Marine has a 6-inch-wide rectangular photograph. She wants to enlarge the photograph using the scale 1:5. What is the width of the enlarged photograph?

The probability that the mean of a sample of 70 computers would differ from the population mean by less than 1.9 months is 0.1217.

In this problem, we have to find the probability that the mean of a sample of 70 computers would differ from the population mean by less than 1.9 months, given that the quality control manager believes that the mean life of a computer is 105 months, with a variance of 81.

To solve this problem, we can use the Central Limit Theorem, which states that the sample mean of a sufficiently large sample size, drawn from any population, will be approximately normally distributed with mean μ and variance σ²/n, where μ is the population mean, σ² is the population variance, and n is the sample size.

In this case, we know that the population mean is μ = 105 months and the population variance is σ² = 81. Since we are interested in the mean of a sample of 70 computers, we can use the formula for the standard error of the mean, which is σ/√n, to calculate the standard deviation of the sampling distribution of the mean.

The standard deviation of the sampling distribution of the mean is given by σ/√n = √(81/70) ≈ 1.226.

Now, we want to find the probability that the mean of a sample of 70 computers would differ from the population mean by less than 1.9 months. We can standardize this difference using the formula

z = (x' - μ)/(σ/√n), where x' is the sample mean.

Substituting the values, we get z = (x' - 105)/(1.226), and we want to find the probability that |z| < 1.9/1.226 ≈ 1.550.

Using a standard normal distribution table, we can find that the probability of |z| < 1.550 is approximately 0.1217.

Therefore, the probability that the mean of a sample of 70 computers would differ from the population mean by less than 1.9 months is 0.1217.

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The value of equivalent expression is,

3 = 87 ÷ h

We have to given that;

Equation is,

⇒ 3/5 = 17 2/5 ÷ h

Now, We can simplify as;

⇒ 3/5 = 17 2/5 ÷ h

⇒ 3/5 = 87/5 ÷ h

⇒ h = 87/5 × 5/3

⇒ h = 29

For Option A;

3 = 87 ÷ h

h = 87 / 3

h = 29

For B;

3 × 9 = (87 ÷ h) ÷ 9

27 × 9 = 87 ÷ h

h = 87 / 27 x 9

h = 0.35

C) 3 - 9 = 87 ÷ h

h = 87 / - 3

h = - 29

Thus, The value of equivalent expression is,

3 = 87 ÷ h

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Step-by-step explanation:

f'(x)=-4x-16

f'(x)=0 <=> x=-4

evaluating the derivative of fx on the numberline we get the negative interval is (-4;+infinity)

The function f(x) = 2x² - 16x - 30 is negative between the roots x = -3 and x = 5. This is found using the quadratic formula to identify the roots and observing that the function dips below the x-axis between these two points.

To find the intervals where f(x) is negative, you would want to determine where the quadratic function is below the x-axis, which means finding the roots of the function first.

Given the quadratic function in standard form as: f(x) = 2x² - 16x - 30

To find the roots, you can use the quadratic formula: x = [-b ± sqrt(b² - 4ac)] / 2a

When you substitute a = 2, b = -16, and c = -30 into the formula, you get x = 5 and x = -3.

Therefore, the function f(x) is negative between these two roots (that is, -3 < x < 5).

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To set up an integral for the volume of the solid obtained by rotating the region in the first quadrant bounded by the curves y, we would use the method of cylindrical shells.

First, we need to identify the limits of integration. The region in the first quadrant is bounded by the curves y, which intersect at the point (1,1). So our limits of integration will be from 0 to 1.

Next, we need to determine the radius and height of each cylindrical shell. The radius will be the distance from the x-axis to the curve y, which is simply y. The height will be the length of the shell, which is the difference between the x-coordinates of the two curves at that value of y.

So our integral will be:

∫[0,1] 2πy(x2 - y2) dy

where x2 is the equation of the curve y=x2 and y2 is the equation of the curve y=x.

