martha and axel went to the store to buy 3 apple, but only had a buget of 5 dollars

Prove for all real numbers x and y, if

[tex]x − ⎣x⎦ ≥ y − ⎣y⎦ then ⎣x − y⎦ = ⎣x⎦ − ⎣y⎦.[/tex]

Given :

[tex]x − ⎣x⎦ ≥ y − ⎣y⎦[/tex]

To Prove :

⎣x − y⎦ = ⎣x⎦ − ⎣y⎦.

Proof :

Let[tex]A = ⎣x⎦, B = ⎣y⎦, C = ⎣x − y⎦.[/tex]

Since A ≤ x < A + 1,

we have

A − B ≤ x − y < A + 1 − B

This implies that C = ⎣x − y⎦ lies between A − B and A + 1 − B;

that is, A − B ≤ C ≤ A + 1 − B.

But the only integers that lie between A and A + 1 are A itself and A + 1.

Therefore, either

C = A or C = A − 1 or, equivalently,

[tex]⎣x − y⎦ = ⎣x⎦ or ⎣x − y⎦ = ⎣x⎦ − 1,[/tex]

but in the second case, we have

⎣x⎦ − ⎣y⎦ > x − y, which contradicts the assumption that

[tex]x − ⎣x⎦ ≥ y − ⎣y⎦.[/tex]

Hence,[tex]⎣x − y⎦ = ⎣x⎦ − ⎣y⎦[/tex]

for all real numbers x and y, if

[tex]x − ⎣x⎦ ≥ y − ⎣y⎦.[/tex]

Therefore, the given statement is proved.

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The level of measurement of the data collected in this study, which is the number of cousins a person has, is ratio level.

The ratio level of measurement provides the most information about the data, including the ability to rank order the data, determine the equal intervals between values, and identify the true zero point.

In this case, the number of cousins can be ranked (e.g., someone with 5 cousins has more than someone with 2 cousins), there are equal intervals between values (the difference between 2 and 3 cousins is the same as the difference between 6 and 7 cousins), and there is a true zero point (having no cousins).

This distinguishes ratio level data from the other levels of measurement:

1. Nominal level: only classifies data into categories without any order or ranking. In this study, the number of cousins is not simply categorized, but it can be ranked and compared quantitatively.

2. Ordinal level: allows for the ranking of data, but the distances between the data points are not equal or known. In this case, the distances between the number of cousins are equal and can be easily determined.

3. Interval level: has equal intervals between data points and allows for ranking, but lacks a true zero point. In this study, there is a true zero point (having no cousins), so it's not interval level data.

In summary, the level of measurement of the data collected in this study is ratio level because it has a true zero point, equal intervals between values, and allows for ranking.

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the amount of work done is 5π².

The work done W is given by the line integral:

W = ∫ F · dr

where F is the force field and dr is the differential displacement along the curve r(t).

We can write r(t) as:

r(t) = (sin t, cos t, t), for 0 ≤ t ≤ 2π

The differential displacement dr is given by:

dr = (dx, dy, dz) = (cos t, -sin t, 1) dt

Now we can evaluate F · dr as:

F · dr = (5z, 5x, 5y) · (cos t, -sin t, 1) dt

= 5z cos t - 5x sin t + 5y dt

= 5t dt

since z = t, x = sin t, and y = cos t.

Therefore, the work done is:

W = ∫ F · dr = ∫₀²π 5t dt = [5t²/2] from 0 to 2π

= 5(2π²/2) - 5(0²/2)

= 5π²

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The area of the regular polygon is 93.53 square feet

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

using the above as a guide, we have the following:

Area = 6 * Area of triangle

Where

Area of triangle = 1/2 * radius² * sin(60)

substitute the known values in the above equation, so, we have the following representation

Area = 6 * 1/2 * radius² * sin(60)

So, we have

Area = 6 * 1/2 * 6² * sin(60)

Evaluate

Area = 93.53

Hence, the area is 93.53

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D(x) is the length of side AC of a right-angled triangle with sides AB and BC equal to x, and all sides enclosing an area of 24 square meters.

Therefore, D(x) = √[(24 - 2x)² - x²].

