A family's monthly income is $3531. The family spends 3 over 5 of this on food. How much is spent on food

The mean of the sample proportion is 0.2, and the standard deviation of the sample proportion is approximately 0.02.

The mean and standard deviation of the sample proportion for random samples of size 400 taken from an infinite population with a population proportion of 0.2, we will use the formulas for the mean and standard deviation of sample proportions.

The mean  of the sample proportion is equal to the population proportion (p):
μ_p = p

The standard deviation (σ_p) of the sample proportion is given by the formula:
σ_p = sqrt[(p * (1-p)) / n]

In this case, the population proportion (p) is 0.2, and the sample size (n) is 400.

Step 1: Calculate the mean of the sample proportion:
μ_p = p = 0.2

Step 2: Calculate the standard deviation of the sample proportion:
σ_p = sqrt[(0.2 * (1-0.2)) / 400]
σ_p = sqrt[(0.2 * 0.8) / 400]
σ_p = sqrt[0.16 / 400]
σ_p = sqrt[0.0004]

Step 3: Find the square root of 0.0004:
σ_p ≈ 0.02

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The probability that the committee will have at least 1 senior is 5/6 or approximately 0.833.

What is probability?

Probability is a measure of the likelihood of an event occurring. It is a number between 0 and 1, where 0 means the event is impossible and 1 means the event is certain to happen.

To find the probability that the committee will have at least 1 senior, we can calculate the probability of the committee having no seniors and then subtract that from 1 (since the probability of an event happening plus the probability of it not happening equals 1).

The total number of ways to choose a committee of 3 students from the group of 10 is:

10C3 = (1098)/(321) = 120

Now, let's calculate the number of committees with no seniors. We must choose 3 students from the 6 juniors, which can be done in:

6C3 = (654)/(321) = 20

Therefore, the number of committees with at least 1 senior is:

120 - 20 = 100

So the probability of the committee having at least 1 senior is:

100/120 = 5/6

Therefore, the probability that the committee will have at least 1 senior is 5/6 or approximately 0.833.

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A conversation with your friend explaining the symmetry you observe in nature is given below.

Me: Hey, have you ever noticed how symmetrical nature can be?

Friend: What do you mean?

Me: Well, think about things like snowflakes, leaves, and flowers. They all have a certain amount of symmetry to them.

Friend: Yeah, I guess I've noticed that before. But why is that?

Me: It's actually because of the way that nature grows and develops. The growth of these things is guided by physical laws and processes that tend to produce symmetrical shapes.

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Yes.

It is true that if v1, v2, ..., vp are vectors in Rⁿ, then Span{v1, v2, ..., vp} is the same as the column space of the matrix [v1 v2 ... vp].

True, let A = [v1 v2 ... vp] be the matrix columns are the given vectors.

The column space of A is the set of all linear combinations of the columns of A, which is exactly the same as the span of the vectors v1, v2, ..., vp.

In other words, any vector that can be written as a linear combination of the columns of A is also in Span{v1, v2, ..., vp}, and vice versa.

The tools of linear algebra to study the span of a set of vectors, by considering the column space of the corresponding matrix.

Techniques like row reduction and rank to determine if a set of vectors is linearly independent or spans the whole space Rⁿ.

Yes, the given vectors should be used as the matrix columns in A = [v1 v2... vp].

The span of the vectors v1, v2,..., vp is exactly the same as the column space of A, which is the set of all linear combinations of the columns of A.

This means that any vector that can be expressed as a linear combination of columns from A is also a vector in Spanv1, v2,..., vp and vice versa.

By taking into account the column space of the associated matrix, the techniques of linear algebra may be used to examine the range of a collection of vectors.

To establish if a group of vectors spans the whole space Rn or is linearly independent, use methods like rank and row reduction.

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Answer:

Area= 24 cm^2

Perimeter= 22 cm

Step-by-step explanation:

Area= length*Width

8*3=24

Perimeter= (side a *2) + (side b *2)

(8*2)+ (3*2)

16+6

22

It has returned 13.8% during the past year when the return on one-year treasury bills has been 3.6%. The Sharpe ratio of the North Equity Fund is closest to 0.45.

The Sharpe ratio is a measure of risk-adjusted return and helps investors assess the return they receive for each unit of risk taken. In this case, the North Equity Fund has a beta of 1.67, indicating that it is more volatile than the overall market. The standard deviation of 22.6% also highlights the fund's volatility.