Note that we do not evaluate this integral, as the question specifically asks us to only set it up.

To set up, but not evaluate, an integral for the volume of the solid obtained by rotating the region in the first quadrant bounded by the curves y, I need the equations of the curves and the axis of rotation.

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The measure of angles:

∠S = 72

∠Q = 72

∠R = 180

In the given trapezium

∠P  = 108 degree

We know that for a trapezium,

The sum of the angles of two adjacent sides = 180°.

Therefore,

∠S + 108 = 180

⇒       ∠S = 72 degree

And

∠Q + 108 = 180

⇒        ∠Q = 72 degree

Now.

  ∠S + ∠R = 108

⇒ 72 + ∠R = 180

⇒         ∠R = 108 degree

Hence,

∠S = 72

∠Q = 72

∠R = 180

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As per the Laplace transform, the solution of the equation is (s² + 2s + 1)Y(s) = -s - 4 + 1/(s - 3).  (option a).

The given differential equation y'' + 2y' + y = ([tex]e^{(3t)}[/tex]) represents a harmonic oscillator with a forcing term ([tex]e^{(3t)}[/tex]). To solve this equation using the Laplace transform, we apply the transform to both sides of the equation and use the linearity property of the transform to obtain:

L(y'') + 2L(y') + L(y) = L([tex]e^{(3t)}[/tex])

Using the derivative property of the Laplace transform, L(y'') = s²Y(s) - s*y(0) - y'(0) and L(y') = sY(s) - y(0), where Y(s) is the Laplace transform of y(t). Substituting these expressions into the above equation and simplifying, we get:

(s² + 2s + 1)Y(s) = s - 4 + 1/(s - 3)

where we have used the initial conditions y(0) = 1 and y'(0) = 2 to obtain the constants s*y(0) and y(0) in the Laplace transforms of y'' and y', respectively.

Therefore, the correct answer is (a) (s² + 2s + 1)Y(s) = -s - 4 + 1/(s - 3).

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The kurtosis value of the data set with many extreme low and high values is expected to be high. Outliers can significantly affect the kurtosis value of a distribution, resulting in a higher kurtosis value.

Kurtosis is a statistical measure that indicates the degree of heaviness or lightness in the tails of a probability distribution compared to the normal distribution. A high kurtosis value indicates that the distribution has more extreme values in its tails than a normal distribution.

When a data set has many extreme low and high values, it means that the data set has a lot of outliers or extreme values. Outliers can significantly affect the kurtosis value of a distribution, resulting in a higher kurtosis value.

In summary, a data set with many extreme low and high values is expected to have a higher kurtosis value than a data set with fewer outliers.

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Our prediction is that it will take 130 students a total of 8,450 minutes to study for the test. So, the correct answer is "It will take them 8,450 minutes."

We can use the idea of proportionality to make a prediction about the time it will take 130 students to study for the test. Assuming that the amount of studying required for the test is the same for all students, we can say that the total amount of studying time is directly proportional to the number of students.

Let T be the time required for 130 students to study for the test. Then we can set up a proportion:

25 students / 1,625 minutes = 130 students / T

Solving for T, we get:

T = (130 students x 1,625 minutes) / 25 students = 8,450 minutes

Therefore, our prediction is that it will take 130 students a total of 8,450 minutes to study for the test. So, the correct answer is "It will take them 8,450 minutes."

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The census bureau would consider a household of three that earns $12,000 to be living below the poverty threshold. The poverty threshold is the minimum income required to meet basic needs such as food, shelter, and clothing. If a household earns less than the poverty threshold, it means they are unable to afford these basic necessities. In the case of a household of three, the poverty threshold is approximately $16,000. Therefore, a household earning $12,000 falls short of this minimum requirement and is considered to be living in poverty.

The poverty threshold is an important benchmark used by the census bureau to determine the poverty status of households. It is based on the income level required to meet basic needs such as food, shelter, and clothing. The poverty threshold varies based on the size of the household and is adjusted annually for inflation.

