A candy bar cost 95 cents. How much will it cost to buy 4 candy bars

Answer:

To find the equation of the tangent line to the curve y = x^2 Arccos(3x) at x = 0.2, we need to find the slope of the tangent line at that point and then use the point-slope form of the equation of a line.

First, we find the derivative of y with respect to x:

dy/dx = 2x Arccos(3x) - x^2 / sqrt(1 - (3x)^2)

Next, we evaluate the derivative at x = 0.2 to find the slope of the tangent line at that point:

dy/dx | x=0.2 = 2(0.2) Arccos(3(0.2)) - (0.2)^2 / sqrt(1 - (3(0.2))^2)

dy/dx | x=0.2 = 0.6865

So the slope of the tangent line at x = 0.2 is approximately 0.6865.

Now we can use the point-slope form of the equation of a line to find the equation of the tangent line. We know that the line passes through the point (0.2, 0.04 Arccos(0.6)), so we have:

y - y1 = m(x - x1)

y - 0.04 Arccos(0.6) = 0.6865(x - 0.2)

Simplifying and rearranging, we get:

y = 0.6865x - 0.1261

Therefore, the equation of the tangent line to the curve y = x^2 Arccos(3x) at x = 0.2 is y = 0.6865x - 0.1261.

The equation of the tangent line to the curve y = x^2 Arccos(3x) at x = 0.2 is approximately y = 0.653x - 0.113.

To find the equation of the tangent line to the curve at x = 0.2, we need to find the slope of the tangent line at that point, and then use the point-slope form of a line to write the equation.

First, we need to find the derivative of the curve:

y = x^2 Arccos(3x)

Taking the derivative with respect to x:

y' = 2x Arccos(3x) - x^2 (1/sqrt(1 - 9x^2))

Now, we can evaluate y' at x = 0.2 to find the slope of the tangent line at that point:

y'(0.2) = 2(0.2) Arccos(3(0.2)) - (0.2)^2 (1/sqrt(1 - 9(0.2)^2))

≈ 0.653

So the slope of the tangent line at x = 0.2 is approximately 0.653.

Next, we need to find the y-coordinate of the point on the curve where x = 0.2:

y = (0.2)^2 Arccos(3(0.2))

≈ 0.012

So the point on the curve where x = 0.2 is (0.2, 0.012).

Now we can use the point-slope form of a line to write the equation of the tangent line:

y - y1 = m(x - x1)

where m is the slope we just found, and (x1, y1) is the point on the curve where x = 0.2.

Substituting in the values we found:

y - 0.012 = 0.653(x - 0.2)

Simplifying:

y = 0.653x - 0.113

So the equation of the tangent line to the curve y = x^2 Arccos(3x) at x = 0.2 is approximately y = 0.653x - 0.113.

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a.  The probability that exactly 3 U.S. adults out of 12 favor the use of unmanned drones by police agencies is 0.218.

b. The probability that at least 4 U.S. adults out of 12 favor the use of unmanned drones by police agencies is 0.684.

c. The probability that less than 8 U.S. adults out of 12 favor the use of unmanned drones by police agencies is 0.968.

This problem requires the use of the binomial distribution, where we have:

n = 12 (number of trials, or U.S. adults randomly selected)

p = 0.21 (probability of success, or favoring the use of unmanned drones by police agencies)

(a) To find P(x=3), the probability that exactly 3 U.S. adults out of 12 favor the use of unmanned drones by police agencies, we can use the binomial probability formula:

P(x=3) = (12 choose 3) * 0.21^3 * (1-0.21)^(12-3)

P(x=3) = 0.218

(b) To find P(x≥4), the probability that at least 4 U.S. adults out of 12 favor the use of unmanned drones by police agencies, we can use the complement rule and the binomial cumulative distribution function:

P(x≥4) = 1 - P(x<4)

P(x≥4) = 1 - P(x=0) - P(x=1) - P(x=2) - P(x=3)

P(x≥4) = 1 - (12 choose 0) * 0.21^0 * (1-0.21)^(12-0) - (12 choose 1) * 0.21^1 * (1-0.21)^(12-1) - (12 choose 2) * 0.21^2 * (1-0.21)^(12-2) - P(x=3)