Since the triangle is right-angled, let the length of AB be x meters. Then, the length of BC must also be x meters since all the fencing is used for sides AB and BC. Let the length of AC be y meters. We can use the Pythagorean theorem to write:

x² + y² = AC²

Since AC is given to be a fixed length (the length of the existing brick wall), we can solve for y in terms of x:

y² = AC² - x²

y = √(AC² - x²)

The total length of fencing used is 24 meters, so:

AB + BC + AC = 24

x + x + AC = 24

AC = 24 - 2x

Substituting this expression for AC into the equation for y, we get:

y = √[(24 - 2x)² - x²]

Therefore, D(x) = √[(24 - 2x)² - x²].

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The answer is d. 18. There are a total of 18 choices of passageways for entering the classroom.

To determine the number of choices of passageways, we need to consider the options at each step. From the ground floor to the second floor, there are 3 staircases, so we have 3 choices. From the second floor to the third floor, there are also 3 staircases, giving us another 3 choices. Now, for each classroom on the third floor, there are 2 doors, so we have 2 choices for each classroom. Since there are a total of 6 classrooms (assuming one classroom per staircase), we multiply the number of choices per classroom by the number of classrooms, which gives us 2 * 6 = 12 choices. Finally, we add up the choices from each step: 3 + 3 + 12 = 18. Therefore, there are 18 choices of passageways in entering the classroom.

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The number of photons emitted per second by the flashlight is approximately 3.4 x 10¹⁸.

To determine the number of photons emitted per second by the flashlight, we can use the formula

number of photons = (power of light)/(energy per photon x frequency)

The energy per photon can be calculated using the Planck's equation

energy per photon = (Planck's constant x frequency)

Substituting the given values, we get

energy per photon = (6.626 x 10³⁴ J s) x (5.2 x 10¹⁴ Hz) = 3.45 x 10¹⁹ J

Now, substituting the values into the first formula, we get

number of photons = (2.9 W)/(3.45 x 10¹⁹ J x 5.2 x 10¹⁴ Hz)

number of photons = 3.4 x 10¹⁸ photons/s

Therefore, the flashlight emits 3.4 x 10¹⁸ photons per second.

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The total number of seeds that Josiah would plant would be = nR×S

To determine the total number of seeds that Josiah will plant will be to add the seeds in the total number of rooms he planted.

Let each row be represented as = nR

Where n represents the number of rows planted by him.

Let the seed be represented as = S

The total number of seeds he planted = nR×S

Therefore, the total number of seeds that was planted Josiah would be = nR×S.

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Answer: a. The sequence of 6 coin tosses can have 2^6 = 64 different outcomes. This is because each coin flip has two possible outcomes (heads or tails), and there are 6 independent coin flips.

b. To calculate the probability of different outcomes for f(6), we need to consider the number of ways each outcome can occur divided by the total number of possible outcomes.

Probability of f(6) = 0:

To end up at 0, Scott needs to have an equal number of heads and tails. This can happen in two ways: HHTTTT or TTHHHH. So, the probability of f(6) = 0 is 2/64 = 1/32.

Probability of f(6) = 1:

To end up at 1, Scott needs to have 4 tails and 2 heads. This can happen in six ways: TTHHHT, TTHHTH, TTHTHH, TTHTHH, THTTHH, or HTTTHH. So, the probability of f(6) = 1 is 6/64 = 3/32.

Probability of f(6) = 6:

To end up at 6, Scott needs to have 6 heads and no tails, which can only happen in one way: HHHHHH. So, the probability of f(6) = 6 is 1/64.

c. Here's a bar graph showing the frequency of different outcomes for this random walk:

Number of Units (f(6))

---------------------

0 | *

1 | ***

2 |

3 |

4 |

5 |

6 | *

In the above bar graph, the asterisks (*) represent the outcomes with non-zero frequency.

d. Scott is most likely to land on f(6) = 1. This is because there are more ways to achieve f(6) = 1 compared to other outcomes. As calculated in part b, there are 6 different ways to end up at f(6) = 1, while there are only 2 ways to end up at f(6) = 0 and only 1 way to end up at f(6) = 6. Therefore, the highest probability is associated with f(6) = 1, making it the most likely outcome.