A household of three that earns $12,000 would be considered to be living below the poverty threshold by the census bureau. This means that they are unable to afford basic necessities and are experiencing financial hardship. It highlights the need for policies and programs that address poverty and support those who are struggling to make ends meet.

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Answer:

935.65 minutes.

Step-by-step explanation:

The battery life of the nth model can be represented by the exponential function:

f(n) = 735(1.04)^(n-1)

where n is the number of the model.

To find the battery life of the latest model 7 months from now, we need to find f(8):

f(8) = 735(1.04)^(8-1)

f(8) = 735(1.04)^7

f(8) = 935.65

Therefore, the battery life of the latest model 7 months from now will be approximately 935.65 minutes.

Note: The battery life is rounded to two decimal places.

Yes, this equation M=45−7. 5d is useful to calculate the number of miles left after each day.

On the 6th day they cover 45 miles.

Plan to cover distance by hiking club to hike = 45 mile

Per day hiking = 7.5 miles

The equation M = 45 - 7.5d represents the number of miles remaining to hike after each day of hiking,

where M is the number of miles remaining and d is the number of days of hiking.

Let us use this equation to calculate the number of miles remaining after each day of hiking.

For Day 1,

d = 1

M = 45 - 7.5(1)

    = 45 - 7.5

    = 37.5 miles remaining

For Day 2,

d = 2

M = 45 - 7.5(2)

   = 45 - 15

   = 30 miles remaining

For Day 3,

d = 3

M = 45 - 7.5(3)

   = 45 - 22.5

   = 22.5 miles remaining

And so on...

For Day 4,

d = 4

M = 45 - 7.5(4)

   = 45 - 30

   = 15 miles remaining

For Day 5,

d = 5

M = 45 - 7.5(5)

   = 45 - 37.5

   = 7.5 miles remaining

For Day 6,

d = 6

M = 45 - 7.5(6)

   = 45 - 45

   = 0 miles remaining

By continuing the pattern it is easy to calculate the number of miles remaining .

After each day of hiking until the remaining miles reach 0, indicating the completion of the 45-mile hike.

Therefore, this equation help us to calculate the number of miles remaining.

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By using the table of values, a graph of the number of tables along the x-axis and the number of guests along the y-axis is shown in the image below.

In Mathematics and Geometry, the point-slope form of a straight line can be calculated by using the following mathematical equation (formula):

y - y₁ = m(x - x₁)

Where:

Based on the sitting arrangement, we have:

x                 y_____

1 table    6 guests.

2 table    10 guests.

3 table    14 guests.

Next, we would determine the slope;

Slope (m) = (y₂ - y₁)/(x₂ - x₁)

Slope (m) = (10 - 6)/(2 - 1)

Slope (m) = 4/1

Slope (m) = 4

At data point (1, 6) and a slope of 4, a linear equation for this line can be calculated by using the point-slope form as follows:

y - y₁ = m(x - x₁)

y - 6 = 4(x - 1)

y = 4x - 4 + 6

y = 4x + 2

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Missing information:

The question is incomplete and the complete question is shown in the attached picture.

The required weight of 1 1/2 packs of paper is 7 1/8 pounds.

One pack of paper weighs 4 3/4 pounds.

Thus, 1 1/2 packs of paper weigh:

1 1/2 × 4 3/4

= 7 1/8 pounds

Therefore, the weight of 1 1/2 packs of paper is 7 1/8 pounds.

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To determine whether a relation is an equivalence relation, we need to check three properties: reflexive, symmetric, and transitive.

Reflexive property: For all a ∈ A, (a, a) ∈ R.

Symmetric property: For all a, b ∈ A, if (a, b) ∈ R, then (b, a) ∈ R.

Transitive property: For all a, b, c ∈ A, if (a, b) ∈ R and (b, c) ∈ R, then (a, c) ∈ R.

Let's check each property for the given relation R on {0, 1, 6}.