P(x≥4) = 0.684

(c) To find P(x<8), the probability that less than 8 U.S. adults out of 12 favor the use of unmanned drones by police agencies, we can use the binomial cumulative distribution function:

P(x<8) = P(x≤7)

P(x<8) = P(x=0) + P(x=1) + P(x=2) + ... + P(x=7)

P(x<8) = (12 choose 0) * 0.21^0 * (1-0.21)^(12-0) + (12 choose 1) * 0.21^1 * (1-0.21)^(12-1) + (12 choose 2) * 0.21^2 * (1-0.21)^(12-2) + ... + (12 choose 7) * 0.21^7 * (1-0.21)^(12-7)

P(x<8) = 0.968

So the probability that less than 8 U.S. adults out of 12 favor the use of unmanned drones by police agencies is 0.968.

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The given absolute value function is f(x) = |x - 3x|.

To evaluate absolute value function f(-2), we substitute -2 in place of x:

f(-2) = |-2 - 3(-2)|

= |-2 + 6|

= |4|

= 4

Therefore, f(-2) = 4.

To evaluate f(0), we substitute 0 in place of x:

f(0) = |0 - 3(0)|

= |0|

= 0

Therefore, f(0) = 0.

To evaluate f(2), we substitute 2 in place of x:

f(2) = |2 - 3(2)|

= |-4|

= 4

Therefore, f(2) = 4.

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The transition probability matrix is:

[tex]\left[\begin{array}{cccc}0.5&0.1&0.2&0.2\\0.75&0&0.6 &0.3\\0.1&0.5&0 &0.1\\0.05&0.1&0.25&0\end{array}\right][/tex]

What is matrix?

A matrix is a rectangular array of numbers or other mathematical objects for which operations such as addition, subtraction, multiplication, and scalar multiplication are defined.

The Markov chain for housing movements can be formulated as follows:

State 1: Apartment

State 2: Condominium

State 3: Own House

State 4: Rented House

The transition probability matrix P is given by:

[tex]\left[\begin{array}{cccc}P_{11}&P_{12}&P_{13} &P_{14}\\P_{21}&P_{22}&P_{23} &P_{24}\\P_{31}&P_{32}&P_{33} &P_{34}\\P_{41}&P_{42}&P_{43} &P_{44}\end{array}\right][/tex]

where [tex]$P_{ij}$[/tex] is the probability of moving from state i to state j. To calculate these probabilities, we need to use the data from the survey.

For example, [tex]$P_{12}$[/tex] is the probability of moving from an apartment to a condominium. From the survey data, we can see that out of 200 apartment dwellers, 100 moved to another apartment, 20 moved to a condominium, 40 moved to their own house, and 40 moved to a rented house. Therefore, [tex]$P_{12} = 20/200 = 0.1$[/tex].

Similarly, we can calculate the other transition probabilities:

[tex]P_{13} = 40/200 = 0.2$\\$P_{14} = 40/200 = 0.2$\\$P_{21} = 150/200 = 0.75$\\$P_{23} = 120/200 = 0.6$\\$P_{24} = 60/200 = 0.3$\\$P_{31} = 20/200 = 0.1$\\$P_{32} = 100/200 = 0.5$\\$P_{34} = 20/200 = 0.1$\\$P_{41} = 10/200 = 0.05$\\$P_{42} = 20/200 = 0.1$\\$P_{43} = 50/200 = 0.25$[/tex]

Therefore, the transition probability matrix is:

[tex]\left[\begin{array}{cccc}0.5&0.1&0.2&0.2\\0.75&0&0.6 &0.3\\0.1&0.5&0 &0.1\\0.05&0.1&0.25&0\end{array}\right][/tex]

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True, the outer loop in each of the three sorting algorithms (e.g., Bubble Sort, Selection Sort, Insertion Sort) is responsible for ensuring the number of passes required are completed. It iterates through the entire list to make sure the sorting process is executed correctly.

An algorithm is a standard formula or set of instructions that has a finite number of steps or instructions for using a computer to solve a problem.

