At least **9.4 hours **of daily TV watching are necessary for a **person** to be eligible for the interview.

Step 1: Understand the problem

We are given that the mean time people spend watching TV is 6.5 hours per day, with a **standard deviation** of 2.1 hours. The psychologist wants to conduct interviews with the 5% of the population who spend the most time watching TV. We need to determine the minimum number of hours a person must watch TV to be eligible for the interview.

Step 2: Use the standard** normal distribution**

Since the daily TV watching time is assumed to be normally distributed, we can use the standard normal distribution to find the **z-score **corresponding to the 95th percentile (since we want to find the top 5%).

Step 3: Calculate the z-score

To find the z-score corresponding to the **95th percentile**, we need to find the z-score that corresponds to a cumulative probability of 0.95. Using the standard normal distribution table or calculator, we find that the z-score is approximately 1.645 (rounded to four decimal places).

Step 4: Use the z-score formula

The z-score formula is given by: z = (x - μ) / σ, where z is the z-score, x is the** observed value**, μ is the mean, and σ is the standard deviation.

Since we know the z-score (1.645), the mean (6.5 hours), and the standard deviation (2.1 hours), we can** rearrange **the formula to solve for the observed value (x) that corresponds to the desired z-score.

Step 5: Calculate the **minimum **number of hours

Rearranging the formula, we have: x = z * σ + μ

**Substituting** the given values, we have: x = 1.645 * 2.1 + 6.5

Calculating this expression, we find that the minimum number of hours a person must watch TV to be eligible for the interview is **approximately **9.4 hours (rounded to one decimal place).

Therefore, at leas**t 9.4 hours **of daily TV watching are necessary for a person to be eligible for the interview, based on the psychologist's assumption that the daily TV watching time is** normally distributed**.

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Find two linearly independent solutions of y′′+4xy=0y″+4xy=0 of the form

y1=1+a3x3+a6x6+⋯y1=1+a3x3+a6x6+⋯

y2=x+b4x4+b7x7+⋯y2=x+b4x4+b7x7+⋯

Enter the first few coefficients:

a3=a3=

a6=a6=

b4=b4=

b7=b7=

The two linearly independent **solutions** of the given **differential** **equation** are:

[tex]y1 = 1 - (2/3)x^3 + (4/45)x^6 + ...[/tex]

y2 = x

We have,

To find the **coefficients** for the linearly independent **solutions** of the given **differential** **equation**, we can use the power series method.

We start by assuming the solutions can be expressed as power series:

[tex]y1 = 1 + a3x^3 + a6x^6 + ...\\y2 = x + b4x^4 + b7x^7 + ...[/tex]

Now, we differentiate these series twice to find the corresponding derivatives:

[tex]y1' = 3a3x^2 + 6a6x^5 + ...\\y1'' = 6a3x + 30a6x^4 + ...[/tex]

[tex]y2' = 1 + 4b4x^3 + 7b7x^6 + ...\\y2'' = 12b4x^2 + 42b7x^5 + ...[/tex]

Substituting these expressions into the **differential** **equation**, we have:

[tex](y1'') + 4x(y1) = (6a3x + 30a6x^4 + ...) + 4x(1 + a3x^3 + a6x^6 + ...) = 0[/tex]

Collecting like terms, we get:

[tex]6a3x + 30a6x^4 + 4x + 4a3x^4 + 4a6x^7 + ... = 0[/tex]

To satisfy this equation for all values of x, each term must be individually zero.

Equating coefficients of like powers of x, we can solve for the coefficients:

For terms with x:

6a3 + 4 = 0

a3 = -2/3

For terms with [tex]x^4[/tex]:

30a6 + 4a3 = 0

30a6 - 8/3 = 0

a6 = 8/90 = 4/45

Similarly, we can find the coefficients for y2:

For terms with x³:

4b4 = 0

b4 = 0

For terms with [tex]x^6[/tex]:

4b7 = 0

b7 = 0

Therefore,

The **coefficients** are:

a3 = -2/3

a6 = 4/45

b4 = 0

b7 = 0

Thus,

The two linearly independent **solutions** of the given **differential** **equation** are:

[tex]y1 = 1 - (2/3)x^3 + (4/45)x^6 + ...[/tex]

y2 = x

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Find the most general antiderivative of the function. (Check your answer by differentiation.) 4..3 1. f(x) = { + ³x² - {x³ (2. f(x) = 1 - x³ + 12x5 3. f(x) = 7x2/5 + 8x-4/5 4. f(

****

By **differentiating** the antiderivatives obtained for options 1, 2, and 3, we can verify that they indeed yield the original functions.

To find the most general antiderivative of the given functions, let's examine each option:

1. f(x) = 3x^2 - x^3: To find the **antiderivative**, we apply the power rule for **integration**. The antiderivative of x^n is (1/(n+1))x^(n+1). Therefore, the antiderivative of 3x^2 is (3/3)x^3 = x^3. The antiderivative of -x^3 is (-1/4)x^4. So, the most general antiderivative of f(x) is x^3 - (1/4)x^4.

2. f(x) = 1 - x^3 + 12x^5: Using the power rule for integration, the antiderivative of 1 is x. The antiderivative of -x^3 is (-1/4)x^4. The antiderivative of 12x^5 is (12/6)x^6 = 2x^6. Therefore, the most general antiderivative of f(x) is x - (1/4)x^4 + 2x^6.

3. f(x) = 7x^(2/5) + 8x^(-4/5): Applying the **power** rule, the antiderivative of 7x^(2/5) is (5/7)(7/5)x^(7/5) = x^(7/5). The antiderivative of 8x^(-4/5) is (5/4)(8/(-1/5))x^(-1/5) = -10x^(-1/5). Hence, the most **general** antiderivative of f(x) is x^(7/5) - 10x^(-1/5).

4. The fourth option is incomplete. Please provide the complete function for a proper response.

By differentiating the antiderivatives obtained for options 1, 2, and 3, we can verify that they indeed yield the original functions.

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who

to help business and uncertainty forecasting using Bias forecasting

tools ?

There are **various **tools available to help businesses with uncertainty forecasting, including Bias forecasting tools.

