}[/tex]. Then, we can use this value of r to find the sine, cosine, and tangent of the angle θ. By using Pythagorean theorem

The sine of the angle θ is defined as the ratio of the y-coordinate of P to r, i.e., sin θ= [tex]\frac{y}{r}[/tex]. Similarly, the cosine of the angle θ is defined as the ratio of the x-coordinate of P to r, i.e., cos θ=[tex]\frac{x}{r}[/tex]. Finally, the tangent of the angle θ is defined as the ratio of the y-coordinate of P to the x-coordinate of P, i.e., tan θ= [tex]\frac{x}{y}[/tex].

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The general solution to the differential equation y''+y=sin(2x) is y(x) = c1cos(x) + c2sin(x) - x/4cos(2x) + Csin(2x)

[tex]u''(x)*(1 + cos(4x))/2 + v''(x)*sin(4x)/2 - 2u'(x)*sin(2x) + u(x)*cos(2x) + 2v'(x)*cos(2x) + v(x)*sin(2x) = sin(2x)/2[/tex]

[tex](1 + cos(4x))/2 * u''(x) + sin(4x)/2 * v''(x) + cos(2x) * u(x) + sin(2x) * v(x) = 0-2 * sin(2x) * u'(x) + 2 * cos(2x) * v'(x) = sin(2x)/2[/tex]

       [tex]u''(x) = -cos(2x)*sin(2x)/2\\v''(x) = (1-cos^2(2x))/2\\u'(x) = -1/4\\v'(x) = 0\\[/tex]

       u(x) = -x/4

       v(x) = C, where C is an arbitrary constant.

       [tex]y_p(x) = -x/4cos(2x) + Csin(2x)[/tex]

       [tex]y(x) = y_h(x) + y_p(x) = c1cos(x) + c2sin(x) - x/4cos(2x) + Csin(2x)[/tex]

So the general solution to the differential equation y''+y=sin(2x) is y(x) = c1cos(x) + c2sin(x) - x/4cos(2x) + Csin(2x), where c1, c2, and C are constants that depend on the initial conditions.

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Mr. Chen's statement is incorrect because 5 hundreds - 3 hundreds does not equal 2 hundreds. 5 hundreds - 3 hundreds equals 2 hundreds and eighty, which is 288. Therefore, Mr. Chen needs a total of 512 - 384 = 128 grams of loose green tea.

Answer:

1, 2, 2, 4, 8, 32

Step-by-step explanation:

a₁ = 1

a₂ = 2

a₃ = a₂ × a₁ = 2 × 1 = 2

a₄ = a₃ × a₂ = 2 × 2 = 4

a₅ = a₄ × a₃ = 4 × 2 = 8

a₆ = a₅ × a₄ = 8 × 4 = 32

the first six terms are 1, 2, 2, 4, 8, 32

The first six terms of the recursively defined sequence are: 1, 2, 2, 4, 8, 32.

A recursively defined sequence is a sequence of numbers that is defined in terms of the previous terms in the sequence. In other words, each term in the sequence is defined as a function of one or more previous terms. This type of sequence is also known as a recurrence relation.

To give the first six terms of the sequence where the first term is 1 and the second term is 2, and the rest of the terms are the product of the two preceding terms, follow these steps:

1. Write down the first two terms: 1, 2
2. Find the third term by multiplying the first and second terms: 1 * 2 = 2
3. Find the fourth term by multiplying the second and third terms: 2 * 2 = 4
4. Find the fifth term by multiplying the third and fourth terms: 2 * 4 = 8
5. Find the sixth term by multiplying the fourth and fifth terms: 4 * 8 = 32

So, the first six terms of the recursively defined sequence are: 1, 2, 2, 4, 8, 32.

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To determine the maximum tensile and compressive stress acting in the built-up beam, we need to use the formula σ = M*c/I

Where:
σ = stress
M = internal moment (75 kN⋅m in this case)
c = distance from the neutral axis to the extreme fiber
I = moment of inertia

Since the built-up beam is made up of multiple materials, we need to first calculate the moment of inertia for the entire cross-section. Let's assume the beam is rectangular in shape with dimensions of 200 mm (height) and 100 mm (width). The built-up section consists of two materials - steel and wood, with steel being on the top and bottom of the section. Let's assume the steel has a thickness of 10 mm and the wood has a thickness of 80 mm.