The dashed blue curve represents the normal distribution with the greater standard deviation.

The z-score of a measure X of a normally distributed variable that has mean represented by [tex]\mu[/tex] and standard deviation represented by [tex]\sigma[/tex] is obtained by the equation presented as follows:

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

Considering the format of the normal curve, we have that a flatter curve, with lower peak, will have a higher standard deviation, hence the dashed blue curve represents the normal distribution with the greater standard deviation.

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The given series is convergent.

To determine if the series [infinity] n = 1 1/(n n!) converges or diverges, we can use 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 absolutely. Mathematically, the ratio test can be written as:

lim n→∞ |a_{n+1}/aₙ| < 1

where aₙ is the nth term of the series.

In this case, the nth term of the series is aₙ = 1/(n n!). To find the ratio of consecutive terms, we can divide a_{n+1} by aₙ:

a_{n+1}/aₙ = 1/((n+1)(n+1)!) * n n!

Simplifying this expression, we get:

a_{n+1}/aₙ = 1/((n+1)!)

As n approaches infinity, the ratio a_{n+1}/aₙ approaches zero. This can be seen by simplifying the expression above, since the factorial function grows much faster than any polynomial function:

lim n→∞ a_{n+1}/aₙ = lim n→∞ 1/((n+1)!) = 0

Since the limit of the ratio of consecutive terms is less than 1, we can conclude by the ratio test that the series [infinity] n = 1 1/(n n!) converges absolutely.

Therefore, the given series is convergent.

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So, dz/dt using the Chain Rule for the given function is  - dz/dt = cos(√t)cos(9/t) * (1/(2√t)) - sin(√t)sin(9/t) * (-9/t^2)

To find dz/dt using the Chain Rule, we need to take the derivative of z with respect to x and y, and then multiply each by their respective derivative with respect to t.

Starting with the derivative of z with respect to x, we have:
dz/dx = cos(x)cos(y)

Next, we find the derivative of x with respect to t:
dx/dt = 1/(2√t)

Now, we can multiply the two derivatives together:
(dz/dt) = (dz/dx) * (dx/dt) = cos(x)cos(y) * (1/(2√t))

To find the derivative of z with respect to y, we have:
dz/dy = -sin(x)sin(y)

Then, we find the derivative of y with respect to t:
dy/dt = -9/t^2

Now, we can multiply the two derivatives together:
(dz/dt) = (dz/dy) * (dy/dt) = -sin(x)sin(y) * (-9/t^2)

Putting it all together, we have:
dz/dt = cos(x)cos(y) * (1/(2√t)) - sin(x)sin(y) * (-9/t^2)

Substituting x and y with their given expressions, we get:
dz/dt = cos(√t)cos(9/t) * (1/(2√t)) - sin(√t)sin(9/t) * (-9/t^2)

Thus,  dz/dt using the Chain Rule for the given function is  - dz/dt = cos(√t)cos(9/t) * (1/(2√t)) - sin(√t)sin(9/t) * (-9/t^2)

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To create a sphere, a cross-section would need to be revolved around the y-axis line (y = 1). Given the circle on a coordinate plane with the center at (0,0) and a radius of 2, the equation of the circle is x² + y² = 4.

This circle is perpendicular to the x-axis and the y-axis. A cross-section of this circle would be a semi-circle with its diameter as the x-axis. If this semi-circle is revolved around the y-axis, it would create a sphere of radius 2. The y-axis line (y = 1) passes through the center of the semi-circle and is perpendicular to the diameter of the semi-circle (which lies along the x-axis).

Therefore, this semi-circle needs to be revolved around the y-axis line (y = 1) to create a sphere.Hence, a cross-section would need to be revolved around the y-axis line (y = 1) to create a sphere.

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The experimental probability of landing on a 3 is 1/3.

To calculate the experimental probability of landing on a 3, we need to divide the number of times the cube landed on a 3 by the total number of trials. In this case, the cube was rolled 30 times.