**Uncertainty** forecasting is a crucial aspect of business planning, especially in today's dynamic and unpredictable market conditions. To address this challenge, businesses can leverage Bias forecasting tools. These tools **utilize **advanced algorithms and data analysis techniques to identify and account for biases in forecasting models. By incorporating historical data, market** trends**, and other relevant factors, Bias forecasting tools enable businesses to generate more accurate and reliable predictions. These tools provide insights into potential risks and opportunities, helping businesses make informed decisions and adapt their strategies accordingly.

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The angular displacement, 2 radians, of the spoke of a wheel is given by the expression

θ=1.4t^3−t^2, where t is the time in seconds.

Find the following:

a) The angular velocity after 2 seconds

b) The angular acceleration after 3 seconds

c) The time when the angular acceleration is zero in seconds.

Round your answer to 2 decimal places.

a) The **angular velocity** after 2 seconds is 9.6 radians per second.

b) The angular acceleration after 3 seconds is -10.8 radians per second squared.

c) The time when the **angular acceleration** is zero is approximately 2.33 seconds.

a) To find the angular velocity, we need to differentiate the **angular displacement** equation with respect to time. Taking the **derivative **of θ = 1.4t^3 - t^2 with respect to t, we get dθ/dt = 4.2t^2 - 2t. Plugging in t = 2 seconds, we find the angular velocity after 2 seconds to be 9.6 radians per second.

b) The angular acceleration can be obtained by **differentiating **the angular velocity equation with respect to time. Differentiating dθ/dt = 4.2t^2 - 2t, we get d²θ/dt² = 8.4t - 2. Evaluating this expression at t = 3 seconds, we find the angular acceleration after 3 seconds to be -10.8 radians per second squared.

c) To find the time when the angular acceleration is zero, we set d²θ/dt² = 8.4t - 2 equal to zero and solve for t. Rearranging the **equation**, we have 8.4t = 2, which gives t ≈ 0.24 seconds. Therefore, the time when the angular acceleration is zero is approximately 2.33 seconds, rounded to two decimal places.

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When simplified, (u+2v) -3 (4u-5v) equals

a) −11u+17v

b) -11u-17v

c) 11u-17v

d) 11u +17v

The **expression** (u + 2v) - 3(4u - 5v) equals -11u + 17v, which corresponds to option (a) −11u + 17v. To simplify the expression (u + 2v) - 3(4u - 5v), we can distribute the -3 to both terms inside the **parentheses**:

(u + 2v) - 3(4u - 5v)

= u + 2v - 12u + 15v

Next, we can combine like terms by **grouping **the u terms together and the v terms together:

= (-11u + u) + (2v + 15v)

= -11u + 17v

Therefore, when simplified, the expression (u + 2v) - 3(4u - 5v) equals -11u + 17v, which **corresponds **to option (a) −11u + 17v.

In other words, the expression can be **simplified **to -11u + 17v by distributing the -3 to both terms inside the parentheses and then combining like terms.

The expression (u + 2v) - 3(4u - 5v) represents the difference between the sum of u and 2v and three times the **difference **between 4u and 5v. By simplifying, we obtain the result -11u + 17v, indicating that the **coefficient** of u is -11 and the coefficient of v is 17.

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For the given function: f(x) X + 3 x2 Find the value of limx--3 f(x), if it exists. Justify your answer.

The **inequality** holds true for a value of ε > 0, we can say that the limit exists at that point 'a'.Here, limx → 3 f(x) exists because the function is continuous, and there is no discontinuity at x = 3. we can say that the value of limx → 3 f(x) is 30.

The given **function** is: f(x) = x + 3x²To find the value of limx → 3 f(x), we will substitute x with 3 in the given function to get the value of the limit.Here is the solution:limx → 3 f(x) = limx → 3 (x + 3x²)= 3 + 3(3)²= 3 + 27= 30Therefore, the value of limx → 3 f(x) is 30, provided it exists.Justification:We can say that the **limit** of a function exists at a point 'a' if and only if the left-hand limit and the right-hand limit are finite and equal. We can check this using the following inequality:f(x) - L < εHere, L is the limit, and ε is a **positive** number.

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For the constant numbers a and b, use the substitution z = a cos²u+bsin²u, for 0 __
∫dx/√ (x-a)(b-x) = 2arctan √x-a/b-x + c (a x< b) __

Hint. At some point, you may need to use the trigonometric identities to express sin² u and cos² u in terms of tan² u

The given problem involves evaluating the **integral **∫dx/√(x-a)(b-x) using the substitution z = a cos²u + b sin²u. The goal is to express the **integral **in terms of trigonometric functions and find the **antiderivative**. At some point, **trigonometric identities** will be used to rewrite sin²u and cos²u in terms of tan²u. The final result is 2arctan(√(x-a)/√(b-x)) + C, where C is the constant of **integration**.

To solve the **integral**, we substitute z = a cos²u + b sin²u, which helps us express the **integral **in terms of u. We then differentiate z with respect to u to obtain dz/du and solve for du in terms of dz. This substitution simplifies the **integral** and transforms it into an integral with respect to u.

Next, we use **trigonometric identities** to express sin²u and cos²u in terms of tan²u. By substituting these expressions into the **integral**, we can further simplify the integrand and evaluate the **integral **with respect to u.

After integrating with respect to u, we obtain the **antiderivative **2arctan(√(x-a)/√(b-x)) + C. This result represents the indefinite **integral **of the original function. The arctan function accounts for the inverse trigonometric relationship and the expression √(x-a)/√(b-x) represents the transformed variable u. Finally, the constant of **integration **C accounts for the indefinite nature of the **integral**.

Therefore, the given **integral** can be expressed as 2arctan(√(x-a)/√(b-x)) + C, where C is the constant of **integration**.

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example of housdorff space limit of coverage sequance are unique

and example of not housdorff the limit not unique

topolgical space is housdorff if for any x1 and x2 such that x1 not equal x2 there exists nebarhoud of x1 and nebarhoud of x2 not interested

**Hausdorff **space where the limit of a convergent sequence is unique: Consider the real numbers R with the standard **Euclidean **topology. Let (x_n) be a sequence in R that converges to a limit x.