The time complexity is a measurement of how long an algorithm takes to run until it completes the task in relation to the size of the input.

Flowcharts can be used to illustrate algorithms, an algorithm for a process or workflow can be graphically represented in a flowchart.

Therefore, an algorithm is a collection of guidelines for resolving a dilemma or carrying out a task.

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When a person walking [tex] \frac{1}{5}[/tex] mile in [tex] \frac{1}{15}[/tex] hour, then the speed ( distance travelled per unit time) of person is equals to the 3 miles per hour.

The speed is defined as the rate at which a particular object covers a certain amount of distance. This speed can be fast or slow. That is simply defined as the rate of change in distance per unit of time. It is defined as Speed=[tex]\frac{d}{t }[/tex]

We have a person who is walks along the road. The distance travelled by person =

[tex] \frac{1}{5}[/tex] mile

Time taken by him to travel the distance 1/5 mile [tex]= \frac{ 1}{15}[/tex] hours.

We have to determine the persons speed per hour. Using the speed formula, now the speed of person, [tex]s = \frac{ \frac{ 1}{5} }{\frac{1}{15} }[/tex]

= 3 miles/hour

Hence, required value of speed is 3 miles per hour.

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The standard deviation of the population is 8.

We have,

The mean of the sampling distribution is the mean of the population, so we have:

[tex]$\bar{x} = \frac{1}{n}\sum_{i=1}^{n}x_i = \mu$[/tex]

where [tex]$\bar{x}$[/tex] is the sample mean, n is the sample size, [tex]x_1[/tex] are the individual samples, and [tex]$\mu$[/tex] is the population mean.

In this case,

We are given the sample size n = 100 and the sample mean [tex]\bar{x}[/tex]

We also know that the sampling distribution comes from a normally distributed population.

The standard error of the mean.

[tex]$SE = \frac{s}{\sqrt{n}}$[/tex]

where s is the sample standard deviation.

The standard error of the mean represents the standard deviation of the sampling distribution.

In this case,

We don't have the sample standard deviation s, but we can estimate it using the sample variance:

[tex]$s^2 = \frac{1}{n-1}\sum_{i=1}^{n}(x_i - \bar{x})^2$[/tex]

Substituting the values we have:

[tex]$s^2 = \frac{1}{99}\sum_{i=1}^{100}(x_i - 145)^2 = 64$[/tex]

Therefore:

[tex]$s = \sqrt{64} = 8$[/tex]

Substituting this value into the standard error equation:

[tex]$SE = \frac{s}{\sqrt{n}} = \frac{8}{\sqrt{100}} = 0.8$[/tex]

The standard deviation of the population is related to the standard error by the following equation:

[tex]$SE = \frac{\sigma}{\sqrt{n}}$[/tex]

Rearranging this equation, we get:

[tex]$\sigma = SE \times \sqrt{n} = 0.8 \times \sqrt{100} = 8$[/tex]

Therefore,

The standard deviation of the population is 8.

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The standardized residuals are -0.11, 0.75, -0.38, 2.08, and 2.16, respectively.

(a) The estimated regression equation can be found by first calculating the sample means and sample standard deviations for both x and y, as well as the sample correlation coefficient, and then using these values to calculate the slope and intercept of the regression line:

x = (6 + 11 + 15 + 18 + 20)/5 = 14

y = (7 + 7 + 13 + 21 + 30)/5 = 15.6

sx = sqrt(((6-14)^2 + (11-14)^2 + (15-14)^2 + (18-14)^2 + (20-14)^2)/4) = 4.49

sy = sqrt(((7-15.6)^2 + (7-15.6)^2 + (13-15.6)^2 + (21-15.6)^2 + (30-15.6)^2)/4) = 8.25

r = ((6-14)(7-15.6) + (11-14)(7-15.6) + (15-14)(13-15.6) + (18-14)(21-15.6) + (20-14)(30-15.6))/4sxsy

= 0.962

b = r(sy/sx) = 1.71

a = y - b(x) = -9.23

Therefore, the estimated regression equation is y = -9.23 + 1.71x.

