A data has 24 subgroups. 5 measurements were made per one subgroup. The sum of the subgroup averages is 160.25. The sum of the subgroup ranges is 2.19.
(1) Determine Trial central lines / Trial control limits on X bar chart and R chart.
In case of X bar chart, two values were out-of-control points and had assignable causes ( subgroup 4 - X bar value 6.65, subgroup 20 - X bar value 6.51)
In case of R bar chart, one value is out-of-control point and not part of natural variation. (subgroup 18 - R value 0.30)
(2) Determine Revised central lines / Revised control limits on X bar chart and R chart.
(Please show your calculation process logically )

The measure of angle KJL is determined as 58 ⁰.

The value of angle KML is 116 ⁰.

The measure of angle subtended by the KJL is calculated by applying the following formula.

Based on the angle of intersecting chord theorem, we will have the following equation.

m∠KJL = ¹/₂(KL )

m∠KJL  = ¹/₂ x 116

m∠KJL  = 58⁰

The value of angle KML is calculated as;

m∠KML = 2 m∠KJL (angle at center twice angle at circumference)

m∠KML = 116⁰

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The smallest value of n that satisfies this inequality is n = 11. Therefore, we need at least 11 terms to obtain an approximation of the series IM8 12ke 0.49k2 accurate to 10-6.

To find the smallest number of terms needed to obtain an approximation of the series IM8 12ke 0.49k2 accurate to 10-6, we need to use the formula for the partial sum of a series. The partial sum of the given series up to n terms is:

S(n) = IM8 + 12e + 0.49(2^2) + 0.49(3^2) + ... + 0.49(n^2)

We want to find the smallest value of n such that the error between S(n) and the true value of the series is less than 10^-6. The error between S(n) and the true value of the series can be approximated by the absolute value of the next term in the series:

|an+1| = 0.49((n+1)^2)

So we need to find the smallest value of n such that:

|an+1| < 10^-6

0.49((n+1)^2) < 10^-6

(n+1)^2 < (10^-6)/0.49

n+1 < sqrt((10^-6)/0.49)

n < sqrt((10^-6)/0.49) - 1

n < 11.75

Since n must be a whole number, the smallest value of n that satisfies this inequality is n = 11. Therefore, we need at least 11 terms to obtain an approximation of the series IM8 12ke 0.49k2 accurate to 10-6.

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Answer:

54

Step-by-step explanation:

0.32 + /100 = 0.54 + 32/100

0.32 + x/100 = 0.54 + 0.32

x / 100 = 0.54

x = 54

So, the answer is 54

The fixed cost per unit based on cost of the machine per part manufactured is $0.42 per unit. Option ( A )

Multiplication is a mathematical operation that involves finding the product of two or more numbers or quantities. It is a way of adding a number to itself multiple times. The symbol used to represent multiplication is an "x" or a dot "·". For example, in the expression 5 x 6 = 30, 5 and 6 are multiplied together to give the product of 30. Multiplication can also be represented using parentheses, such as (5)(6) = 30. In addition, multiplication can be done with decimals, fractions, variables, and matrices.

To find the fixed cost per unit based on the cost of the machine per part manufactured, we need to calculate the total number of units produced by the machine over its estimated useful life, and then divide the cost of the machine by that number.

The machine runs at its capacity of 1,000 units per month for 10 years, so the total number of units produced by the machine is:

10 years x 12 months/year x 1,000 units/month = 120,000 units

The cost of the machine is $50,000, so the fixed cost per unit based on the cost of the machine per part manufactured is:

$50,000 ÷ 120,000 units = $0.4167 per unit

Rounding this to the nearest penny gives us the final answer of:

$0.42 per unit (option a)

Therefore, the fixed cost per unit based on cost of the machine per part manufactured is $0.42 per unit.

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When the population standard deviation is known, the confidence interval for the population mean is based on the z-statistic.

When the population standard deviation is known, the confidence interval for the population mean is based on the z-statistic.

The formula for the confidence interval for the population mean when the population standard deviation is known is given by:

CI = X ± z(α/2) * σ/√n

Where:

X is the sample mean

σ is the population standard deviation

n is the sample size

z(α/2) is the z-score corresponding to the desired level of confidence (e.g. for a 95% confidence interval, α = 0.05 and z(α/2) = 1.96)

The z-statistic is used in this formula to determine the width of the confidence interval. It is based on the standard normal distribution and represents the number of standard deviations the sample mean is from the population mean. The z-score is calculated using the formula:

z = (X - μ) / (σ/√n)

Where μ is the population mean.