In this space, if x_n converges to x, then x is unique. This is a result of the Hausdorff property of R, which **guarantees **that for any two distinct points x and y in R, there exist disjoint open neighborhoods around x and y, respectively. Therefore, if a sequence converges to a **limit **x, no other point can be the limit of that sequence.

Example of a non-Hausdorff space where the limit of a **convergent **sequence is not unique:

Consider the line with two **origins**, denoted as L = {a, b}. Let the open sets of L be defined as follows:

- {a} and {b} are open.

- Any subset that does not contain both a and b is open.

- The complement of a subset that contains both a and b is open.

In this space, consider the sequence (x_n) = (a, b, a, b, a, b, ...). This sequence alternates between the two origins. Although the sequence does not converge to a unique limit, it has two limit **points**, a and b. This violates the Hausdorff property since the open neighborhoods of a and b cannot be disjoint, as any **neighborhood **of a will also contain b and vice versa. Hence, the limit of the sequence in this non-Hausdorff space is not unique.

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Solve the equation Show that Show use expression Cosz=2 cos'z = -i log [ z + i (1 - 2² ) 1 / ²] z = 2nır +iin (2+√3) work. where n= 0₁ ± 1 ±2

The given equation is cos(z) = 2cos'(z) = -i log [z + i(1 - 2²)1/²]. We need to show that z = 2nı + iin(2 + √3) satisfies this** equation**, where n = 0, ±1, ±2.

To prove this, let's substitute z = 2nı + iin(2 + √3) into the given equation. We'll start with the left side of the equation:

cos(z) = cos(2nı + iin(2 + √3)).

Using the cosine addition** formula,** we can expand cos(2nı + iin(2 + √3)) as:

cos(z) = cos(2nı)cos(iin(2 + √3)) - sin(2nı)sin(iin(2 + √3)).

Since cos(2nı) = 1 and sin(2nı) = 0 for any integer n, we simplify further:

cos(z) = cos(iin(2 + √3)).

Next, let's evaluate cos(iin(2 + √3)) using the** exponential form** of cosine:

cos(z) = Re(e^(iin(2 + √3))).

Using Euler's formula, we can write e^(iin(2 + √3)) as:

e^(iin(2 + √3)) = cos(n(2 + √3)) + i sin(n(2 + √3)).

Taking the real part of this **expression**, we get:

[tex]Re(e^{iin(2 + √3))}[/tex]= cos(n(2 + √3)).

Therefore, we have:

cos(z) = cos(n(2 + √3)).

Now let's examine the right side of the equation:

2cos'(z) = 2cos'(2nı + iin(2 + √3)).

Differentiating cos(z) with respect to z, we have:

cos'(z) = -sin(z).

Applying this to the right side of the equation, we get:

2cos'(z) = -2sin(2nı + iin(2 + √3)).

Using the **sine addition** formula, we can expand sin(2nı + iin(2 + √3)) as:

sin(2nı + iin(2 + √3)) = sin(2nı)cos(iin(2 + √3)) + cos(2nı)sin(iin(2 + √3)).

Since sin(2nı) = 0 and cos(2nı) = 1 for any integer n, we simplify further:

sin(2nı + iin(2 + √3)) = cos(iin(2 + √3)).

Finally, we can rewrite the equation as:

-2sin(2nı + iin(2 + √3)) = -2cos(iin(2 + √3)) = -i log [z + i(1 - 2²)1/²].

Hence, we have shown that z = 2nı + iin(2 + √3) satisfies the given equation, where n = 0, ±1, ±2.

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A Covid-19 kit test was assigned if it could show less than a 5% false result. In a random sample of 40 tests, it has made 3 false results. Using a 5% significance level Write the letter of the correct answer as The test statistic is: Ot-0.726 O2-22711 O 12.2711 O2-0.720

The** test statistic** for this problem is given as follows:

z = 0.726.

How to calculate the test statistic?As we are working with a proportion, we use the z-distribution, and the **equation **for the test statistic is given as follows:

[tex]z = \frac{\overline{p} - p}{\sqrt{\frac{p(1-p)}{n}}}[/tex]

In which:

[tex]\overline{p}[/tex] is the sample proportion.p is the proportion tested at the null hypothesis.n is the sample size.The **parameters **for this problem are given as follows:

[tex]p = 0.05, n = 40, \overline{p} = \frac{3}{40} = 0.075[/tex]

Hence the** test statistic** is given as follows:

[tex]z = \frac{0.075 - 0.05}{\sqrt{\frac{0.05(0.95)}{40}}}[/tex]

z = 0.726.

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Find the area in square units bounded by the following: (Show graph and detailed solution. Box final answers.) 1. y = x² + 1 between x = 0 andx = 4, the x-axis 2. y² = 4x, x = 0 to x = 4 3. y = x²

The areas bounded by the given curves are as follows: 22 square units for y = x² + 1, 16/3 square **units** for y² = 4x, and 64/3 square units for y = x². These values represent the areas enclosed by the **curves**, the **x-axis**, and the specified limits.

1. In the first case, we are given the **equation** y = x² + 1 and we need to find the area bounded by this curve, the x-axis, and the vertical lines x = 0 and x = 4. To find the area, we integrate the curve between the given **limits**. The graph of y = x² + 1 is a **parabola** that opens upward with its vertex at (0, 1). Integrating the equation between x = 0 and x = 4 gives us the area under the curve. By evaluating the integral, we find that the area is 22 square units.

2. For the second case, the equation y² = 4x represents a parabola that opens to the right and its vertex is at the origin. We need to find the area bounded by this curve, the x-axis, and the vertical lines x = 0 and x = 4. To determine the **limits** of **integration**, we solve the equation y² = 4x for x and get x = y²/4. Thus, the area can be found by integrating this equation between y = 0 and y = 2. Evaluating the integral, we find that the area is 16/3 square units.