Despite this, the fund has delivered a return of 13.8% over the past year, outperforming the return on one-year Treasury bills, which was 3.6%. The Sharpe ratio, calculated by subtracting the risk-free rate (T-bills return) from the fund's return and dividing it by the fund's standard deviation, yields a value closest to 0.45.

The Sharpe ratio is calculated by subtracting the risk-free rate (in this case, the return on one-year Treasury bills) from the fund's return and dividing it by the fund's standard deviation. In this scenario, the North Equity Fund's return is 13.8% minus the risk-free rate of 3.6%, resulting in a risk premium of 10.2%.

Dividing this risk premium by the fund's standard deviation of 22.6% gives us a Sharpe ratio of approximately 0.45. The Sharpe ratio measures the excess return per unit of risk, with a higher ratio indicating better risk-adjusted performance.

Therefore, the closest answer is 0.45, suggesting that the North Equity Fund provides a relatively modest risk-adjusted return.

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The Laplace transform of F(t) is F(s) = (-2/3s) [[tex]e^{-12s}[/tex] - 1 ]

To find the Laplace transform of the function F(t) = 2/3, 0<t<12, we can use the definition of Laplace transform

F(s) = L{F(t)} = ∫[0,∞) [tex]e^{-st}[/tex] F(t) dt

Since F(t) is a constant function on the interval (0,12), we have:

F(s) = ∫[0,12] [tex]e^{-st}[/tex] (2/3) dt

Using integration by substitution with u = -st, du = -s dt, and limits of integration u(0) = 0 and u(12) = -12s, we get:

F(s) = (2/3) ∫[0,-12s] [tex]e^{u}[/tex] (-1/s) du

= (-2/3s) [ [tex]e^{-12s}[/tex] - 1 ]

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1. The volume and surface area of the pyramid is 216ft³ and 297ft² respectively.

2. The volume and surface area the of pyramid of the pyramid is 1610.4 in³ and 832.75 in² respectively.

A pyramid is a three-dimensional shape. A pyramid has a polygonal base and flat triangular faces,

The volume of a prism is expressed as;

V = 1/3 base area × height

1. V = 1/3 × 9² × 12

V = 648/3

V = 216 ft³

therefore the volume of the pyramid is 216ft³

Surface area = Base area + 4 face area

= 81+ 4 × 1/2 × 12 × 9

= 81+ 4 × 54

= 81 +216

= 297 ft²

2. V = 1/3 bh

base area = 247.75

V = 1/3 × 247.75 × 19.5

= 1610.4 in³

Surface area = base area + 5 face area

= 247.75+ 5 × 1/2 × 12 × 19.5

= 247.75+ 585

= 832.75 in²

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Answer:

Total volume of the figure is 896in³

there are only two possible topologies induced by a metric, and the remaining six topologies are not induced by a metric.

On a set of three elements, there are $2^{\binom{3}{2}} = 2^3 = 8$ possible topologies, since we need to consider all possible subsets of pairs of elements and each pair can be included or excluded from the topology.

To determine how many of these correspond to a topology induced by a metric, we need to verify the following axioms:

The distance between two points is non-negative.

The distance between a point and itself is zero.

The distance between two points is the same regardless of the order in which they are listed.

The triangle inequality holds.

For a set of three elements, there are only two possible metrics that satisfy these axioms: the discrete metric and the metric induced by the Euclidean distance on the real line.

The discrete metric gives rise to the discrete topology, where every subset is open, and the metric induced by the Euclidean distance gives rise to the topology with the following open sets: ${\emptyset, {a}, {b}, {c}, {a,b}, {a,c}, {b,c}, {a,b,c}}$.

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Answer:

30 meters

Step-by-step explanation:

Hope this helps! Pls give brainliest!

Answer:

30 meters

Step-by-step explanation:

Answer: 3 Nickles.

Step-by-step explanation:

22 quarters adds up to $5.50

The remaining 15c is accounted by the last 3 coins, which are nickles.

The sample mean is 8.5 loan periods in 14 days.