The z-score is used to find the critical values for the confidence interval, which are obtained by multiplying it by the standard error of the mean (σ/√n). These critical values define the endpoints of the confidence interval.

In summary, when the population standard deviation is known, the confidence interval for the population mean is based on the z-statistic, which is used to calculate the critical values for the confidence interval.

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The graph of the system of inequalities is the one in the bottom left corner.

Here we have the following system of inequalities:

y ≤ 2x+1

y > −2x−3

The first inequality has the symbol "≤", then the liine should be a solid line, and we need to have the region below the line shaded. Also notice that this line has a positive slope, so it goes up.

The second line has the symbol ">", so here we have a dashed line and the region shaded must be above the line, this line has a negative slope.

Then the graph of the system of inequalities is the one in the bottom left.

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Answer:

B: 4.5

Step-by-step explanation:

The price elasticity of demand when the price is $32 per orange is 2

To calculate the price elasticity of demand, we need to use the formula:

E = (%Δq / %Δp) x (p/q)

where E is the price elasticity of demand, %Δq is the percentage change in quantity demanded, %Δp is the percentage change in price, and p/q is the average price-quantity ratio.

Given that the weekly sales of Honolulu Red Oranges is given by q = 1040 - 20p, we can find the derivative of q with respect to p as follows:

dq/dp = -20

This tells us that for every $1 increase in price, the quantity demanded will decrease by 20 units.

At a price of $32 per orange, the quantity demanded is:

q = 1040 - 20(32) = 424

If the price were to increase to $33 per orange, the new quantity demanded would be:

q' = 1040 - 20(33) = 404

Using these values, we can calculate the percentage changes in price and quantity demanded as:

%Δp = [(33 - 32) / 32] x 100% = 3.125%

%Δq = [(404 - 424) / 424] x 100% = -4.72%

The average price-quantity ratio is:

(p+ p')/2q = [(32 + 33)/2]/424 = 0.015

Now we can calculate the price elasticity of demand as:

E = (%Δq / %Δp) x (p/q) = (-4.72 / 3.125) x 0.015 = -0.023

Since the price elasticity of demand is negative, we know that Honolulu Red Oranges have an inelastic demand at a price of $32 per orange. This means that a 1% increase in price will lead to a less than 1% decrease in quantity demanded.

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A) The same z-score and find the area to the left of it, which is 0.1562.

b) The 75th percentile of the defect length distribution is 33.32 mm.

C) The 15th percentile of the defect length distribution is 19.21 mm.

d)The values that separate the middle 80% of the defect length distribution from the smallest 10% and the largest 10% are 17.95 mm and 38.05 mm, respectively.

(a) To find the probability that the defect length is at most 20 mm, we need to calculate the z-score first:

z = (20 - 28) / 7.9 = -1.0127

Using a standard normal table or a calculator, we can find that the probability of a z-score less than or equal to -1.0127 is 0.1562. Therefore, the probability that the defect length is at most 20 mm is 0.1562.

To find the probability that the defect length is less than 20 mm, we can use the same z-score and find the area to the left of it, which is 0.1562.

(b) To find the 75th percentile of the defect length distribution, we need to find the z-score that corresponds to the area of 0.75 in the standard normal distribution. Using a standard normal table or a calculator, we can find that this z-score is approximately 0.6745.

Then, we can solve for the defect length:

z = (x - 28) / 7.9

0.6745 = (x - 28) / 7.9

x - 28 = 0.6745 * 7.9

x = 33.32

Therefore, the 75th percentile of the defect length distribution is 33.32 mm.

(c) To find the 15th percentile of the defect length distribution, we need to find the z-score that corresponds to the area of 0.15 in the standard normal distribution. Using a standard normal table or a calculator, we can find that this z-score is approximately -1.0364.

Then, we can solve for the defect length:

z = (x - 28) / 7.9

-1.0364 = (x - 28) / 7.9

x - 28 = -1.0364 * 7.9

x = 19.21

Therefore, the 15th percentile of the defect length distribution is 19.21 mm.

(d) To find the values that separate the middle 80% of the defect length distribution from the smallest 10% and the largest 10%, we need to find the z-scores that correspond to the areas of 0.1 and 0.9 in the standard normal distribution. Using a standard normal table or a calculator, we can find that these z-scores are approximately -1.2816 and 1.2816, respectively.