(b) The residuals can be found by subtracting the predicted values of y (based on the regression line) from the actual values of y:

xi

yi

y

Residuals

6

7

0.09

-0.09

11

7

6.38

0.62

15

13

13.31

-0.31

18

21

19.29

1.71

20

30

23.57

6.43

(c) The standardized residuals can be found by dividing each residual by its estimated standard deviation:

xi

yi

ŷ

Residuals

Standardized Residuals

6

7

0.09

-0.09

-0.11

11

7

6.38

0.62

0.75

15

13

13.31

-0.31

-0.38

18

21

19.29

1.71

2.08

20

30

23.57

6.43

2.16

The estimated standard deviation of the residuals can be found by calculating the root mean squared error (RMSE):

RMSE = sqrt(((-0.09)^2 + (0.62)^2 + (-0.31)^2 + (1.71)^2 + (6.43)^2)/4) = 3.04

Therefore, the standardized residuals are -0.11, 0.75, -0.38, 2.08, and 2.16, respectively.

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The probability of winning first prize is 1 in 324,632 and winning the second prize is 1 in 52,360.

(a) The probability of winning the first prize in Cash 5 is the probability of correctly choosing all 5 numbers out of the 35 possible numbers. This can be calculated using the formula for combinations, which is

[tex]^{n} C_{r}[/tex]  = n! / r!(n-r)! where n is the total number of items and r is the number of items to be chosen.

For Cash 5, the formula is:

[tex]^{35} C_{5}[/tex] = 35!÷5!(35-5)! = 324,632
So, the probability of winning first prize is 1 in 324,632.

(b) The probability of winning the second prize in Cash 5 is the probability of correctly choosing 4 out of the 5 numbers and not choosing the fifth number (which would be the Cash Ball).

This can be calculated using the formula for combinations again, but this time with n = 35 (the total number of numbers) and r = 4 (the number of numbers to be chosen). Then, the probability of not choosing the Cash Ball is 30/34 (since there are 30 numbers left after the Cash Ball is chosen out of the remaining 34 numbers).

So the formula is:

[tex]^{35} C_{5} (\frac{30}{34}) = 52,360[/tex]

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The two cases weigh 102,100 decigrams together.

First, we need to convert dekagrams to decigrams, since the question asks for the weight in decigrams.

1 dekagram = 10 grams

1 gram = 10 decigrams

Therefore, 1 dekagram = 100 decigrams

Now, let's calculate the weight of the two cases in decigrams:

Weight of tomato cans case = 563 dekagrams x 100 decigrams/dekagram = 56,300 decigrams

Weight of soup cans case = 458 dekagrams x 100 decigrams/dekagram = 45,800 decigrams

The weight of the two cases together is the sum of the two weights:

Total weight = 56,300 decigrams + 45,800 decigrams = 102,100 decigrams

Therefore, the two cases together weigh 102,100 decigrams.

To solve this problem, we need to first convert the weight of the two cases from dekagrams to decigrams so we can add them together.

1 dekagram = 10 grams

1 gram = 10 decigrams

So,

563 dekagrams = 5630 grams

5630 grams = 56300 decigrams

and

458 dekagrams = 4580 grams

4580 grams = 45800 decigrams

Now we can add the weights of the two cases in decigrams:

56300 decigrams + 45800 decigrams = 102,100 decigrams

Therefore, the two cases weigh 102,100 decigrams together.

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The Pythagorean Theorem is a fundamental concept that relates to the sides of a right-angled triangle, and it can also be used to understand the relationship between the areas of the squares constructed on the sides of the triangle.

The area of a square is given by the formula A = s², where s is the length of one of its sides. Therefore, the areas of the three squares are:

Area of the square with side a = a²

Area of the square with side b = b²

Area of the square with side c = c²

Now, let's compare the areas of the squares. We can start by subtracting the area of the square with side a from the area of the square with side c:

c² - a²

Using the Pythagorean Theorem, we know that c² = a² + b². Substituting this into the above expression, we get:

c² - a² = (a² + b²) - a² = b²

This tells us that the difference between the area of the square with side c and the area of the square with side a is equal to the area of the square with side b. In other words:

c² - a² = b²

This is known as the Pythagorean identity. It states that in any right-angled triangle, the square of the hypotenuse is equal to the sum of the squares of the other two sides. We can also rearrange this identity to obtain the following:

c² = a² + b²

This is the Pythagorean Theorem that we are familiar with. Therefore, we can conclude that the relationship between the areas of the squares constructed on the sides of a right-angled triangle is given by the Pythagorean identity: the difference between the area of the square on the hypotenuse and the area of the square on the shorter side is equal to the area of the square on the other shorter side.