The cube landed on a 3 ten times. So the experimental probability of landing on a 3 is:

Experimental probability of landing on a 3 = Number of times cube landed on a 3 / Total number of trials

= 10 / 30

= 1/3

Therefore, the experimental probability of landing on a 3 is 1/3.

The experimental probability represents the observed frequency of an event occurring in a given number of trials. In this case, out of the 30 rolls of the cube, it landed on a 3 ten times. By dividing this number by the total number of trials, we can determine the likelihood or probability of landing on a 3.

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In calculus, the derivative of a function represents its rate of change at any given point. If the derivative is positive at a point, it indicates that the function is increasing at that point.

Conversely, if the derivative is negative, the function is decreasing. Therefore, by analyzing the sign of the derivative, we can determine the intervals of increasing and decreasing for a given function.

To determine the intervals of increasing and decreasing, we need to find the critical points of the function. These are the points where the derivative is either zero or undefined. At these points, the function might change from increasing to decreasing or vice versa.

Once we have the critical points, we can create a sign chart and evaluate the sign of the derivative in different intervals. If the derivative is positive, the function is increasing, and if it is negative, the function is decreasing.

However, without the specific function or the graph of the derivative, I cannot provide a detailed analysis. To determine the intervals of increasing and decreasing for your specific case, you need to examine the graph of the derivative and identify the critical points. Then, based on the sign of the derivative in each interval, you can determine the intervals of increasing and decreasing for the original function.

If you provide the function or any additional information, I would be happy to assist you further in analyzing the intervals of increasing and decreasing.

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The surface area of the rectangular prism is 188 square units.

A rectangular prism is simply a three-dimensional solid shape which has six faces that are rectangles.

The surface area of a rectangular prism is expressed as;

Surface Area = 2lw + 2lh + 2wh

Where w is the width, h is height and l is length

From the diagram:

Length l = 7 units

Width w = 4 units

Height h = 6 units

Plug these values into the above formula and solve for the surface area.

Surface Area = 2lw + 2lh + 2wh

Surface Area = 2(7 × 4) + 2(7 × 6) + 2(4 × 6)

Simplifying the calculation:

Surface Area = 56 + 84 + 48

Surface Area = 188 square units

Therefore, the surface area equals 188 square units.

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To solve the system of equations:

4x^2 + 9y^2 = 72

x^2 - y^2 = 5

We can use the method of substitution. Let's solve the second equation for x^2:

x^2 = y^2 + 5

Now substitute x^2 in the first equation:

4(y^2 + 5) + 9y^2 = 72

4y^2 + 20 + 9y^2 = 72

13y^2 + 20 = 72

13y^2 = 52

y^2 = 4

y = ±2

Substituting y = 2 into x^2 = y^2 + 5, we get:

x^2 = 2^2 + 5

x^2 = 9

x = ±3

Therefore, the solutions to the system of equations are:

(x, y) = (-3, 2), (-3, -2), (3, 2), (3, -2)

Listing the solutions with the smallest x-values and then the smallest y-value first, we have:

(-3, -2), (-3, 2), (3, -2), (3, 2)

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a) p^^ = 0.71.,b) verified c) zc ≈ 2.576 d) The left endpoint is given by p^^  - E, and the right endpoint is given by p^^  + E. e)We are 99% confident that the true proportion of U.S. adults thinking that teenagers are the more dangerous drivers lies between the calculated left and right endpoints.

a. To construct a confidence interval, we need to determine the sample proportion, p^^ . From the graph, we can see that 71% of the 498 U.S. adults surveyed believe that teenagers are the more dangerous drivers. Therefore, p^^  = 0.71.

b. In order to approximate the sampling distribution by a normal distribution, we need to check two conditions: (1) the sample size should be sufficiently large, and (2) the sampling method should be random. Since we are given a sample size of 498 and assuming that the survey was conducted using a random sampling method, we can consider these conditions met.

c. For a 99% confidence level, we can find the critical z-value, zc, using the standard normal distribution. The z-value corresponds to the desired confidence level, so we find the z-value such that the area to the right is 0.005. Using a standard normal table or calculator, we find zc ≈ 2.576.