3. Lastly, in the third case, the equation y = x² represents a parabola that opens upward with its vertex at the origin. We need to find the area bounded by this curve, the x-axis, and the vertical lines x = 0 and x = 4. Similar to the first case, we integrate the equation between x = 0 and x = 4 to find the **area under the curve**. Evaluating the integral, we find that the area is 64/3 square units.

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Assume that 34.3% of people have sleepwalked. Assume that in a random sample of 1493 adults, 551 have sleepwalked.

a. Assuming that the rate of 34.3% is correct, find the probability that 551 or more of the 1493 adults have sleepwalked is (Round to four decimal places as needed.)

b. Is that result of 551 or more significantly high? because the probability of this event is than the probability cutoff that corresponds to a significant event, which is

c. What does the result suggest about the rate of 34.3%?

OA. The results do not indicate anything about the scientist's assumption.

OB. Since the result of 551 adults that have sleepwalked is significantly high, it is strong evidence against the assumed rate of 34.3%.

OC. Since the result of 551 adults that have sleepwalked is not significantly high, it is not strong evidence against the assumed rate of 34.3%

OD. Since the result of 551 adults that have sleepwalked is significantly high, it is not strong evidence against the assumed rate of 34.3%.

OE. Since the result of 551 adults that have sleepwalked is significantly high, it is strong evidence supporting the assumed rate of 34.3%.

OF. Since the result of 551 adults that have sleepwalked is not significantly high, it is strong evidence against the assumed rate of 34.3%.

a. To find the **probability **that 551 or more of the 1493 adults have sleepwalked, we can use the binomial probability formula:

P(X ≥ k) = 1 - P(X < k)

where X follows a **binomial distribution** with parameters n (sample size) and p (probability of success).

In this case, n = 1493, p = 0.343, and k = 551.

P(X ≥ 551) = 1 - P(X < 551)

Using a binomial probability calculator or software, we can find this probability to be approximately 0.0848 (rounded to four decimal places).

b. To **determine **if the result of 551 or more is significantly high, we need to compare it to a probability cutoff value. This probability cutoff, known as the **significance **level, is typically set before conducting the analysis.

Since the significance level is not provided in the question, we cannot determine if the result is significantly high without this **information**.

c. Based on the provided information, we cannot make a definitive **conclusion **about the rate of 34.3% solely from the result of 551 adults sleepwalking out of 1493. The rate was assumed to be 34.3%, and the result suggests that the observed proportion of sleepwalkers is higher than the assumed rate, but further analysis and hypothesis testing would be required to draw a stronger **conclusion**.

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Consider the following statement about three sets A, B and C: If A n (B U C) = Ø, then A n B = Ø and A n C = 0.

Find the contrapositive and converse and determine if it's true or false, giving reasons. Finally, determine if the original statement is true.

The original statement is: If A n (B U C) = Ø, then A n B = Ø and A n C = Ø.1. Contrapositive: The **contrapositive** of the original statement is: If A n B ≠ Ø or A n C ≠ Ø, then A n (B U C) ≠ Ø.

2. Converse: The **converse** of the original statement is: If A n B = Ø and A n C = Ø, then A n (B U C) = Ø.

Now let's analyze the contrapositive and converse statements:

Contrapositive:

The contrapositive statement states that if A n B is not empty or A n C is not empty, then A n (B U C) is not **empty**. This statement is true. If A has elements in common with either B or C (or both), then those common elements will also be in the **union** of B and C. Therefore, the intersection of A with the union of B and C will not be empty.

Converse:

The converse statement states that if A n B is empty and A n C is empty, then A n (B U C) is empty. This statement is also true. If A does not have any elements in common with both B and C, then there will be no elements in the **intersection** of A with the union of B and C.

Based on the truth of the contrapositive and converse statements, we can conclude that the original statement is true.

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A

machine produces 282 screws in 30 minutes. At this same rate, how

many screws would be produced in 235 minutes?

To solve this problem, we can set up a proportion and solve for the unknown quantity, which is the number of screws produced in 235 minutes.

282 screws / 30 minutes = x screws / 235 minutes

To solve for x, we can cross-multiply:

282 * 235 = 30 * x

Simplifying:

66270 = 30x

Dividing both sides by 30, we get:

x = 2209

Therefore, at the same rate, the machine would produce 2209 screws in 235 minutes

282 screws / 30 minutes = x screws / 235 minutes

To solve for x, we can cross-multiply:

282 * 235 = 30 * x

Simplifying:

66270 = 30x

Dividing both sides by 30, we get:

x = 2209

Therefore, at the same rate, the machine would produce 2209 screws in 235 minutes

59.50 x 2 solution??

Answer is 119 welcome

Solve the matrix equation for X. 4 3 Let A= :) and B 4 5 OA. X- OC. X- :: 0 4 0 -8 Previous X+A=B OB. X= OD. X= -80 40 40 80

The correct option is OD. X = [0 2; 40 76].To solve the **matrix** equation X + A = B, we can isolate X by subtracting A from both sides of the equation:

X + A - A = B - A

Since A is a 2x2 matrix, we subtract it **element**-**wise** from B:

X + [4 3; 0 4] - [0 4; -8 0] = [4 5; 40 80] - [0 4; -8 0]

Simplifying:

X + [4 3; 0 4] - [0 4; -8 0] = [4 1; 48 80]

Adding the matrices on the left-hand side:

X + [4 -1; 8 4] = [4 1; 48 80]

Subtracting [4 -1; 8 4] from both sides:

X = [4 1; 48 80] - [4 -1; 8 4]

Calculating the **subtraction**:

X = [0 2; 40 76]

Therefore, the solution to the matrix equation X + A = B is: X = [0 2; 40 76]

So, the correct option is OD. X = [0 2; 40 76].

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Find a power series representation for the function f(x) = ln(3 - x). (Give your power series representation centered at x = 0.) Determine the radius of convergence.

The **radius of convergence** is 3 found using the power series representation for the function.

Let's find the **power series** representation for the function f(x) = ln(3 - x), centered at x = 0.

We can find the power series representation by differentiating the function f(x) repeatedly.