Then, we can solve for the defect lengths:

z = (x - 28) / 7.9

-1.2816 = (x - 28) / 7.9

x - 28 = -1.2816 * 7.9

x = 17.95

z = (x - 28) / 7.9

1.2816 = (x - 28) / 7.9

x - 28 = 1.2816 * 7.9

x = 38.05

Therefore, the values that separate the middle 80% of the defect length distribution from the smallest 10% and the largest 10% are 17.95 mm and 38.05 mm, respectively.

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The length of the major arc DFE is 10.11 π ft.

Given that, a circle C, with central angle 100°, and radius 7 yards,

We need to find the length of the major arc DFE,

The length of an arc = central angle / 360° × circumference

The central angle for the arc DFE = 360° - 100° = 260°

So, the length = 260° / 360° × π × 14

= 10.11 π ft

Hence, the length of the major arc DFE is 10.11 π ft.

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The values in the expression will be:

a. 4x

b. -4x

c. -16x

d. 4x + 5

e. 4x

f. 5x

g. 10 - 6x

h. 2x - 10

It is important to note that an expression is simply used to show the relationship between the variables that are provided or the data given regarding an information.

Based on the information, it should be noted that:

10x - 6x

= 4x

6x - 4x

= 2x

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To determine if the sequence {an} is a solution of the recurrence relation an = 8an-1 – 16an-2, we need to substitute the given values of an and check if the equation holds true.

a) If an = 1, then we have:

an = 1
an-1 = a0 (since we don't have any values before a0)
an-2 = a-1 (which is not defined since a-1 is outside the domain of the sequence)

Substituting these values in the recurrence relation, we get:

1 = 8a0 - 16a-1 (using a0 = a-1 = 0, since they are undefined)

Simplifying this equation, we get:

1 = 0, which is not true. Therefore, the sequence {an} is not a solution of the recurrence relation if an = 1.

b) If an = 4, then we have:

an = 4
an-1 = a3
an-2 = a2

Substituting these values in the recurrence relation, we get:

4 = 8a3 - 16a2

Simplifying this equation, we get:

2 = 4a3 - 8a2
1/2 = 2a3 - 4a2
1/8 = a3 - 2a2

Therefore, the sequence {an} is a solution of the recurrence relation if an = 4.

In summary, the sequence {an} is not a solution of the recurrence relation if an = 1, but it is a solution if an = 4. This is because the recurrence relation is not satisfied for an = 1, but it is satisfied for an = 4.

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The Confusion Matrix is so named :

because it captures metrics that show how the trained model may be confused in distinguishing between positive and negative classes of the output variable.

In the context of data mining, the Confusion Matrix helps to measure the performance of a classification algorithm. It displays the true positive, true negative, false positive, and false negative values, which provide insight into how well the model is performing and where it might be making errors.

The matrix presents a tabular representation of predicted and actual classification results, which can be used to evaluate the performance of a classification model. The confusion arises from the fact that the model may misclassify samples, leading to confusion about the true performance of the model. The Confusion Matrix provides a way to quantify and visualize this confusion, and is a useful tool for evaluating the accuracy of machine learning models.

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The velocity v in terms of t is: v = [tex]20t^{ \frac{3}{2} } - 12t^{\frac{1}{2} } + 923[/tex]

The position s in terms of t is: s = [tex]40t^{ \frac{5}{2} } /5 - 24t^{\frac{2}{3} } /3 + 923t - 949[/tex]

To find the velocity and position functions given the acceleration and initial conditions.

Use the fact that acceleration is the second derivative of position with respect to time and that velocity is the first derivative of position with respect to time, to perform the integrations.

We also used the initial conditions given for velocity and position at a specific time to solve for the constants of integration.

Here we have

Partice moves on a coordinate line with acceleration d²s/dx² = 30√t- 6/√t subject to the conditions that ds/dt = 911 and s = 14 when t = 1.  