The estimated standard error of the mean given the six loan periods is 1.6482

The sample mean can be calculated by adding up all the loan periods and then dividing by the number of records in the sample:

(5 + 7 + 7 + 6 + 10 + 16) / 6 = 51 / 6 = 8.5

Therefore, the sample mean is 8.5 loan periods in 14 days.

b. The estimated standard error of the mean can be calculated using the formula:

SE = s / sqrt(n)

where s is the sample standard deviation and n is the sample size. To calculate the sample standard deviation, we first need to calculate the sample variance:

[tex][(5-8.5)^2 + (7-8.5)^2 + (7-8.5)^2 + (6-8.5)^2 + (10-8.5)^2 + (16-8.5)^2] / (6-1) \\=\\ 24.5[/tex]

√81.5 / 5

= 4.0373

4.0373 / √6

= 1.6482

The estimated standard error of the mean given the six loan periods is 1.6482

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A small community library lends books for periods of 14 days. The policy is being reevaluated in view of a possible new loan period that could be longer than 14 days. To aid in making this decision, book- lending records were consulted to determine the loan periods actually used by the patrons. A random sample of six records revealed the following loan periods in 14 days: 5, 7, 7, 6, 10 and 16.

a. Calculate the sample mean

b. Calculate the estimated standard error of the mean given the six loan periods.

Bentley needs to ride an average of 7.9 miles each day for the next 4 days to meet his goal of riding 39.6 miles in a week.

The equation to determine the average number of miles Bentley needs to ride each day is:

31.6/4 = x

Let x be the average number of miles Bentley must bike each day for the next four days in order to reach his objective. The total distance Bentley needs to ride is 39.6 miles, and he has already ridden 8 miles.

Therefore, he needs to ride an additional (39.6 - 8) = 31.6 miles in the remaining 4 days.

The equation to determine the average number of miles Bentley needs to ride each day is:

31.6/4 = x

Simplifying this equation, we get:

x = 7.9

Therefore, Bentley needs to ride an average of 7.9 miles each day for the next 4 days to meet his goal of riding 39.6 miles in a week.

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Therefore, the 90% confidence interval for Student 1 is (89.61, 105.19). Therefore, the 90% confidence interval for Student 2 is (84.96, 131.24).

To calculate the 90% confidence interval for the mean number of customers served within 5 minutes for each student, we need to use the formula:

CI = X ± (tα/2 * s/√n)

where X is the sample mean, s is the sample standard deviation, n is the sample size, and tα/2 is the critical value from the t-distribution with (n-1) degrees of freedom at the desired confidence level (in this case, 90%).

For Student 1:

X = (102 + 86 + 98 + 109 + 92)/5

= 97.4

s = √([(102-97.4)² + (86-97.4)² + (98-97.4)² + (109-97.4)² + (92-97.4)²]/(5-1))

= 7.94

n = 5

tα/2 = 1.895 (from t-distribution table with 4 degrees of freedom at 90% confidence level)

CI = 97.4 ± (1.895 * 7.94/√5)

= 97.4 ± 7.79

= (89.61, 105.19)

For Student 2:

X = (81 + 165 + 97 + 134 + 92 + 87 + 114)/7

= 108.1

s = √([(81-108.1)² + (165-108.1)² + (97-108.1)² + (134-108.1)² + (92-108.1)² + (87-108.1)² + (114-108.1)²]/(7-1))

= 30.18

n = 7

tα/2 = 1.895 (from t-distribution table with 6 degrees of freedom at 90% confidence level)

CI = 108.1 ± (1.895 * 30.18/√7)

= 108.1 ± 23.14

= (84.96, 131.24)

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There are 19 different ways for Jeff to climb the staircase without stepping on a spider.

What is combinatorics?

Combinatorics is a branch of mathematics that deals with counting and arranging the possible outcomes of different arrangements and selections of objects.

we can use the recurrence relation:

f(n) = f(n-1) + f(n-2)

where f(n) is the number of ways to climb n steps without stepping on a spider. The base cases are f(0) = 1, f(1) = 1, and f(2) = 1.

However, we need to subtract the number of ways that involve stepping on a spider. Let g(n) be the number of ways to climb n steps while stepping on a spider. Then we have:

g(3) = g(9) = 0

g(n) = g(n-1) + g(n-2)   for n > 3, n != 9

We can then use the formula:

ans = f(10) - g(10)

to get the answer.

Using the recurrence relations, we can compute:

f(3) = 1

f(4) = 2

f(5) = 3

f(6) = 4

f(7) = 6

f(8) = 9

f(9) = 13

f(10) = 19

and

g(3) = g(9) = 0

g(4) = 0

g(5) = 0

g(6) = 0

g(7) = 0

g(8) = 0

g(10) = g(9) + g(8) = 0

Therefore, the answer is:

ans = f(10) - g(10) = 19 - 0 = 19

So there are 19 different ways for Jeff to climb the staircase without stepping on a spider.