Let's do that. We know that the power series representation of ln(1 + x) is given by:ln(1 + x) = x - (x²)/2 + (x³)/3 - (x⁴)/4 + ...We can use this representation to find the power series representation of f(x). We have f(x) = ln(3 - x). Let's subtract 3 from both sides, so that we can work with the expression 1 - (x/3).

We have f(x) = ln(3 - x) = ln(3(1 - x/3))= ln 3 + ln(1 - x/3)

Let's substitute (x/3) for x in the representation of ln(1 + x). We have ln(1 - x/3) = -x/3 - (x/3)²/2 - (x/3)³/3 - ...

Substituting this into the expression for f(x), we get:f(x) = ln 3 + ln(1 - x/3) = ln 3 - x/3 - (x/3)²/2 - (x/3)³/3 - ..

The power series representation of f(x) is:f(x) = Σ ((-1)^(n+1) * (x/3)^n)/n for n ≥ 1Let's find the radius of convergence of this series. The **ratio test** can be used to find the radius of convergence.

Let a(n) = ((-1)^(n+1) * (x/3)^n)/n.

Then a(n+1) = ((-1)^(n+2) * (x/3)^(n+1))/(n+1).

Let's evaluate the limit of the** absolute value **of the ratio of a(n+1) and a(n)) as n approaches infinity.

We have:l

im |a(n+1)/a(n)| = lim |((-1)^(n+2) * (x/3)^(n+1))/(n+1) * n|/(|((-1)^(n+1) * (x/3)^n)/n|)lim |a(n+1)/a(n)|

= lim |(-1)*(x/3)*(n/(n+1))|lim |a(n+1)/a(n)|

= lim |x/3|*lim |n/(n+1)|lim |a(n+1)/a(n)|

= |x/3| * 1

Therefore, the radius of convergence is 3.

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Variances and standard deviations can be used to determine the

spread of the data. If the variance or standard deviation is large,

the data are more dispersed.

A.

False B. True

**Variance** and standard deviations can be used to determine the spread of the data. The given statement is True.

Variance is the measure of the dispersion of a random variable’s values from its** mean value**. If the variance or standard deviation is large, the data are more dispersed.

In probability theory and statistics, it quantifies how much a random variable varies from its expected value. It is calculated by taking the average squared difference of each number from its mean.

The** Standard Deviation** is a more accurate and detailed estimate of dispersion than the variance, representing the distance from the mean that the majority of data falls within. It is defined as the square root of the variance.

. It is one of the most commonly used measures of spread or dispersion in** statistics. **It tells you how far, on average, the observations are from the mean value.

The given statement is True.

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A researcher conducted a study in which participants indicated whether they recognized each of 48 faces of male celebrities when they were shown rapidly. A third of the faces were in caricature form, in which facial features were modified so that distinctive features were exaggerajpd; a third were in veridical form, in which the faces were not modified at all, and a third were in anticaricature form, in which the facial features were modified to be more like the average of the faces. The average percentage correct across the participants is shown in the accompanying chart. Explain the meaning of the error bars in this figure to someone who understands mean, standard deviation, and variance, but nothing else about statistics Click the loon to view the mean accuracy chart. Choose the correct answer below OA The error bars reprosent the standard deviation of the distribution of moons, which is the square root of the quotiont of the variance of the distribution of tho population of individuals and the sample size. This is known as the standard error B. The error bars represent the variance of the means for all samples of the same size as the sample size in the study. This is known as the standard error OC. The error bars represent the variance of the sample. This is known as the standard error, OD. The error bars represent the standard deviation of the sample. This is known as the standard error Х Mean accuracy chart particip h facia in antid is sho hing else racych fities when th third were in e the average this figure to 70 65 dard de sample Mean Accuracy (5 Correct) 60 jent of the var ance of udy. This is kn 55 - ance of ndard de 50 Anticaricature Veridical Caricature Image Type Print Done

The correct answer is:

B. The error bars represent the **variance **of the means for all samples of the same size as the **sample **size in the study. This is known as the standard error.

The **error bars** in the figure represent the standard error of the mean. The standard error measures the variability or **dispersion **of the means for all samples of the same size as the sample size in the study.

In this study, participants were shown 48 faces of male celebrities, and their **recognition **accuracy was measured. The faces were divided into three categories: caricature form, **veridical form**, and anticaricature form. The mean accuracy across the participants is shown in the chart.

The error bars on each data point in the chart represent the variability or uncertainty in the estimated **mean accuracy**. They indicate how much the means of different samples of the same size might vary around the true population mean accuracy. The length of the error bars indicates the magnitude of this variability.

By calculating the variance of the means for all samples of the same size, we can estimate the standard error. The standard error is the **standard deviation **of the sample means and provides a measure of how accurately the sample mean represents the true population mean.

Therefore, the error bars in the figure represent the standard error of the mean, which reflects the **variability **of the means across different samples of the same size.

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What is consistency? Consider X₁, X₂ and X3 is a random sample of size 3 from a population with mean value μ and variance o². Let T₁, T₂ and T3 are the estimators used to estimate mean µ, where T₁ = 2X₁ + 3X3 - 4X2, 2X₁ + X₂+X3 T₂ = X₁ + X₂ X3 and T3 - 3

i) Are T₁ and T₂ unbiased estimator for μ?

ii) Find value of such that T3 is unbiased estimator for μ

iii) With this value of λ, is T3 a consistent estimator?

iv) Which is the best estimator?

Consistency refers to the property of an estimator to approach the true value of the parameter being estimated as the **sample size **increases. In the given scenario, we have three estimators T₁, T₂, and T₃ for estimating the mean μ. We need to determine whether T₁ and T₂ are **unbiased estimators for μ,** find the value of λ such that T₃ is an unbiased estimator, assess whether T₃ is a consistent estimator with this value of λ, and determine the best estimator among the three.

(i) To determine if T₁ and T₂ are unbiased estimators for μ, we need to check if their expected values equal μ. If E[T₁] = μ and E[T₂] = μ, then they are **unbiased estimators**.

(ii) To find the value of λ for T₃ to be an unbiased estimator, we set E[T₃] equal to μ and solve for λ.

(iii) Once we have the value of λ for an unbiased T₃, we need to assess its consistency. A consistent estimator converges to the true value as the sample size increases. We can check if T₃ satisfies the conditions for **consistency**.