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a) Counter-example: x=1

When x=1, 7x^3=7 and x^4=1, which means 7x^3>x^4 is not true for all positive integers.

b) Counter-example: x=-2 and y=-3

When x=-2 and y=-3, x^2=4 and y^2=9, which means x^2<y^2, then x^2>y^2 is not true for all real numbers.

c) Counter-example: n=0

When n=0, n^2=0 and n=0, which means n^2=n. Therefore, the statement "If n is an integer, then n^2≠n" is not true for all integers.

a) The conjecture states that if x is a positive integer, then 7x^3>x^4. To find a counter-example, we need to find a value of x that is a positive integer for which this statement is false. Let's try x=1. Substituting this value in the conjecture, we get 7x^3=7 and x^4=1. Therefore, 7x^3>x^4 becomes 7>1, which is false. Thus, we have found a counter-example, and the conjecture is false.

b) The conjecture states that if x and y are real numbers and x>y, then x^2>y^2. To find a counter-example, we need to find two real numbers x and y such that x>y but x^2<y^2. Let's try x=-2 and y=-3. Substituting these values in the conjecture, we get x^2=4 and y^2=9. Therefore, x^2<y^2 becomes 4<9, which is true. But x^2>y^2 becomes 4>9, which is false. Thus, we have found a counter-example, and the conjecture is false.

c) The conjecture states that if n is an integer, then n^2≠n. To find a counter-example, we need to find an integer n for which n^2=n. Let's try n=0. Substituting this value in the conjecture, we get n^2=0 and n=0. Therefore, n^2=n becomes 0=0, which is true. Thus, we have found a counter-example, and the conjecture is false.

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The max-flow min-cut theorem helps to demonstrate that the maximum number of independent 1's in the matrix H equals the minimum number of lines in a cover.

To show that the maximum number of independent 1's in a 0-1 matrix H with $n_{1}$ rows and $n_{2}$ columns equals the minimum number of lines in a cover, we can use the max-flow min-cut theorem on an appropriately defined network.

First, create a bipartite graph G, where one set of vertices represents the rows and the other set represents the columns of the matrix H. Connect an edge between a row vertex and a column vertex if there is a 1 in the corresponding entry of the matrix H.

Next, add a source vertex s connected to all row vertices and a sink vertex t connected to all column vertices. Assign capacities of 1 to all edges in the network.

Now, apply the max-flow min-cut theorem on this network. The maximum flow in the network represents the maximum number of independent 1's in the matrix H. The minimum cut corresponds to the minimum number of lines in a cover of H, as it separates the source and sink while minimizing the number of crossing edges.

Hence, the max-flow min-cut theorem helps to demonstrate that the maximum number of independent 1's in the matrix H equals the minimum number of lines in a cover.

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We can say with 95% confidence that the true population mean of the growing season is between 176.3 and 212.9 days.

We can use a t-distribution since the population standard deviation is unknown and the sample size is small (n < 30).

The formula for a confidence interval with a t-distribution is:

CI = x ± tα/2 * (s/√n)

Where:

x = sample mean

s = sample standard deviation

n = sample size

tα/2 = t-value with degrees of freedom (df = n-1) and α/2 level of significance

Using the given information, we have:

x = 194.6

s = 55.6

n = 32

df = n-1 = 31

α/2 = 0.05/2 = 0.025 (since it's a 95% confidence interval)

We can find the t-value using a t-distribution table or a calculator. For df = 31 and α/2 = 0.025, we get:

tα/2 = 2.0395

Substituting the values into the formula, we get:

CI = 194.6 ± 2.0395 * (55.6/√32)

CI = (176.3, 212.9)

Therefore, we can say with 95% confidence that the true population mean of the growing season is between 176.3 and 212.9 days.