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The common ratio (r) is 0.2, the series is convergent, and its sum is 2.5.

Given the series: 2 + 0.4 + 0.08 + 0.016 + ...

To find the common ratio (r), we can divide any term by its preceding term. For example:

r = 0.4 / 2 = 0.2

Now that we have the common ratio, we can determine if the series is convergent or divergent. A geometric series is convergent if the absolute value of the common ratio is less than 1 (|r| < 1), and divergent otherwise. Since |0.2| < 1, the series is convergent.

For a convergent geometric series, we can find its sum using the formula:

Sum = a / (1 - r)

where 'a' is the first term of the series. In this case, a = 2, and r = 0.2. So, the sum is:

Sum = 2 / (1 - 0.2) = 2 / 0.8 = 2.5

Therefore, the common ratio (r) is 0.2, the series is convergent, and its sum is 2.5.

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0.2889 is approximately the area to the right of 0.57 under the t-distribution with 17 degrees of freedom.

Using statistical software or a t-distribution table, we can find that the area to the left of 0.57 under the t-distribution with 17 degrees of freedom is approximately 0.7111.

To find the area to the right of 0.57, we need to subtract the area to the left of 0.57 from 1

Area to the right of 0.57 = 1 - 0.7111 = 0.2889

Rounding this to 4 decimal places gives us a final answer of 0.2889. Therefore, 0.2889 is approximately the area to the right of 0.57 under the t-distribution with 17 degrees of freedom.

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No, at 0°F the ticket sales would be -631.25 and it is not reasonable (or possible) to have negative ticket sales in a linear regression model for predicting ticket sales.

In the statistics, the concept of regression analysis is useful for creating a predictive model that predicts the value of a target or dependent variable using all the controlling independent or explanatory variables. Depending on the number of independent variables, regression can be called simple regression or multiple regression. We have a linear regression model that predicts ticket sales for popular water parks.

The regression line equion in this model is written as -631.25 + 11.25 (current temperature in degree F). Comparing above equation with y = a + bx, here, the interaction in the equation above means that hourly ticket sales will be -631.25 when the current temperature (in degrees Fahrenheit) is 0. This does not make sense because hourly ticket sales can be at least 0 but never a negative number. So, it is not reasonable interpretation.

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The area of the resulting triangle is equal to 950 cm².

In Mathematics and Geometry, the area of a triangle can be calculated by using this formula:

Area = 1/2 × b × h

Where:

Since the base area and height were scaled by a factor of 5, the area of the resulting triangle, A₂ can be calculated as follows;

Base area, b = 5b

Height, h = 5h

A₂ = (5b) × (5h)/2

A₂ = 25(b × h/2)

A₂ = 25 × A₁

A₂ = 25 × 38

A₂ = 950 cm²

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The trinomial expression of (x−3)(2x−5) is 2[tex]x^{2}[/tex] − 11x + 15.

To express the product of two binomials (x−3) and (2x−5) as a trinomial, we can use the FOIL method or distributive property.

FOIL stands for First, Outer, Inner, Last. We multiply the First terms in each binomial, then the Outer terms, then the Inner terms, and finally the Last terms. We then add these four products together to get our trinomial.

Using the distributive property, we can multiply each term in the first binomial by each term in the second binomial. This gives us four terms, which we can then simplify by combining like terms to obtain the trinomial.

So, using either method, we get:

(x−3)(2x−5) = x(2x) + x(-5) - 3(2x) - 3(-5)

                  = 2[tex]x^{2}[/tex] -5x -6x + 15

                  = 2[tex]x^{2}[/tex] − 11x + 15

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The product AB is equal to [-7 28], while the product BA = [0 2].

To find AB and BA, we need to multiply the given matrices A and B.

Given,

A = [2 1 5 1]

B = [1 -2 -2 6]

To find AB, we multiply A with B in the order AB.

AB = A x B

= [2 1 5 1] x [1 -2 -2 6]

= [(2 x 1) + (1 x (-2)) + (5 x (-2)) + (1 x 6), (2 x (-2)) + (1 x 1) + (5 x 6) + (1 x (-2))]

= [-7, 28]

Therefore, AB = [-7 28]

To find BA, we multiply B with A in the order BA.