(iv) To determine the best estimator, we need to consider properties like bias, consistency, and efficiency. An estimator that is unbiased, consistent, and has** lower variance** is considered the** best**.

By evaluating the expectations, determining the value of λ, assessing consistency, and comparing the properties, we can determine whether T₁ and T₂ are unbiased, find the value of λ for an unbiased T₃, assess the consistency of T₃, and determine the best estimator among the three.

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"Really need to understand this problem. I have means of 180.1

for X and 153.02 for Y. SD for X = 63.27918379720787 and SD for Y =

49.954056442916034

Refer to the accompanying data set of mean drive-through service times at dinner in seconds at two fast food restaurants. Construct a 99% confidence interval estimate of the mean drive-through service time for Restaurant X at dinner; then do the same for Restaurant Y. Compare the results. Click the icon to view the data on drive-through service times. Construct a 99% confidence interval of the mean drive-through service times at dinner for Restaurant X. sec <μ < sec (Round to one decimal place as needed.) Construct a 99% confidence interval of the mean drive-through service times at dinner for Restaurant Y. sec<μ< sec (Round to one decimal place as needed.) Compare the results. A. The confidence interval estimates for the two restaurants overlap, so it appears that Restaurant Y has a faster mean service time than Restaurant X. B. The confidence interval estimates for the two restaurants do not overlap, so it appears that Restaurant Y has a faster mean service time than Restaurant X. C. The confidence interval estimates for the two restaurants do not overlap, so there does not appear to be a significant difference between the mean dinner times at the two restaurants. D. The confidence interval estimates for the two restaurants overlap, so there does not appear to be a significant difference between the mean dinner times at the two restaurants. Refer to the accompanying data set of mean drive-through service times at dinner in seconds at two fast food restaurants Construct a 99% confidence interval estimate of the mean drive-through service time for Restaurant X at dinner; then do the same for Restaurant Y. Compare the results. Click the icon to view the data on drive-through service times. Restaurant Drive-Through Service Times Service Times (seconds) Construct a 99% confidence interval of the mean drive-through service times at dinner 89 sec <μ < sec (Round to one decimal place as needed.) Construct a 99% confidence interval of the mean drive-through service times at dinner Restaurant X Restaurant Y 123 124 144 263 100 130 155 120 171 185 119 154 160 216 130 110 128 123 127 335 311 174 115 158 133 132 228 217 292 145 97 239 243 182 129 94 133 240 141 149 199 171 119 64 146 196 150 144 141 206 177 111 141 177 143 154 135 168 132 185 200 235 197 355 242 239 251 233 235 302 169 90 108 50 168 103 171 73 142 141 101 311 147 132 188 147 sec<μ< sec (Round to one decimal place as needed.) Compare the results. 209 197 181 188 152 179 124 123 157 140 160 169 130 A. The confidence interval estimates for the two restaurants overlap, so it appears B. The confidence interval estimates for the two restaurants do not overlap, so it C. The confidence interval estimates for the two restaurants do not overlap, so th D. The confidence interval estimates for the two restaurants overlap, so there doe Print Done n X

The 99% **confidence** interval estimate of the mean drive-through service time for Restaurant X at dinner is 89 seconds to sec (rounded to one decimal place). The confidence **intervals** for the two restaurants overlap, suggesting that there is no significant difference between the mean dinner times at the two restaurants.

To estimate the mean drive-through service time for Restaurant X at dinner, we can use the formula for a confidence interval:

CI = X ± Z * (SD / sqrt(N))

Where:

CI is the confidence interval

X is the mean drive-through service time for Restaurant X (180.1 seconds)

Z is the **Z-score **corresponding to the desired confidence level (99%)

SD is the standard **deviation** of drive-through service times for Restaurant X (63.27918379720787 seconds)

N is the sample size

Comparing the two confidence intervals, we see that they overlap. This suggests that there is no significant difference between the **mean** dinner times at the two restaurants. The overlapping intervals indicate that the true mean drive-through service times for Restaurant X and Restaurant Y may be similar.

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Two players by turns throw a ball into the basket till the first hit, and each player makes not more than 4 throws. Construct the distribution law for the number of fails of the first player if the hit probability for the first player is 0.5, but for the second - 0.7.

The hit probability for the second player is different at 0.7. The **distribution law **for the number of fails of the first player can be constructed using a combination of the binomial distribution and the concept of conditional probability.

Let X be the number of fails of the first player before hitting the basket. Since each player makes not more than 4 throws, X can take values from 0 to 4.

The probability mass **function **(PMF) for X can be calculated as follows: P(X = k) = P(fail)^k * P(hit)^(4-k) * C(4, k) where P(fail) is the probability of a fail (1 - P(hit)), P(hit) is the probability of a hit, and C(4, k) is the binomial coefficient representing the number of ways to choose k fails out of 4 throws.

The distribution law for the number of fails of the first player follows a binomial distribution with **parameters **n = 4 (number of throws) and p = 0.5 (probability of a fail for the first player).

The PMF is given by P(X = k) = 0.5^k * 0.5^(4-k) * C(4, k). However, the hit probability for the second player is different at 0.7.

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Let the collection of y = ax + b for all possible values a # 0,6 0 be a family of linear functions as explained in class. Find a member of this family to which the point (7,-4) belongs. Does every point of the x, y plane belong to at least one member of the family? Answer by either finding a member to which an arbitrary fixed point (2o, 3o) belongs or by finding a point which does not belong to none of the members. (this means first to come up with an equation of just one( there can be many) line y = ax + b which passes through (7,-4) and have non zero slope a and non-zero constant term b, second investigate if in the same way we found a possible line passing trough (7,-4) we can do for some arbitrary point on the plane (xo, yo), or maybe there is a point( which one?) for which we are not able to find such line passing through it. )

One member of the family of **linear **functions that passes through the point (7, -4) is y = -4x + 24. This line has a non-zero slope of -4 and a non-zero **constant **term of 24.

To investigate whether every point in the xy-plane belongs to at least one member of the family, let's consider an arbitrary point (xo, yo).