The margin of error (E) is calculated as E = zc * sqrt(p^^6(1-p^^ )/n), where n is the sample size. In this case, n = 498. By substituting the values, we can calculate the margin of error.

d. Using the sample proportion p^^ , the margin of error E, and the formula for the confidence interval, we can find the left and right endpoints. The left endpoint is given by p^^  - E, and the right endpoint is given by p^^  + E.

e. The confidence interval for the population proportion is interpreted as follows: We are 99% confident that the true proportion of U.S. adults who think that teenagers are the more dangerous drivers lies between the calculated left and right endpoints.

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With side lengths of 5 inches, 8 inches, and 20 inches, it is not possible to construct a triangle.

To construct a triangle, the sum of the lengths of any two sides must be greater than the length of the third side. In this case, let's check the conditions:

1. The sum of the lengths of the sides 5 inches and 8 inches is 13 inches, which is less than the length of the third side, 20 inches. So, a triangle cannot be formed using these side lengths.

2. The sum of the lengths of the sides 5 inches and 20 inches is 25 inches, which is greater than the length of the third side, 8 inches. However, the difference between these two sides is 15 inches, which is less than the length of the third side, 8 inches. So, a triangle cannot be formed using these side lengths.

3. The sum of the lengths of the sides 8 inches and 20 inches is 28 inches, which is greater than the length of the third side, 5 inches. However, the difference between these two sides is 12 inches, which is less than the length of the third side, 5 inches. So, a triangle cannot be formed using these side lengths.

Therefore, it is not possible to construct a triangle with side lengths of 5 inches, 8 inches, and 20 inches.

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The trig model or equation that represents the data is T = 65 + 10sin(2pi/12(m-1))

T is the temperature in degrees Fahrenheit, m is the month (1 = January, 2 = February, etc.)

This model was arrived at by using the following steps:

The amplitude of the sine curve is 10 degrees Fahrenheit, which represents the difference between the highest and lowest temperatures in the year. The period of the sine curve is 12 months, which represents the time it takes for the temperature to complete one cycle.

The equation of the sine curve can be used to predict the temperature for any month of the year. For example, the temperature in Atlanta in March is predicted to be 75 degrees Fahrenheit. Hence the trig model or equation that represents the data is T = 65 + 10sin(2pi/12(m-1))

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In summary, the sum-of-products expansions for the given Boolean functions are: a) F(x,y,z) = x + y + z b) F(x,y,z) = xy + yz c) F(x,y,z) = x d) F(x,y,z) = xy

a) F(x,y,z) = x + y + z
The sum-of-products expansion is obtained by finding all possible product terms and then combining them with OR operations. In this case, F(x,y,z) is already in sum-of-products form as it represents the OR operation between x, y, and z.
b) F(x,y,z) = (x + z)y
To convert this to sum-of-products form, we can apply the distributive law of Boolean algebra, which gives:
F(x,y,z) = xy + yz
Here, the function is in sum-of-products form with xy and yz as product terms combined using an OR operation.
c) F(x,y,z) = x
Since this function is dependent only on the variable x, it is already in sum-of-products form as it doesn't involve any product terms with other variables.
d) F(x,y,z) = xy
In this case, the function is also already in sum-of-products form as it represents a single product term (xy) involving two variables. There are no other terms to combine with OR operations.

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The Probability that a randomly selected pair of sneakers from the 500 pairs has nothing wrong is 49/50.

The probability that a pair of sneakers selected from the 500 pairs has nothing wrong, we need to divide the number of pairs with nothing wrong by the total number of pairs.

Given that Nike conducted a test on 500 pairs of sneakers and found nothing wrong with 490 pairs, we can calculate the probability as follows:

Probability = Number of pairs with nothing wrong / Total number of pairs

Probability = 490 / 500

Simplifying the fraction:

Probability = 49/50

Therefore, the probability that a randomly selected pair of sneakers from the 500 pairs has nothing wrong is 49/50.

The fraction 49/50 represents the ratio of the favorable outcome (pairs with nothing wrong) to the total possible outcomes (all pairs of sneakers). In this case, since 490 out of 500 pairs have nothing wrong, the probability of selecting a pair with nothing wrong is high, given by 49/50.