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Answer:

14. C6H12O6 + 6O2 -> 6CO2 + 6H2O

Yes, a special form of a combustion reaction called respiration.

15. Cu(s) + AgNO3(aq) => Ag(s) + CuNO3(aq)

Step-by-step explanation:

Are you asking for equations?

Answer:

BOTH OF THEM ARE TRUE

14:(C6H12O6) burns in oxygen to produce carbon dioxide and water vapor as described in the following equation: C6H12O6 + 6O2 → 6H2O + 6CO2.

15:silver crystal form on the surface of the copper. Additionally, highly soluble copper (I) nitrate is generated.

The mean of this distribution is (a+b)/2 = $500, and the standard deviation is (b-a)/sqrt(12) = $288.68. The probability of winning more than $600 on one spin of the wheel is the area under the uniform distribution curve from $600 to $1000, which is (1000-600)/(1000-0) = 0.4 or 40%.

In a uniform distribution, all possible outcomes have an equal probability of occurring, and the range of values is defined by the minimum value (a) and the maximum value (b). In this case, the range is from $0 to $1000, so a=0 and b=1000.

The mean of a uniform distribution is the average of the minimum and maximum values, which is (a+ b)/2 = $500. The standard deviation of a uniform distribution is calculated using the formula (b-a)/sqrt(12), which gives a value of $288.68 for this distribution.

To find the probability of winning more than $600, we need to calculate the area under the uniform distribution curve from $600 to $1000. Since the total area under the curve is 1, we can calculate the probability by dividing the width of the interval by the total width of the distribution, which is (1000-600)/(1000-0) = 0.4 or 40%.

Therefore, the probability of winning more than $600 on one spin of the wheel is 0.4.

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The rule for the translation by the vector (0,5), plus a reflection around the line y = 5 is given as follows:

(x, y) -> (x, |y - 5| + 5).

The general coordinates of the point in a coordinate plane is given as follows:

(x,y).

The rule for the translation by the vector (0,5) is obtained as follows:

(x, y) -> (x + 0, y + 5) -> (x, y + 5).

For the reflection about the line y = 5, the x-coordinate remains constant, while the y-coordinate is moved on the opposite direction to y = 5, as follows:

(x, y) -> (x, |y - 5| + 5).

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The printer that has a better rate of cost per page would be = printer B.

For printer A:

The number of pages printed = 100

The cost for the printed pages = $26.99

Cost per page = 26.99/100 = $0.27/page

For printer B:

The number of pages printed = 275

The cost for the printed pages = $67.99

Cost per page =67.99/275

= 0.25

Therefore the printer that has a better rate of cost per page would be = printer B

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The z-score of the norminal distribution is 10.14.

Z-score is a statistical measurement that describes a value's relationship to the mean of a group of values.

To calculate the z-score of the norminal distribution, we use the formula below

Formula:

Where:

From the question,

Given:

Substitute these values into equation 1

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Answer:

The cost before rebates is: $69.95 + $49.95 = $119.90

The total rebate amount is: $20 + $30 = $50

The cost of two envelopes is: 2 x $0.20 = $0.40

The cost of two stamps is: 2 x $0.394 = $0.788

The total cost after rebates and including expenses is: $119.90 - $50 + $0.40 + $0.788 = $70.078

Rounding to two decimal places, the total cost after rebates and including expenses is $70.08

The actual rebate after expenses is: $50 - $0.40 - $0.788 = $48.812

Rounding to two decimal places, the actual rebate after expenses is $48.81

The graph of the function g(x) = −|x + 3| − 2 is added as an attachment

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

g(x) = −|x + 3| − 2

The above expression is an absolute value function that hs the following properties

Next, we plot the graph

See attachment for the graph of the function

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The number is -4. We can solve for it using algebraic equations and multiplication.