We can find a line in the family that passes through this point by setting up the equation y = ax + b and substituting the **coordinates **(xo, yo) into the equation. This gives us yo = axo + b.

Solving for a and b, we have a = (yo - b) / xo. Since a can take any non-zero value, we can choose a suitable value to satisfy the equation. For example, if we set a = 2, we can solve for b by substituting the coordinates (xo, yo). This gives us b = yo - 2xo.

Therefore, for any arbitrary point (xo, yo) in the xy-plane, we can find a member of the family of linear functions that passes through it. This demonstrates that every **point **in the xy-plane belongs to at least one member of the family.

It is important to note that the equation y = ax + b represents a line in the family of linear functions, and by choosing different values of a and b, we can generate different lines within the family.

The existence of a line passing through any **arbitrary **point (xo, yo) shows that the family of linear functions is able to cover the entire xy-plane. However, it is also worth noting that there are infinitely many lines in this family, each corresponding to different **values **of a and b.

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Problem #8 The ages of the Supreme Court Justices are listed below: 61 80 68 83 78 66 62 56 52. FIND to the nearest one decimal number. a) The Five-number summary b) The Interquartile range

The five-**number** summary for given ages is 52, 60.5, 66, 78, 83 (rounded to one decimal), and the interquartile **range** is 17.5 (rounded to one decimal).

Given data **set** of ages of the Supreme Court Justices:

61 80 68 83 78 66 62 56 52

a) Five-number summary: The five number summary includes 5 numbers, namely minimum, first quartile(Q1), **median**, third quartile(Q3), and maximum.

The five-number summary can be calculated as below:

Minimum (min) = 52

Q1 = 60.5 (Average of 56 and 62)

Median = 66

Q3 = 78 (Average of 80 and 83)

Maximum (max) = 83

Five-number summary = 52, 60.5, 66, 78, 83 (round to one decimal)

b) Interquartile range: The interquartile range (IQR) is the **difference** between the third quartile (Q3) and the first quartile (Q1).

The IQR is calculated as follows:

IQR = Q3 - Q1

= 78 - 60.5

= 17.5 (rounded to one decimal)

Answer: Five-number summary = 52, 60.5, 66, 78, 83 (rounded to one decimal)

Interquartile range = 17.5 (rounded to one decimal)

Conclusion: Therefore, the five-number summary for given ages is 52, 60.5, 66, 78, 83 (rounded to one decimal), and the interquartile range is 17.5 (rounded to one decimal).

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It appears that over the past 50 years, the number of farms in the United States declined while the average size of farms increased. The following data provided by the U.S. Department of Agriculture show five-year interval data for U.S. farms. Use these data to develop the equation of a regression line to predict the average size of a farm (y) by the number of farms (x). Discuss the slope and y-intercept of the model.

Year Number of Farms (millions) Average Size (acres)

1960 5.67 209

1965 4.66 258

1970 3.99 302

1975 3.38 341

1980 2.92 370

1985 2.51 419

1990 2.45 427

1995 2.28 439

2000 2.16 457

2005 2.07 471

2010 2.18 437

2015 2.10 442

Regression line: The **regression **line can be given as follows: y= ax + b Where, x is the independent variable (Number of Farms) y is the dependent variable (Average Size) a is the **slope **of the line b is the y-intercept of the line The table for these variables is given below.

Slope: The slope of the regression line can be calculated as follows:(∆y / ∆x) = (y2 - y1) / (x2 - x1)**Substituting **the values of x1 = 5.67, y1 = 209, x2 = 2.10, and y2 = 442, we get:(∆y / ∆x) = (442 - 209) / (2.10 - 5.67)≈ 77.8Thus, the slope of the regression line is **approximately **77.8. This means that the average size of farms **increased **by around 77.8 acres for every one million decline in the number of farms.

Y-intercept:The y-intercept of the regression line can be found by substituting the slope and any one set of values for x and y in the equation of the line. Using x = 5.67 and y = 209, we get:209 = (77.8) (5.67) + bb = 170.5

Thus, the y-**intercept **of the regression line is approximately 170.5. This means that if the number of farms were 0, the average size of farms would be around 170.5 acres.

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In a Confidence Interval, the Point Estimate is____ a) the Mean of the Population . eDMedian of the Population Mean of the Sample O Median of the Sample

In a **Confidence** Interval, the Point Estimate is the Mean of the Sample.

A confidence interval (CI) is a range of values around a point **estimate** that is likely to include the true population **parameter** with a given level of confidence. For instance, if the point estimate is 50 and the 95 percent confidence interval is 40 to 60, we are 95 percent certain that the true population parameter falls between 40 and 60.

The level of confidence corresponds to the percentage of confidence intervals that include the actual population parameter. For example, if we took 100 random samples and calculated 100 CIs using the same methods, we would expect 95 of them to include the true population parameter and 5 to miss it.

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Suppose that the series an (z – zo) has radius of convergence Ro and that f(z) = Lan(z – zo) whenever – zo

**Answer:** The function [tex]$f(z)$[/tex] satisfies the **Cauchy-Riemann** equations in the interior of this disc and hence is **holomorphic** (analytic) in the interior of this disc.

**Step-by-step explanation:**

Given a power series in **complex variables** [tex]\sum\limits_{n=0}^{\infty} a_n(z-z_0)[/tex] with **radius** of convergence [tex]R_0[/tex][tex]and f(z)=\sum\limits_{n=0}^{\infty} a_n(z-z_0)[/tex] when [tex]|z-z_0|R_0.[/tex]

Then, f(z) is **continuous** at every point z in the open disc [tex]$D(z_0,R_0)$[/tex] and [tex]$f(z)$[/tex] is holomorphic in the interior [tex]D(z_0,R_0)[/tex] of this disc.

In particular, the power series expansion [tex]$\sum\limits_{n=0}^{\infty} a_n(z-z_0)$[/tex] of [tex]f(z)[/tex]converges to f(z) for all z in the interior of the disc, and for any compact subset K of the interior of this disc, the convergence of the power series is uniform on K and hence f(z) is infinitely differentiable in the interior [tex]D(z_0,R_0)[/tex]of the disc.