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To find an explicit formula for the sequence given by the recurrence relation dk = 8dk−1 − 16dk−2 with initial conditions d1 = 0 and d2 = 1, we can use the method of characteristic equations.

The characteristic equation for the recurrence relation is r^2 - 8r + 16 = 0. Factoring this equation, we get (r-4)^2 = 0, which means that the roots are both equal to 4.
Therefore, the general solution for the recurrence relation is of the form dk = c1(4)^k + c2k(4)^k, where c1 and c2 are constants that can be determined from the initial conditions.
Using d1 = 0 and d2 = 1, we can solve for c1 and c2. Substituting k = 1, we get 0 = c1(4)^1 + c2(4)^1, and substituting k = 2, we get 1 = c1(4)^2 + c2(2)(4)^2. Solving this system of equations, we find that c1 = 1/16 and c2 = -1/32.
Therefore, the explicit formula for the sequence is dk = (1/16)(4)^k - (1/32)k(4)^k.

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The energy of the red light emitted by a neon atom with a wavelength of 703.2 nm is approximately 2.82 x 10⁻¹⁹ joules.

To calculate the energy of this light, we need to use the formula:

Energy = Planck's constant x speed of light / wavelength

Planck's constant (h) is a fundamental constant of nature, and its value is 6.626 x 10⁻³⁴ joule-seconds.

The speed of light (c) is another fundamental constant, and its value is approximately 3.00 x 10⁸ meters per second.

We can plug in the values we know and solve for energy:

Energy = 6.626 x 10⁻³⁴ J s x 3.00 x 10⁸ m/s / 703.2 x 10⁻⁹ m

Energy = 19.878 x 10⁻²⁶ J m / 703.2 x 10⁻⁹ m

Energy = 2.82 x 10⁻¹⁹ J

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To prove the question that the set of vectors b = {(1, 1, 1), (1, 1, 0), (1, 0, 0)} is linearly independent and spans R3, we need to show two things:

1. Linear independence: We need to show that no vector in b can be written as a linear combination of the other two vectors. We can do this by setting up the following equation:

a(1, 1, 1) + b(1, 1, 0) + c(1, 0, 0) = (0, 0, 0)

where a, b, and c are constants. We can write this equation as a system of linear equations:

a + b + c = 0
a + b = 0
a = 0

Solving this system of equations, we get a = b = c = 0, which means that the only linear combination that gives us the zero vector is the trivial one. Therefore, the set of vectors b is linearly independent.

2. Spanning R3: We need to show that any vector in R3 can be written as a linear combination of the vectors in b. Let (x, y, z) be an arbitrary vector in R3. We need to find constants a, b, and c such that:

a(1, 1, 1) + b(1, 1, 0) + c(1, 0, 0) = (x, y, z)

We can write this equation as a system of linear equations:

a + b + c = x
a + b = y
a = z

Solving this system of equations, we get:

a = z
b = y - z
c = x - y

Therefore, any vector (x, y, z) in R3 can be written as a linear combination of the vectors in b. Hence, the set of vectors b spans R3.

The matrix [(1 1 1) (1 1 0) ( 1 0 0)] row reduces to:

[1 1 1 | 0]
[0 1 -1 | 0]
[0 0 -1 | 0]

We can further simplify this matrix by subtracting the second row from the first:

[1 0 2 | 0]
[0 1 -1 | 0]
[0 0 -1 | 0]

Finally, we can divide the third row by -1 to get:

[1 0 2 | 0]
[0 1 -1 | 0]
[0 0 1 | 0]

This is the row reduced echelon form of the matrix.

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The expression representing the situation is B = 3M + d, where B represents the number of baseball cards Bobby has, M represents the number of baseball cards Michael has, and d represents the additional amount that Bobby has compared to three times the number of cards Michael has.

Step 1: Assign variables.

Let's assign the variable "B" to represent the number of baseball cards Bobby has and the variable "M" to represent the number of baseball cards Michael has.

Step 2: Understand the relationship.

According to the given information, Bobby has "d" more than 3 times the number of baseball cards as Michael. This means that Bobby's number of baseball cards can be calculated by taking 3 times the number of cards Michael has and adding "d" to it.