To calculate the moment of inertia, we need to first find the individual moments of inertia for each material:

For the steel:
I_st = (b*h^3)/12
I_st = (100*10^3)/12
I_st = 8.33 x 10^6 mm^4

For the wood:
I_wd = (b*h^3)/12
I_wd = (100*80^3)/12
I_wd = 6.44 x 10^8 mm^4

Now we can calculate the total moment of inertia:
I_total = I_st + I_wd
I_total = 6.52 x 10^8 mm^4

Next, we need to find the distance from the neutral axis to the extreme fiber. Since the beam is symmetric about the horizontal axis, the neutral axis is located at the center of the section. The distance from the center to the top or bottom of the section is:
c = h/2
c = 200/2
c = 100 mm

Finally, we can calculate the maximum tensile and compressive stress using the formula:
σ = M*c/I

For tension:
σ_tension = (75*10^3*100)/(6.52*10^8)
σ_tension = 1.15 MPa

For compression:
σ_compression = -(75*10^3*100)/(6.52*10^8)
σ_compression = -1.15 MPa

Therefore, the maximum tensile stress is 1.15 MPa and the maximum compressive stress is -1.15 MPa (which is equal in magnitude to the tensile stress).

Note that the negative sign indicates compression.

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The graph of the parabola (x- 5 )²/25 - (y + 3)²/36 = 1 is added as an attachment

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

(X-5)2/25 - (y+3)2/36 = 1.

Express the equation properly

So, we have

(x- 5 )²/25 - (y + 3)²/36 = 1

The above expression is a an equation of a conic section

Next, we plot the graph using a graphing tool

To plot the graph, we enter the equation in a graphing tool and attach the display

See attachment for the graph of the function

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(a) The equation of the least squares line is: Y = -0.901X + 148.35.

(b) The coefficient of determination is 0.771.

(c) The estimate of the error standard deviation is 5.47 MPa.

(a) To obtain the equation of the least squares line, we need to calculate the slope and intercept of the regression line.

Using the given data, we can calculate the sample means and standard deviations of x and y as follows:

x-bar = [tex](112.3 + 97.0 + 92.7 + 86.0 + 102.0 + 99.2 + 95.8 + 103.5 + 89.0 + 86.7)/10 = 94.2[/tex]

[tex]s_x = sqrt(((112.3-94.2)^2 + (97.0-94.2)^2 + ... + (86.7-94.2)^2)/9) = 9.83[/tex]

[tex]y-bar = (75.1 + 70.6 + 58.2 + 49.1 + 74.0 + 74.0 + 73.3 + 68.2 + 59.6 + 57.4 + 48.2)/11 = 65.27[/tex]

[tex]s_y = sqrt(((75.1-65.27)^2 + (70.6-65.27)^2 + ... + (48.2-65.27)^2)^/^1^0^) = 10.99[/tex]

The correlation coefficient between x and y can be calculated as:

r =[tex]Σ[(x - x-bar)/s_x][(y - y-bar)/s_y]/(n-1) = -0.944[/tex]

The slope of the regression line can be calculated as:

b = [tex]r*s_y/s_x = -0.901[/tex]

The intercept of the regression line can be calculated as:

a =[tex]y-bar - b*x-bar = 148.35[/tex]

Therefore, the equation of the least squares line is:

Y = -0.901X + 148.35

(b) The coefficient of determination, denoted as [tex]R^2[/tex], is a measure of the proportion of the total variation in y that is explained by the regression on x. It can be calculated as:

[tex]R^2[/tex] = (SSR/SST) = 1 - (SSE/SST)

where SSR is the sum of squares due to regression, SSE is the sum of squares due to error, and SST is the total sum of squares.

Using the given data, we can calculate the following:

SST = Σ[tex](y - y-bar)^2[/tex] = 1146.16

SSE = Σ[tex](y - ŷ)^2 = 261.70[/tex]

SSR = Σ[tex](ŷ - y-bar)^2 = 884.46[/tex]

where[tex]ŷ[/tex]is the predicted value of y based on the regression line.

Therefore,

[tex]R^2[/tex]= SSR/SST = 0.771

The coefficient of determination is 0.771, which means that approximately 77.1% of the total variation in y is explained by the regression on x.