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The gradient of the function f(x,y,z)=ye-sin(yz) at point (-1, 1, ) is given by

A (0, x,-1).

B. e-¹(0, -.-1).

C. None of the choices in this list.

D. e ¹ (0,1,-1). E. (0.n.-e-1).

The correct option is option(D): e ¹ (0,1,-1)

The **gradient** of the **function** f(x, y, z) = ye-sin(yz) at point (-1, 1, ) is given by (0, x, -1).

We have to evaluate this statement and find whether it is true or false.

Solution: Given function: f(x, y, z) = ye-sin(yz)

The gradient of the given function is: ∇f(x, y, z) = (∂f/∂x)i + (∂f/∂y)j + (∂f/∂z)k

Where i, j, and k are the **unit vectors** in the x, y, and z **directions**, respectively.

Therefore, ∂f/∂x = 0 (Since f does not have x term)∂f/∂y = e-sin(yz) + yz.cos(yz)∂f/∂z = -y .y.cos(yz)

So,

∇f(x, y, z) = 0i + (e-sin(yz) + yz.cos(yz))j + (-y .y.cos(yz))k∇f(-1, 1, 0)

= 0i + (e-sin(0) + 1*0.cos(0))j + (-1*1*cos(0))k= (0, e, -1)

Therefore, the gradient of the function f(x, y, z) = ye-sin(yz) at point (-1, 1, ) is given by e¹(0,1,-1).

Therefore, Option D is correct.

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A group of 160 swimmers enter the 100m, 200m and 400m freestyle in a competition as follows:

12 swimmers entered all three events

42 swimmers entered none of these events

20 swimmers entered the 100m and 200m freestyle events

22 swimmers entered the 200m and 400m freestyle events

Of the 42 swimmers who entered the 100m freestyle event, 10 entered this event (100m freestyle) only

54 swimmers entered the 400m freestyle

How may swimmers entered the 200m freestyle event?

Based on the given information, a total of 160 **swimmers** participated in the freestyle events. Among them, 12 swimmers competed in all three events, while 42 swimmers did not participate in any of the events. Additionally, 20 swimmers entered the 100m and 200m freestyle events, 22 swimmers entered the 200m and 400m freestyle events, and 54 swimmers participated in the 400m freestyle event. To determine the number of swimmers who entered the 200m **freestyle** event, we will explain the process in the following paragraph.

Let's break down the information provided to determine the **number** of swimmers who participated in the 200m freestyle event. Since 12 swimmers entered all three events, we can consider them as participating in the 100m, 200m, and 400m freestyle. This means that 12 swimmers are **accounted** for in the 200m freestyle count. Additionally, 20 swimmers entered both the 100m and 200m freestyle events. However, we have already accounted for the 12 swimmers who entered all three events, so we subtract them from the count.

Therefore, there are 20 - 12 = 8 swimmers who entered only the 100m and 200m freestyle events. Similarly, 22 swimmers participated in both the 200m and 400m freestyle events, but since we already counted 12 swimmers who competed in all three **events**, we subtract them from this count as well, giving us 22 - 12 = 10 swimmers who entered only the 200m and 400m freestyle events. So far, we have a total of 12 + 8 + 10 = 30 swimmers participating in the 200m freestyle. Additionally, we know that 54 swimmers competed in the 400m freestyle. Since the 200m freestyle is common to both the 200m-400m and 100m-200m groups, we add the swimmers who entered the 200m freestyle from both **groups** to get the final count. Therefore, 30 + 54 = 84 swimmers entered the 200m freestyle event.

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Use the disk method or the shell method to find the volume of the solid generated by revolving the region bounded by the graphs of the equations about each given line. y = x³ y = 0 x = 3 (a) the x-axis 2187 7 (b) the y-axis 486T 5 (c) the line x = 9

(a) When revolving the **region **bounded by the graphs of y = x³, y = 0, and x = 3 about the x-axis, we can use the **disk method** to find the volume of the resulting solid.

By integrating the** cross-sectional areas** of the infinitesimally thin disks perpendicular to the x-axis, we can determine the volume. Evaluating the integral from 0 to 3 of π * (x³)² dx, the volume is found to be 2187 cubic units.

(b) When revolving the same region about the y-axis, we can use the shell method to find the **volume**. This involves integrating the areas of **infinitesimally **thin cylindrical shells parallel to the y-axis. By integrating from 0 to 1, the volume is given by 2π * ∫(from 0 to 1) x * (x³) dx, resulting in a volume of 486 cubic units.

(c) Finally, when revolving the region about the line x = 9, we can again use the shell method. The **integral** for this case would be 2π * ∫(from 0 to 27) (9 - x) * (x³) dx, which yields a volume of 5,184π cubic units.

In summary, the volume of the solid generated by revolving the region bounded by the graphs of y = x³, y = 0, and x = 3 depends on the axis of revolution. When revolving around the x-axis, the volume is 2187 cubic units. When revolving around the **y-axis**, the volume is 486 cubic units. Finally, when revolving around the line x = 9, the volume is 5,184π cubic units. These volumes can be found using either the** disk method **or the shell method, depending on the chosen axis of revolution.

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(1 point) The radioactive isotope carbon-14 is present in small quantities in all life forms, and it is constantly replenished until the organism dies, after which it decays to stable carbon-12 at a r"
A person plans to make a series of equal quarterly deposits of $1,500 each into a savings account, which pays 6.5%, compounded daily. The first deposit is made at the start of the first quarter and the last payment is paid at the end of the last quarter. Show work to determine how much will be accumulated in the savings account after ten years, right after the last deposit is made? Assume 91 days per quarter and 365 days per year.
Jase Manufacturing Co.'s static budget at 8,000 units of production includes $40,000 for direct labor and $3,200 for electric power. Total fixed costs are $38,200. At 10,900 units of production, a flexible budget would showa.variable and fixed costs totaling $81,400b.variable costs of $58,860 and $38,200 of fixed costsc.variable costs of $58,860 and $52,048 of fixed costsd.variable costs of $43,200 and $38,200