Reflexive property: (0, 0), (1, 1), and (6, 6) are in R, so the reflexive property holds for these elements. However, (1, 1) is the only element in R that satisfies this property. (0, 0) and (6, 6) are not enough to establish the reflexive property for the relation R.

Symmetric property: (0, 1) and (1, 0) are in R, but (1, 0) is not in R. Therefore, the symmetric property does not hold for the relation R.

Transitive property: (0, 1) and (1, 6) are in R, but (0, 6) is not in R. Therefore, the transitive property does not hold for the relation R.

Since the relation R does not satisfy all three properties, it is not an equivalence relation.

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True. Based on the given scatter plot, there is evidence to suggest the model suffers from heteroskedasticity. Heteroskedasticity refers to the presence of unequal variances across different levels of a predictor variable in a regression model.

Based on the scatter plot alone, it is difficult to determine whether or not there is evidence to suggest that the model suffers from heteroskedasticity. Heteroskedasticity refers to the presence of unequal variances in the error term across different levels of the independent variable(s). To test for heteroskedasticity, one would typically examine the residuals of the regression model and look for patterns in the variance of these residuals as a function of the independent variable(s). Therefore, without analyzing the residuals, it is not possible to definitively say whether or not there is evidence of heteroskedasticity.

Heteroskedasticity refers to the presence of unequal variances across different levels of a predictor variable in a regression model. In a scatter plot, this is typically indicated by a pattern in which the spread of the data points increases or decreases along the predictor variable's range.

The presence of heteroskedasticity can have negative consequences for the reliability and efficiency of regression estimates. It can lead to biased standard errors, which can then affect hypothesis testing and confidence intervals. Consequently, it is crucial to identify and address heteroskedasticity when analyzing regression models.

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Answer:

129*

Step-by-step explanation:

First notice the 2 parallel lines. Since the 2 parallel lines are intersecting the same line, the angle measures would be the same for both. Since the first angle is 51*, the corresponding angle for the next line is also 51*. Since it intersects a straight line, the angles need to add up to 180*. 51 + x = 180 so x = 129*

The correct inverse demand function for the given demand function, q = 100 - 5p, is q = 20 - 0.2p.

To understand why q = 20 - 0.2p is the correct inverse demand function, it is necessary to solve for p in terms of q. To do this, we can rearrange the original demand equation as follows:

q = 100 - 5p

5p = 100 - q

p = (100 - q)/5

This equation shows that the price of oranges (p) is a function of the quantity demanded (q). To derive the inverse demand function, we simply need to swap the variables q and p:

q = 20 - 0.2p

This equation shows that the quantity demanded (q) is a function of the price (p) and gives us a downward sloping demand curve. The other three equations provided are incorrect because they do not represent the relationship between price and quantity demanded correctly. In summary, the correct inverse demand function for the given demand function, q = 100 - 5p, is q = 20 - 0.2p.

This equation shows that the quantity demanded (q) is a function of the price (p) and that as the price of oranges increases, the quantity demanded decreases. In other words, the demand curve for oranges is downward sloping, which is a common characteristic of most goods in a market economy. It is important to note that the other three equations provided are incorrect and do not represent the inverse demand function for this scenario.

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Answer:

  in the triangle shown, AX = (2/3)AG

Step-by-step explanation:

You want to prove the medians meet at a point 2/3 of the distance from the vertex to the opposite side.

Consider triangle ABC shown in the attached. Without any loss of generality, we can assign coordinates to the vertices as ...

  A(0, 0), B(6a, 0), C(6b, 6c)

Then the segment midpoints are ...

  G = (B+C)/2 = (3(a+b), 3c), H = (C +A)/2 = (3b, 3c), J = (A+B)/2 = (3a, 0)

The lines through a pair of coordinates (x1, y1) and (x2, y2) will have equations ...

  y = (y2 -y1)/(x2 -x1)(x -x1) +y1

Median AG has equation ...

  y = (3c/(3(a+b))(x -0) +0 = cx/(a+b)

Median BH has equation ...

  y = (3c)/(3b -6a)(x -6a) +0

When written in the form px -y = q, we have ...