BA = B x A

= [1 -2 -2 6] x [2 1 5 1]

= [(1 x 2) + (-2 x 1) + (-2 x 5) + (6 x 1), (1 x 1) + (-2 x 5) + (-2 x 1) + (6 x 1)]

= [0 2]

Therefore, BA = [0 2] ,

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The probability of rolling an odd number on a standard number cube is 1/2.

The probability of rolling an even number on a standard number cube is 1/2 since there are three even numbers (2, 4, and 6) out of a total of six possible outcomes (1, 2, 3, 4, 5, and 6).

To find the probability of rolling an odd number, we can use the fact that the sum of the probabilities of all possible outcomes is 1. Therefore, the probability of rolling an odd number is:

1 - probability of rolling an even number

= 1 - 1/2

= 1/2

So, the probability of rolling an odd number on a standard number cube is 1/2.

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Answer:

A: y = -4/5x + 3/2 i believe is the correct answer

Step-by-step explanation:

The average value of the function over the given solid is given by Volume = 4/3 and Average value is 3/2.

The average is determined by adding up all the numbers and dividing the total by the total number of figures provided. It represents the midpoint of the supplied data set. The numerical number that may display a lot of facts is the average value.

In plain English, an average is a single number chosen to represent a group of numbers. This average is often the arithmetic mean, which is the total of the numbers divided by the number of numbers in the group. The average of the numbers 2, 3, 4, 7, and 9 (which add up to 25) is, for instance, 5. An average might be another statistic like the median or mode depending on the situation.

f(x, y, z) = x + y + z on over tetrahedron in the first octant with vertices (0, 0, 0), (2, 0, 0), (0, 2, 0) and (0, 0, 2),

The volume is given by,

[tex]V=\int\limits^2_0 {((2-x)^2-\frac{(2-x)^2}{2} )} \, dx[/tex]

V = 4/3

Now average value of f(x,y,z) on solid region Q is given by,

Average value = 1/V ∫∫∫f(x, y, z)dV.

[tex]=\frac{3}{4} \int\limits^2_0 {\frac{x^3}{6} -2x+\frac{8}{3} } \, dx[/tex]

= 3/2.

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In geometry, a locus is a set of points that satisfy a specific set of conditions or criteria. The term locus comes from the Latin word for "place" or "location," and it refers to the idea that a locus is a specific location or region in space that is determined by a particular rule or constraint.

For example, the locus of points equidistant from two fixed points is the perpendicular bisector of the line segment connecting those two points. The locus of points that are a fixed distance from a given point is a circle with that point as its center. The locus of points that satisfy an equation, such as a line or a parabola, is a curve in the plane.

Loci are important in geometry because they can help us understand the properties and relationships of geometric objects. By studying the loci of points that satisfy certain conditions, we can gain insight into the behavior of lines, circles, conic sections, and other geometric figures. Loci also play a key role in many geometry proofs, where we use them to establish important theorems and results.

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There is one specific type of transformation that can cause a change in the period of a tangent or cotangent function, and that is a dilation.

A dilation is a transformation that stretches or compresses a function horizontally or vertically. When a tangent or cotangent function is dilated horizontally, the period of the function changes. The period of a tangent function is π, while the period of a cotangent function is also π.

If the function is dilated by a factor of k, then the new period will be π/k. This means that the function will oscillate faster if it is compressed horizontally (k > 1) and slower if it is stretched horizontally (k < 1). Therefore, it is important to consider the effects of dilations when analyzing the period of a tangent or cotangent function.

The type of transformation that could cause a change in the period of a tangent or cotangent function is called a "horizontal stretch" or "horizontal compression." These transformations affect the frequency of the function by scaling it horizontally, which in turn alters the period of the tangent or cotangent function.

In mathematical terms, the general form of a tangent function is y = A * tan(B(x - C)) + D, and for a cotangent function, it's y = A * cot(B(x - C)) + D. In these expressions, A represents the amplitude, B determines the horizontal stretch or compression, C is the phase shift, and D is the vertical shift.

The factor B directly affects the period of the function. For a tangent or cotangent function, the standard period is π. To find the new period after a horizontal transformation, you can use the formula: new period = (standard period) / |B|. Thus, by changing the value of B, the period of the tangent or cotangent function will be affected accordingly.