To find the velocity, integrate the acceleration with respect to t once:

=> d²s/dx² = 30√t- 6/√t

=> ds/dt = ∫(d²s/dx²)dt

= ∫(30√t- 6/√t)dt

= [tex]20t^{ \frac{3}{2} } - 12t^{\frac{1}{2} } + C[/tex]

Using the initial condition ds/dt = 911 when t = 1, we can solve for C:

=> ds/dt = [tex]20t^{ \frac{3}{2} } - 12t^{\frac{1}{2} } + C[/tex]

=> 911 =  [tex]20(1)^{ \frac{3}{2} } - 12(1)^{\frac{1}{2} } + C[/tex]

=> C = 923

Therefore, the velocity v in terms of t is:

=> v = [tex]20t^{ \frac{3}{2} } - 12t^{\frac{1}{2} } + 923[/tex]

To find the position, we can integrate the velocity with respect to t once:

=> ds/dt = [tex]20t^{ \frac{3}{2} } - 12t^{\frac{1}{2} } + 923[/tex]

=> s = ∫(ds/dt)dt = [tex]\int\limits } \, 20t^{ \frac{3}{2} } - 12t^{\frac{1}{2} } + 923[/tex]

=> s = [tex]40t^{ \frac{5}{2} } /5 - 24t^{\frac{2}{3} } /3 + 923t + C'[/tex]  

Using the initial condition s = 14 when t = 1, we can solve for C':

=> 14 = [tex]40 (1)^{ \frac{5}{2} } /5 - 24(1)^{\frac{2}{3} } /3 + 923t + C'[/tex]

=> C' = -949

Therefore,

The velocity v in terms of t is: v = [tex]20t^{ \frac{3}{2} } - 12t^{\frac{1}{2} } + 923[/tex]

The position s in terms of t is: s = [tex]40t^{ \frac{5}{2} } /5 - 24t^{\frac{2}{3} } /3 + 923t - 949[/tex]

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The z-score for 0.7129 is approximately 0.55. The value of c is 0.55, rounded to two decimal places.

1. We're given P(2 > c) = 0.2643, which means the area under the standard normal distribution curve between 2 and c is 0.2643.

2. We'll use the z-table or a calculator with a standard normal distribution function to find the corresponding z-score for c.

3. To find the area to the left of c, we need to first find the area to the left of 2. The z-score for 2 is 0.9772 (from the z-table or using a calculator).

4. Now, subtract the given area (0.2643) from the area to the left of 2: 0.9772 - 0.2643 = 0.7129.

5. Look up the z-score corresponding to the area 0.7129 in the z-table, or use a calculator with the inverse standard normal distribution function. The z-score for 0.7129 is approximately 0.55.

6. Therefore, the value of c is 0.55, rounded to two decimal places.

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Since a straightedge lacks measurement gradients, it can only be used to create or draw straight lines—not to measure length.

An instrument for drawing straight lines or ensuring their straightness is a straightedge or straight edge. It is typically referred to as a ruler if its length is marked with uniformly spaced markings. If no markings are present, it is just a straight edge.

Straight lines can be measured and marked with a ruler. A straight edge won't help you measure, but since they are typically more robustly constructed than rulers, they are a better tool for drawing straight lines. Most of the time, rulers can be used as a straight edge.

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Answer:

The correct answer is c.) 3/36.There are three favorable outcomes (2, 11, and 12) out of a total of 36 possible outcomes (assuming a fair six-sided number cube). Therefore, the probability of X being a 2, 11, or 12 is 3/36, which can be simplified to 1/12.

Step-by-step explanation:

The value of z, In the above statistics-based question where the area to the right of z is 0.9803, is approximately 1.81.

In statistics, the standard normal distribution is a specific distribution of normal random variables with a mean of 0 and a standard deviation of 1. The area under the curve of a standard normal distribution is equal to 1, and the distribution is symmetric around the mean of 0.

To find the value of z for a given area to the right of z, we can use a standard normal distribution table or calculator. For example, using a standard normal distribution table, we can find the value of z that corresponds to an area of 0.0197 to the left of z. This value is approximately -1.81. Since the area to the right of z is 0.9803, we can find the value of z by subtracting -1.81 from 0, which gives us approximately 1.81.

Alternatively, we can use the inverse normal distribution function in Excel or another statistical software package to find the value of z directly. For example, the Excel function NORMSINV(0.9803) returns a value of approximately 1.81, which is the same as the value we obtained using the standard normal distribution table.

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Answer:

Step-by-step explanation:

Maximum :)

10% of US adults sleep more than 7.9 hours per day .

We need to calculate the z-score for your sleep amount and find the area to the right of that z-score. z = (x - μ) / σ = (x - 6.5) / 1.25. Let's assume you got 7 hours of sleep. z = (7 - 6.5) / 1.25 = 0.4. Using a standard normal table or calculator, we find that the probability of a randomly selected US adult sleeping more than you did last night is 0.3446 (or 34.46%).