The second attachment shows the solution of these equations is ...

  X = (2(a+b), 2c)

This point is 2/3 of the distance from vertex A to the opposite midpoint G:

  (2(a+b), 2c) = (2/3)×(3(a+b), 3c)

Hence the intersection of medians is 2/3 of the distance from the vertex to the opposite side.

__

Additional comment

We can verify that point X is also 2/3 of the distance from the other vertices to their opposite sides.

The 2/3 point of BH is (2H+B)/3 = (2(3b, 3c) +(6a, 0))/3 = (2(a+b), 2c)

The 2/3 point of CJ is (2J +C)/3 = (2(3a, 0) +(6b, 6c))/3 = (2(a+b), 2c)

That is, the 2/3 point of each median has the same coordinates as for the others. (Perhaps this is the simplest proof of all.)

The probability that a player will toss the die at least 2 times before blue lands faceup is 15/28.

The geometric distribution, which is a probability distribution that models the number of trials needed to achieve the first success in a sequence of Bernoulli trials, where each trial has a constant probability of success.

In this case, the Bernoulli trial is whether the die lands on blue, and the geometric distribution models the number of tosses needed to achieve the first blue face.

To find the probability that a player will toss the die at least 2 times before blue lands faceup, we need to find the probability of getting either a red or a yellow face on the first toss, and then either a blue face or another red/yellow face on the second toss.

The probability of getting a red or yellow face on the first toss is:

P(Red or Yellow) = 3/8 + 3/8 = 6/8 = 3/4

If the first toss is a red or yellow face,

then the probability of getting a blue face on the second toss is:

P(Blue on 2nd toss | Red or Yellow on 1st toss) = 2/7

So, the probability of getting blue on the second toss given the first toss is red or yellow is 2/7.

Therefore, the probability of not getting a blue face on the second toss given the first toss is red or yellow is 1-2/7=5/7.

Putting it all together, the probability of tossing the die at least 2 times before blue lands faceup is:

P(at least 2 tosses)

= P(Red or Yellow on 1st toss) × P(Not Blue on 2nd toss given Red or Yellow on 1st toss)

= (3/4) × (5/7)

= 15/28

Therefore,

The probability that a player will toss the die at least 2 times before blue lands faceup is 15/28.

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The horizontal distance between the base of the ladder and the wall is 8.6 feet.

distance is the length between two points.

To calculate the horizontal distance between the ladder and the wall, we use the formula below.

Formula:

[tex]\sf cos \ \theta=\dfrac{adjacent(y)}{hypotenuse(h)}[/tex]

Make y the subject of the equation

[tex]\sf h = \dfrac{y}{ cos\ \theta}[/tex]........ Equation 2

Where:

From the question,

Given:

Substitute these values into equation 2

[tex]\sf y = \dfrac{24}{(cos \ 69^\circ)}[/tex]

[tex]\sf y = \dfrac{24}{0.358}[/tex]

[tex]\sf y =\bold{8.6 \ feet}[/tex]

Hence, The horizontal distance between the base of the ladder and the wall is 8.6 feet.

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To find the point at which the line intersects the given plane, we will first substitute the parametric equations of the line into the equation of the plane and then solve for the parameter 't'.

The parametric equations of the line are:

x = 3 - t
y = 2t
z = 2t

The equation of the plane is:

x - y + 5z = 9

Step 1: Substitute the parametric equations of the line into the plane equation:

(3 - t) - (2t) + 5(2t) = 9

Step 2: Simplify the equation and solve for 't':

3 - t - 2t + 10t = 9
7t - t = 6
6t = 6
t = 1

Step 3: Substitute the value of 't' back into the parametric equations of the line to find the intersection point (x, y, z):

x = 3 - t = 3 - 1 = 2
y = 2t = 2(1) = 2
z = 2t = 2(1) = 2

Therefore, the point at which the line intersects the given plane is (2, 2, 2).