The problem states that when we multiply our number by four and add twenty, we get 4. We can represent this relationship using an algebraic equation with the variable x representing our unknown number:

4x + 20 = 4

To solve for x, we need to isolate it on one side of the equation. We start by subtracting 20 from both sides of the equation:

4x = -16

Now, we divide both sides by 4:

x = -4

Therefore, our number is -4. We can check this answer by plugging it back into the original equation:

Simplifying the left side of the equation, we get:

-16 + 20 = 4

4 = 4

This confirms that our answer, x = -4, is correct.

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Based on the given premises, we know that either the butler, maid, or cook committed the crime. If it was the cook, poison was used, and if poison was used, it wasn't done swiftly, but we know that the crime was swift. Therefore, we can conclude that the cook is not the culprit. This leaves us with the butler and the maid. However, there is no information given about the maid that would implicate her in the crime.

On the other hand, the butler is the only suspect left who has not been ruled out by the given premises. Therefore, we can conclude that the butler did it. However, to prove his guilt, we need more information or evidence. The given premises only allow us to eliminate the other suspects and narrow down the list of possible culprits to one.

In order to prove the butler's guilt, we would need additional information or evidence that directly implicates him in the crime. This could come in the form of eyewitness testimony, forensic evidence, or a confession. Without further information, we cannot definitively prove that the butler is guilty.
To prove that the butler is guilty, we can use the given statements and logical reasoning. Here is a step-by-step explanation for the sequent:

1. Either it was the butler or the maid, or it was the cook. [(BvM)vC]
2. If the cook did it, poison was used. [(CvM)-->P]
3. If it was done with poison then it wasn't done swiftly, but it was swift. [(P--> ~S)&S]

From statement 3, we know that it was done swiftly (S), so it can't be poison (~P):
4. ~P (from 3)

Now, since it wasn't poison, it means the cook couldn't have done it (~C):
5. ~C (from 2 and 4, using Modus Tollens)

We're left with either the butler or the maid:
6. BvM (from 1 and 5, using Disjunction Elimination)

Since we know it was done swiftly, and the only available options are the butler and the maid, we can conclude:
7. B (Butler)

So, we must conclude that the butler did it. The butler is guilty based on the given sequent and logical reasoning.

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Here, we can say with 95% confidence that the annual profit for the new restaurant in Kamloops with the given characteristics will fall between $1,065,200 and $1,264,800.

Based on the given characteristics of the new restaurant in Kamloops, we can estimate the annual profit by subtracting the total costs from the total revenue generated by the restaurant.
Total revenue = 15,000 covers x $100 per cover = $1,500,000
Total costs = $150k food cost + $85k overhead costs + $100k lab = $335,000
Annual profit = Total revenue - Total costs = $1,500,000 - $335,000 = $1,165,000
To compute the 95% prediction interval for annual profit, we need to consider the variability in the data and assume that the annual profit follows a normal distribution. Assuming a standard deviation of $50,000, the 95% prediction interval can be calculated as follows:  95% prediction interval = $1,165,000 +/- (1.96 x $50,000) = $1,065,200 to $1,264,800
Therefore, we can say with 95% confidence that the annual profit for the new restaurant in Kamloops with the given characteristics will fall between $1,065,200 and $1,264,800.

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A graph that represents the inequality y < x² + 4x include the following: A. graph A.

In Mathematics and Geometry, the graph of a quadratic function would always form a parabolic curve because it is a u-shaped. Based on the first graph of a quadratic function, we can logically deduce that the graph is an upward parabola because the coefficient of x² is positive and the value of "a" is greater than zero (0).

Since the leading coefficient (value of a) in the given quadratic function y < x² + 4x is positive 1, we can logically deduce that the parabola would open upward and the solution would be below the line because of the less than inequality symbol. Also, the value of the quadratic function f(x) would be minimum at -4.

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To find the volume of Tammy's storage shed, which is in the shape of a rectangular prism, we need to use the formula: Volume = Length × Width × Height.

Given the dimensions of the rectangular prism storage shed are:
Length = 10 feet
Width = 9 feet
Height = 9 feet

We can calculate the volume as follows:

Step 1: Multiply the length, width, and height.
Volume = 10 × 9 × 9

Step 2: Perform the multiplication.
Volume = 810 cubic feet

So, Tammy's storage shed has a volume of 810 cubic feet.

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