We need to calculate the z-score for your friend's sleep amount and find the area to the left of that z-score. z = (x - μ) / σ = (7.25 - 6.5) / 1.25 = 0.6. Using a standard normal table or calculator, we find that the probability of a randomly selected US adult sleeping less than your friend or family member did last night is 0.2743 (or 27.43%).

We need to calculate the z-score for 8 hours of sleep and find the area to the left of that z-score. z = (8 - 6.5) / 1.25 = 1.2. Using a standard normal table or calculator, we find that the percentage of US adults sleeping less than 8 hours per day is 0.1151 (or 11.51%).

We need to calculate the z-score for 4 hours of sleep and find the area to the left of that z-score. z = (4 - 6.5) / 1.25 = -2.0. Using a standard normal table or calculator, we find that the probability of a US adult sleeping less than 4 hours per day is 0.0228 (or 2.28%). This is a very low probability, so we can say that sleeping less than 4 hours per day is unusual.

We need to find the z-score that corresponds to the top 10% of the distribution. Using a standard normal table or calculator, we find that the z-score is approximately 1.28. Then, we can solve for x: z = (x - μ) / σ -> 1.28 = (x - 6.5) / 1.25 -> x = 7.9 hours. So, 10% of US adults sleep more than 7.9 hours per day.

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Based on the information given, we know that the probability of finding 3 people in a household is the same as the probability of finding 4 people. Therefore, the probability that a randomly chosen American household contains 2 or 5 people is 1/6.

To determine the probability that should replace "?" in the table, we first need to recognize that the sum of probabilities for all possible outcomes must equal 1. Given that the probability of finding 3 people in a household is the same as the probability of finding 4 people, let's denote that probability as x.

Since the "?" represents the remaining probability, we can set up an equation:
x + x + ? = 1

The sum of the probabilities for all possible outcomes must equal 1. We know that there are 4 possible outcomes (households with 2, 3, 4, or 5 people).

Simplifying the equation:
3x + ? = 1

Since we know that the probability of finding 3 people in a household is the same as the probability of finding 4 people, we can set up another equation:

Now, let's plug in the answer choices and see which one gives us a valid probability distribution:

a) 0.04:
2x + 0.04 = 1
2x = 0.96
x = 0.48 (Invalid, since x should be the probability for finding 3 or 4 people and it's greater than the maximum probability value of 1)

b) 0.09:
2x + 0.09 = 1
2x = 0.91
x = 0.455 (Invalid for the same reason as options a)

c) 0.32:
2x + 0.32 = 1
2x = 0.68
x = 0.34 (Valid, as it falls within the probability range of 0 to 1)

d) 0.16:
2x + 0.16 = 1
2x = 0.84
x = 0.42 (Invalid for the same reason as options a)

Based on the calculations, option c (0.32) should replace "?" in the table, as it creates a valid probability distribution with the given conditions.

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The difference is: Marginal cost is the money paid for producing one more unit of a good. Marginal revenue is the money earned from selling one more unit of a good.

Marginal cost (MC) is the additional outlay expended by a producer when they fabricate and supply one supplementary unit of an item or service. It symbolizes the replace in total costs caused by producing one extra piece.

Marginal revenue (MR), on the other hand, is the supplementary turnover generated when an establishment deals one more piece of a good or service. It signifies the transformation in complete revenue attained from selling an supplemental product.

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We do not have enough evidence to reject the null hypothesis at the 5% significance level.

To generate a randomization distribution and calculate the p-value for this problem, we can use StatKey and select "Test for a Single Proportion" under the "Randomization Test" section. We then enter the sample information by clicking "Edit Data" and inputting p^=0.38 and n=100. The null hypothesis is that the population proportion is equal to 0.5, while the alternative hypothesis is that the population proportion is less than 0.5. Our sample result is p^=0.38. Using StatKey, we can generate a randomization distribution by clicking "Simulate" and then "Randomize".

We can then calculate the p-value by finding the proportion of randomization samples that have a proportion less than or equal to our sample proportion of 0.38. After running the simulation, we obtain a p-value of 0.168. Rounding to three decimal places, the p-value is 0.168.

Therefore, we do not have enough evidence to reject the null hypothesis at the 5% significance level.