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How many triangles exist with the given side lengths: C) More than one triangle exists with the given side lengths.

In Euclidean geometry, the Triangle Inequality Theorem states that the sum of any two side lengths of a triangle must be greater than or equal (≥) to the third side of the triangle.

Mathematically, the Triangle Inequality Theorem is represented by this mathematical expression:

b - c < n < b + c

Where:

n, b, and c represent the side lengths of this triangle.

4 + 4 > 7 (True).

4 + 7 > 4 (True).

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Complete Question:

How many triangles exist with the given side lengths?

4m, 4m, 7m

A) No triangle exists with the given side lengths.

B) Exactly one unique triangle exists with the given side lengths.

C) More than one triangle exists with the given side lengths.

Answer:

  B.  -1/2e^(-2x) +C

Step-by-step explanation:

You want the indefinite integral of ln(e^(e^(-2x))).

The integrand can be simplified using ln(e^x) = x:

  ln(e^(e^(-2x))) = e^(-2x)

The antiderivative of e^a is (1/a)e^a, so the integral of interest is ...

  [tex]\displaystyle \int{e^{-2x}}\,dx=\dfrac{1}{-2}e^{-2x}+C=\boxed{-\dfrac{1}{2}e^{-2x}+C}[/tex]

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The conditions and assumptions for inference are reasonably satisfied, particularly with regard to random sampling, independence, and sample sizes.

To show that the conditions and assumptions for inference are satisfied, we need to assess whether the sample meets the necessary requirements. In this case, we are examining the support for the principal among white and minority students in a large school.

1. Random Sampling: The statement mentions that students were randomly chosen for the survey. Random sampling helps ensure that the sample is representative of the larger population. If the students were truly selected randomly, this condition is satisfied.

2. Independence: To conduct inference, it is essential to assume that the responses from different students are independent of each other. If students were selected randomly and surveyed independently without any influence from one another, this condition is likely to be satisfied.

3. Sample Size: The sample sizes for both white and minority students are given: 56 white students and 33 minority students. While sample size alone does not guarantee inference validity, larger samples tend to provide more reliable estimates.

4. Normality: For inference methods such as hypothesis testing or constructing confidence intervals, the sample data should follow an approximately normal distribution. Since we don't have information about the underlying population or the distribution of the responses, we cannot directly assess the normality assumption. However, if the sample sizes are sufficiently large (typically around 30 or more), the Central Limit Theorem suggests that the sampling distribution will tend to be approximately normal, even if the underlying population is not.

5. Random Assignment (for experiments): The statement doesn't mention whether this study is an experiment with a randomly assigned treatment. Since it only involves surveying students' opinions, this assumption is not applicable in this case.

Based on the information provided, it appears that the conditions and assumptions for inference are reasonably satisfied, particularly with regard to random sampling, independence, and sample sizes. However, without additional information or data, it cannot definitively confirm the exact nature of the population or distribution.

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The poset (n, |) has a unique minimal element 1, but no maximal elements. The poset (n, |) is the set of natural numbers n with the relation "divides" denoted by |. In other words, a | b if and only if a divides b evenly with no remainder.

To determine if there are any minimal elements in this poset, we need to find the smallest element in the set that is related to all other elements. In this case, 1 is the smallest natural number and it is related to all other natural numbers since 1 | n for all n in the set. Therefore, 1 is a minimal element in this poset.

To determine if there are any maximal elements in this poset, we need to find the largest element in the set that is related to all other elements. However, there is no such element in this poset since for any natural number n, there is always another natural number greater than n that is related to it. For example, 2 | 4 and 4 | 8, so 8 is related to both 2 and 4 but it is greater than both of them. Therefore, there are no maximal elements in this poset.

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The distance between two parallel planes is given by the absolute value of the difference between the constant terms in their equations divided by the square root of the sum of the squares of the coefficients of x, y, and z.