(c) The estimate of the error standard deviation, denoted as σ, can be calculated as:

σ = sqrt(SSE/(n-2)) = 5.47

where n is the sample size.

Therefore, the estimate of the error standard deviation is 5.47 MPa. This value represents the typical amount of variability in the axial strength that is not explained by the linear relationship with cube strength.

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The lines can divide the plane such that :

General position means that no two lines are parallel and no three lines intersect at a single point. When lines are in general position, we can count the number of bounded and unbounded regions they divide the plane.

The plane is divided into 2 unbounded and 0 bounded sections by 1 line. The plane is divided into 1 bounded and 4 unbounded sections by 2 lines. The plane is divided into 4 bounded and 6 unbounded sections by 3 lines. The plane is divided into 11 bounded and 8 unbounded sections by 4 lines.

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The lower bound of the 99% confidence interval for the population proportion of employed individuals who work at home at least once per week is 0.086.

To construct the 99% confidence interval for the population proportion (p), first find the sample proportion (p-hat) by dividing the number of people who work at home (41) by the total sample size (350): p-hat = 41/350 = 0.117.

Next, determine the standard error (SE) using the formula SE = √(p-hat * (1 - p-hat) / n) = √(0.117 * (1 - 0.117) / 350) ≈ 0.026. For a 99% confidence interval, use a z-score of 2.576.

Finally, calculate the margin of error (ME) by multiplying the z-score by the SE: ME = 2.576 * 0.026 ≈ 0.067. The lower bound of the 99% confidence interval is p-hat - ME: 0.117 - 0.067 = 0.086 (rounded to three decimal places).

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Answer:

Point-circle

Step-by-step explanation:

The equation x^2 + y^2 = 0 represents a point circle.

To see why, note that any point (x, y) that satisfies this equation must have x^2 = 0 and y^2 = 0, since the sum of two non-negative numbers is zero only when both are zero. This implies that x = 0 and y = 0, so the only point that satisfies the equation is the origin (0, 0).

Therefore, the equation x^2 + y^2 = 0 represents a circle with radius zero, which is a point circle at the origin. The appropriate description for the equation is a point circle.

There is a 21.5% chance that the stock's price will exceed $105 after 10 days.

Given that the daily change of price of the company's stock has a mean of 0 and variance of 1 (σ2=1), we know that the standard deviation is σ=1. Using the formula for the mean and variance of the sum of independent random variables, we can find that the mean of the stock's price after 10 days is 0 and the variance is 10σ2=10.

To find the probability that the stock's price will exceed $105 after 10 days, we need to calculate the probability of the standardized variable being greater than (105-100)/σ√10, where σ√10 is the standard deviation of the sum of the 10 independent random variables.

Thus, the probability that the stock's price will exceed $105 after 10 days is the same as the probability that a standard normal variable Z is greater than 0.79 (=(105-100)/1√10). Using a standard normal distribution table or a calculator, we find that this probability is approximately 0.215, or 21.5%.

Therefore, we can say that there is a 21.5% chance that the stock's price will exceed $105 after 10 days.

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To find the linearization l(x) of the function at a=32, we need to first calculate the slope or derivative of the function at a) f'(x) = (4/5)x^(-1/5).

Now we can use the point-slope form of a line to find the linearization: l(x) = f(a) + f'(a)(x-a), Substituting the values we get: l(x) = f(32) + f'(32)(x-32)
l(x) = (32^(4/5)) + ((4/5)(32^(-1/5)))(x-32)

Therefore, the linearization of the function at a=32 is l(x) = (32^(4/5)) + ((4/5)(32^(-1/5)))(x-32).
To find the linearization L(x) of the function f(x) = x^(4/5) at a = 32, we need to find the equation of the tangent line at that point. The formula for linearization is L(x) = f(a) + f'(a)(x - a).

First, find f(a):
f(32) = (32)^(4/5) = 16, Next, find the derivative f'(x):
f'(x) = (4/5)x^(-1/5)

Now, find f'(a):
f'(32) = (4/5)(32)^(-1/5) = (4/5)(1/2) = 2/5, Finally, plug these values into the linearization formula:
L(x) = 16 + (2/5)(x - 32), So, the linearization L(x) of the function f(x) = x^(4/5) at a = 32 is L(x) = 16 + (2/5)(x - 32).

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