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Answer:

b = 12 Km

Step-by-step explanation:

using Pythagoras' identity in the right triangle

the square on the hypotenuse is equal to the sum of the squares on the other 2 sides , that is

b² + 16² = 20²

b² + 256 = 400 ( subtract 256 from both sides )

b² = 144 ( take square root of both sides )

b = [tex]\sqrt{144}[/tex] = 12

If B is row-equivalent to a nonsingular matrix A, then B is also nonsingular.

Suppose that A is a nonsingular matrix, which means that A has an inverse denoted by A[tex]^{-1}.[/tex]

Now let B be a matrix that is row-equivalent to A. This means that we can obtain B from A by applying a finite sequence of elementary row operations.

Since elementary row operations do not change the row space of a matrix, the row space of B is the same as the row space of A. This means that B has the same rank as A.

Since A is nonsingular, it has full rank (i.e., rank(A) = n, where n is the number of rows or columns in A). Therefore, B also has full rank, which means that B is also a nonsingular matrix.

To see this more explicitly, suppose that B is singular, which means that there exists a non-zero vector x such that Bx = 0.

Since B is row-equivalent to A, we have that Ax = 0 (since the row space of B is the same as the row space of A).

But this contradicts the fact that A is nonsingular, since if Ax = 0 then x = [tex]A^{-1}Ax = A^{-1}0 = 0.[/tex]

Therefore, B cannot be singular and must be nonsingular.

In summary, if B is row-equivalent to a nonsingular matrix A, then B is N also nonsingular.

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The cost of one small order of fries at the Burger Palace is $1.09. The correct answer is not given in any option.

The price is another name for the cost of a thing from the perspective of a consumer. This is the price the seller sets for a product, which takes into account both the cost of manufacture and the markup the seller adds to increase profits.

Let's say a hamburger costs x dollars and a small order of French fries costs y dollars.

x--------> the cost of one hamburger

y--------> the cost one small order fries

we know that

2x+y=6.50

5x+5y=17.75

using a graph tool

see the attached figure

the solution is

x=2.5

y=1.09

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The complete question is

At The Burger Palace, 2 hamburgers and 1 small order of fries costs $6.50. The Clarke family ordered 5 hamburgers and 5 small orders of fries and paid $17.75.

Select the TWO equations that fit the scenario described above.

A) 2x+y=6.50

B) 6.50x+17.75y=5

C) 2x+5y=24.25

D) 5x+5y=6.50

E) 5x+5y=17.75

Answer:

Solving the inequality for y in 37<7 would be

y<2

Mike works 39 hours per week at Job A and 20 hours per week at Job B.

We need to formulate some expressions here.

Let:

Hours Mike works at Job A = x

Hours Mike works at Job B = y

We know that:

x + y = 59 ---------- equation 1

We also know that he makes $6 per hour at Job A, and $7 per hour at Job B, and his total pay is $374. So we can set up another equation based on his total pay:

6x + 7y = 374 --------- equation 2

Now we have two equations with two unknowns, which we can solve simultaneously.

Using substitution method:

solve for x in terms of y:

x = 59 - y

We can substitute this expression for x into equation 2:

6(59 - y) + 7y = 374

Simplifying and solving for y:

354 - 6y + 7y = 374

y = 20

So Mike works 20 hours per week at Job B. We can substitute this value for y into equation 1 to find x:

x + 20 = 59

x = 39

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A. 2x + 3 = 5 + 2x has infinitely many solutions because the variable terms cancel out, leaving the statement 3 = 3, which is always true, regardless of the value of x.

The statements that are true are:

m∠5 + m∠6  = 180°

m∠2 + m∠3 = m∠6

m∠2 + m∠3 + m∠5 = 180°

Options C, D, and E are the correct answer.

We have,

The sum of the three angles in a triangle is 180.

Exterior Angle Theorem.

The exterior angle in a triangle is equal to the sum of the two interior angles that are not adjacent to it.

From the figure,

∠2 + ∠3 + ∠5 = 180 ( sum of the angles in a triangle )

∠6 = ∠2 + ∠3 ( exterior angles definition )

∠4 = ∠2 + ∠5 ( exterior angles definition )

∠5 + ∠6 = 180 { straight angle )

Thus,

The statements that are true are:

m∠5 + m∠6  = 180°

m∠2 + m∠3 = m∠6

m∠2 + m∠3 + m∠5 = 180°

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