In this case, the constant term in the equation 2x − 5y + z = 4 is 4, and the constant term in the equation 4x − 10y − 2z = 2 is 2. Therefore, the absolute value of their difference is |4 - 2| = 2.  The coefficients of x, y, and z in the two equations are 2, -5, 1 and 4, -10, -2, respectively. The sum of the squares of these coefficients is 30 + 41 = 71. Therefore, the distance between the two planes is 2/√71.

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The sampling distribution for random samples of 30 students is most likely to follow a normal distribution.

This is based on the central limit theorem, which states that as sample size increases, the sampling distribution of the mean tends to approach a normal distribution, regardless of the shape of the population distribution.

The normal distribution is characterized by a symmetrical bell-shaped curve and is commonly used in statistical analysis to model a wide range of natural phenomena, including measurement errors, human traits, and physical properties. It is also widely used in inferential statistics to estimate population parameters, such as means and variances, from sample statistics.

Therefore, in the absence of information about the population distribution, a normal distribution is a reasonable assumption for the sampling distribution of random samples of 30 students.

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The sampling distribution for random samples of 30 students is most likely to follow a normal distribution.

This is based on the central limit theorem, which states that as sample size increases, the sampling distribution of the mean tends to approach a normal distribution, regardless of the shape of the population distribution.

The normal distribution is characterized by a symmetrical bell-shaped curve and is commonly used in statistical analysis to model a wide range of natural phenomena, including measurement errors, human traits, and physical properties. It is also widely used in inferential statistics to estimate population parameters, such as means and variances, from sample statistics.

Therefore, in the absence of information about the population distribution, a normal distribution is a reasonable assumption for the sampling distribution of random samples of 30 students.

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Answer:

do you choose the best

Step-by-step explanation:

9 1/2 + 1 1/2

Converting to improper fractions: 9 1/2 = (9 * 2 + 1) / 2 = 19/2 and 1 1/2 = (1 * 2 + 1) / 2 = 3/2

Adding the fractions: 19/2 + 3/2 = (19 + 3) / 2 = 22/2 = 11/1 = 11

5 + 3 1/3

Converting to improper fractions: 5 = 5/1 and 3 1/3 = (3 * 3 + 1) / 3 = 10/3

Adding the fractions: 5/1 + 10/3 = (5 * 3 + 10) / 3 = 25/3

2 4/5 + 16 2/5

Converting to improper fractions: 2 4/5 = (2 * 5 + 4) / 5 = 14/5 and 16 2/5 = (16 * 5 + 2) / 5 = 82/5

Adding the fractions: 14/5 + 82/5 = (14 + 82) / 5 = 96/5

7 1/2 + 2 1/4

Converting to improper fractions: 7 1/2 = (7 * 2 + 1) / 2 = 15/2 and 2 1/4 = (2 * 4 + 1) / 4 = 9/4

Adding the fractions: 15/2 + 9/4 = (15 * 2 + 9) / 2 = 39/4

8 5/6 + 3 2/3

Converting to improper fractions: 8 5/6 = (8 * 6 + 5) / 6 = 53/6 and 3 2/3 = (3 * 3 + 2) / 3 = 11/3

Adding the fractions: 53/6 + 11/3 = (53 * 3 + 11 * 6) / 6 = 257/6

2 7/8 + 3 1/2 + 5 + 3 1/4

Converting to improper fractions: 2 7/8 = (2 * 8 + 7) / 8 = 23/8, 3 1/2 = (3 * 2 + 1) / 2 = 7/2, 3 1/4 = (3 * 4 + 1) / 4 = 13/4

Adding the fractions: 23/8 + 7/2 + 5 + 13/4 = (23 * 2 + 7 * 8 + 5 * 8 + 13 * 2) / 8 = 101/8

5 1/2 + 2 1/3 + 9 1/6 + 2

Converting to improper fractions: 5 1/2 = (5 * 2 + 1) / 2 = 11/2

Answer:

For n = 1, 2, 3,.....,

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

[tex] = 5 {n}^{2} + 5n + 1[/tex]