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Answer:

[tex]6225.50 {(1 + \frac{.039}{12} )}^{11 \times 12} = 9553.98[/tex]

$9,553.98 - $6,225.50 = $3,328.48

The interest is $3,328.48

The answer is that the expected waiting time until the next service completion is 7.44 minutes.



To calculate the expected waiting time, we need to first find the expected remaining service time for each server. Since the service times are exponentially distributed, the expected remaining service time for each server is equal to the reciprocal of its service rate. The service rate is the inverse of the expected service time.

Thus, the expected remaining service time for the first server is 1/λ1 = 1/0.2 = 5 minutes, where λ1 is the arrival rate for the first server. Similarly, the expected remaining service time for the second and third servers are 1/λ2 = 1/0.0333 = 30 minutes and 1/λ3 = 1/0.1 = 10 minutes, respectively.

Since each server has been busy for 5 minutes with a current customer, the expected remaining service time for each server is reduced by 5 minutes. Thus, the expected remaining service times are 0 minutes, 25 minutes, and 5 minutes, respectively.

The expected waiting time until the next service completion is equal to the sum of the expected remaining service times weighted by the probability that a customer arrives at each server while it is busy. The probability of a customer arriving at each server while it is busy can be calculated using the Erlang C formula.

Using the Erlang C formula, we can calculate that the probability of a customer arriving at the first server while it is busy is 0.016, the probability of a customer arriving at the second server while it is busy is 0.524, and the probability of a customer arriving at the third server while it is busy is 0.091.

Thus, the expected waiting time until the next service completion is (0 minutes)*(0.016) + (25 minutes)*(0.524) + (5 minutes)*(0.091) = 7.44 minutes.

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The value of the coordinate matrix is [tex]\begin{bmatrix} 2&3 &0 \\ 2& 2 & 6\\ 0& 2 &4 \\0 & 0& 2\end{bmatrix}[/tex]

To find the coordinate matrix LFE, we need to express the images of the basis vectors of E in terms of the basis vectors of F. Let's start with e₁(t) = 1, which is a constant polynomial of degree 0. Applying L to this polynomial gives us L(e₁(t)) = 5(0) + 3(0) + 2(1) + 2t(1) = 2 + 2t. We want to express this polynomial as a linear combination of the basis vectors of F, so we write:

2 + 2t = a₁f₁(t) + a₂f₂(t) + a₃f₃(t) + a₄f₄(t)

where a₁, a₂, a₃, and a₄ are unknown coefficients. We can substitute the definitions of the basis vectors of F to obtain:

2 + 2t = a₁ + a₂t + a₃t² + a₄t³.

This is a system of linear equations in the variables a₁, a₂, a₃, and a₄. We can solve this system to obtain the coefficients as follows:

a₁ = 2

a₂ = 2

a₃ = 0

a₄ = 0

Therefore, the coordinate vector of L(e₁(t)) with respect to the basis F is [2, 2, 0, 0]ᵀ. Similarly, we can find the coordinate vectors of L(e₂(t)) and L(e₃(t)):

L(e₂(t)) = 5(0) + 3(1) + 2t(1) + 2t² = 2t² + 2t + 3

⇒ [L(e₂(t))]ₘ = [3, 2, 2, 0]ᵀ

L(e₃(t)) = 5(2) + 3(2t) + 2t²(1) + 2t(t²) = 2t³ + 4t² + 6t

⇒ [L(e₃(t))]ₘ = [0, 6, 4, 2]ᵀ

Finally, we can arrange these coordinate vectors as columns of a matrix to obtain the coordinate matrix LFE:

LFE = [tex]\begin{bmatrix} 2&3 &0 \\ 2& 2 & 6\\ 0& 2 &4 \\0 & 0& 2\end{bmatrix}[/tex]

This is a 4x3 matrix because the range space has dimension 4 and the domain space has dimension 3. Each column of the matrix represents the coordinates of the image of a basis vector of E in terms of the basis vectors of F.

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Complete Question:

Let L: P2 → P3 be the linear transformation given by

L(p(t)) = 5p"(t) + 3p'(t) + 2p(t) + 2tp(t).

Let E = (e₁, e₂, e₃) be the basis of P2 given by e₁(t) = 1, e₂(t) = t, e₃(t) = t². and let F = (f₁, f₂, f₃, f₄) be the basis of P3 given by f₁(t) = 1, f₂(t) = t, f₃(t) = t² , f₄(t) =t³".

Find the coordinate matrix LFE of L relative to the ordered bases E and F.