Step 3: Create the expression.

To represent the situation, we can write the expression as: B = 3M + d.

Step 4: Interpret the expression.

In this expression, "3M" represents 3 times the number of baseball cards Michael has, and "d" represents the additional amount that Bobby has compared to that.

Therefore, the expression B = 3M + d represents the situation where Bobby has "d" more than 3 times the number of baseball cards as Michael. This expression allows us to calculate Bobby's number of cards based on the given relationship between their card counts.

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To construct a 99% confidence interval for the mean difference of the before minus after weights, we can use the following steps:

State the null hypothesis and alternative hypothesis. The null hypothesis is that the mean difference is zero, while the alternative hypothesis is that the mean difference is not zero.

Find the standard error of the difference of the means, denoted by s. The formula for the standard error of the difference of the means is:

s = √[(sd1)^2 + (sd2)^2]

where sd1 and sd2 are the standard deviations of the before and after weights, respectively.

Use the t-distribution to find the critical value for a 99% confidence level. The critical value is ±2.084 for a two-tailed test with a sample size of 20.

Substitute the values into the formula for the confidence interval:

Md ± z*(s / sqrt(n))

where Md is the mean difference, z is the critical value, and n is the sample size.

For a sample size of 20, the formula becomes:

Md ± ±2.084 * (√[(sd1)^2 + (sd2)^2] / sqrt(20))

Plugging in the values for sd1 and sd2, we get:

Md ± ±2.084 * (√(25^2 + 10^2) / sqrt(20))

Md ± ±2.084 * (125 / sqrt(20))

Md ± 4.168 / sqrt(20)

Therefore, the 99% confidence interval for the mean difference of the before minus after weights is (−3.992, 8.161).

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Answer: Dimensions are 105m by 68m

Step-by-step explanation:

7140=(4x+5)(3x-7)

7140=12x^2-35-13x

7175=12x^2-13x

0=12x^2-13x-7175

x=25

The planning value for the population standard deviation is estimated to be $3,350, and sample sizes of approximately 46, 566, and 2,262 would be needed to achieve desired margins of error of $500, $200, and $100, respectively.

(a) Desired margin of error = $500

The formula for the sample size required to estimate the population mean with a desired margin of error is:

n = (Z * σ / E)²

Where:

n = sample size

Z = Z-score corresponding to the desired confidence level (95% confidence level corresponds to a Z-score of 1.96)

σ = population standard deviation

E = desired margin of error

Since we don't have the actual population standard deviation, we can estimate it using the planning value.

Range of expected salaries = $55,400 - $42,000 = $13,400

Planning value for standard deviation = Range / 4 = $13,400 / 4 = $3,350

Substituting the values into the formula:

n = (1.96 * $3,350 / $500)² ≈ 45.96

Since we can't have a fraction of a sample, we need to round up to the nearest whole number.

Therefore, the sample size needed for a desired margin of error of $500 is 46.

(b) Desired margin of error = $200

Using the same formula:

n = (1.96 * $3,350 / $200)² ≈ 565.44

Rounding up to the nearest whole number, the sample size needed for a desired margin of error of $200 is 566.

(c) Desired margin of error = $100

Using the same formula:

n = (1.96 * $3,350 / $100)² ≈ 2,261.76

Rounding up to the nearest whole number, the sample size needed for a desired margin of error of $100 is 2,262.

(d) Would you recommend trying to obtain the $100 margin of error? Explain.

Obtaining a margin of error as low as $100 would require a sample size of 2,262. While this larger sample size may provide a more precise estimate, it also increases the cost and time required for data collection and analysis. Therefore, the decision to obtain such a small margin of error should be based on the practicality and resources available. It is important to consider the trade-off between the desired level of precision and the associated costs and efforts.

Therefore, the planning value for the population standard deviation is estimated to be $3,350, and sample sizes of approximately 46, 566, and 2,262 would be needed to achieve desired margins of error of $500, $200, and $100, respectively.

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Answer: 0

Step-by-step explanation:

16w+11 = -3w + 11

19w + 11 = 11

19w = 0

w = 0