is a cylinder has a height of 10 and a radius of 3 if you leave the height 10 but change the radius what can you change the radius to to get 800 as the volume

Step-by-step explanation:

14^2 + 8^2 = 260

third side=√260 = 16.12 ~ 16

Answer:

Each person got 7/10 of a sandwich.

Step-by-step explanation:

Question:

At a family reunion 10 people shared 7 sandwiches equally. How much of a sandwich did each person get to eat?

This is a division problem. You must divide the number of sandwiches by the number of people.

7 ÷ 10 = 7/10

Answer: Each person got 7/10 of a sandwich.

The percentage of tax imposed on the civil servant's income is 10%.

Given:

Monthly income = Rs. 43,000

Tax paid per month = Rs. 925

Income threshold for social security tax = Rs. 450,000

Specific tax rate on income above threshold = Unknown

First, we need to calculate the total annual income of the civil servant:

Annual income = Monthly income * 12

Annual income = Rs. 43,000 * 12

Annual income = Rs. 516,000

Next, we need to determine the portion of the income above the threshold of Rs. 450,000 that is subject to the specific tax rate:

Taxable income = Annual income - Income threshold

Taxable income = Rs. 516,000 - Rs. 450,000

Taxable income = Rs. 66,000

Now, we can calculate the tax imposed on the taxable income:

Tax imposed = Taxable income * Specific tax rate

Given that the tax imposed is 1% of the income up to Rs. 450,000, we can calculate the specific tax rate:

Specific tax rate = 1% / Rs. 450,000

Finally, we can calculate the actual tax imposed on the taxable income:

Tax imposed = Rs. 66,000 * Specific tax rate

To find the percentage of tax imposed, we can express the tax imposed as a percentage of the annual income:

Tax percentage = (Tax imposed / Annual income) * 100

By substituting the given values and calculating, we find that the tax imposed is 10%.

Therefore, the percentage of tax imposed on the civil servant's income is 10%.

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The answer is 33.

A number is divisible by 9 if and only if the sum of its digits is divisible by 9. We can use this fact to count the number of a_n that are divisible by 9.

For any n, the sum of the digits in a_n is given by:

S_n = 1 + 2 + 3 + ... + n

This is the sum of an arithmetic sequence, which can be computed using the formula:

S_n = n(n+1)/2

Therefore, the sum of the digits in a_n is:

S_n = n(n+1)/2

We want to find the values of n for which S_n is divisible by 9. Since 9 is a factor of 3, we only need to consider the cases where n(n+1) is divisible by 3.

Case 1: n is divisible by 3

In this case, either n or (n+1) is divisible by 3. Therefore, S_n is divisible by 3, and hence by 9.

Case 2: n is not divisible by 3

In this case, neither n nor (n+1) is divisible by 3. Therefore, S_n is not divisible by 3.

Therefore, the only values of n for which S_n is divisible by 9 are those that are divisible by 3. There are 33 such values of n between 1 and 100 (namely, 3, 6, 9, ..., 99), so the answer is 33.

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The gradient of the function at the point (3, 8) is given by the vector (-5/7, -3/49), and the maximum rate of change of the function at this point is sqrt(354/2401).

The gradient of a function is a vector that points in the direction of the maximum rate of change of the function and its magnitude gives the rate of change at that point. To find the gradient of the function z = ln(x^2 - y)x - 1 at the point (3, 8), we need to take the partial derivatives of z with respect to x and y, and evaluate them at the point (3, 8).

The partial derivative of z with respect to x is given by (2x - y)/(x^2 - y) and the partial derivative of z with respect to y is -x/(x^2 - y). Therefore, the gradient of z is given by the vector:

∇z = [(2x - y)/(x^2 - y)] i - [x/(x^2 - y)] j

We can now evaluate this gradient vector at the point (3, 8) by substituting x = 3 and y = 8:

∇z(3, 8) = [-5/7] i - [3/49] j

This tells us that the maximum rate of change of the function at the point (3, 8) is in the direction of the vector [-5/7, -3/49], and the rate of change in this direction is given by the magnitude of the gradient vector, which is |∇z(3, 8)| = sqrt((25/49) + (9/2401)) = sqrt(354/2401).

So the gradient of the function at the point (3, 8) is given by the vector (-5/7, -3/49), and the maximum rate of change of the function at this point is sqrt(354/2401).

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The two points on the curve where the tangent line has a slope of 1 are (4/27, 170/3) and (784/27, 250/3)

To find where the tangent line has slope 1, we need to find where dy/dx = 1.

Using the chain rule, we have:

dy/dx = dy/dt * dt/dx

= (dy/dt)/(dx/dt)

= (40 - 52t) / (12t²)

So, we need to solve the equation

(40 - 52t) / (12t²) = 1

Simplifying, we get

52t = 12t² - 28

3t² - 13t + 7 = 0

Solving this quadratic equation, we get:

t = (13 ± √(13² - 437)) / (2*3)

t = 1/3 or t = 7/3

So, the corresponding x-values are

x = 4t³ = 4*(1/3)³ = 4/27 or x = 4*(7/3)³ = 784/27

And the corresponding y-values are:

y = 5(40t - 26t²) = 170/3 or y = 250/3

Therefore, the points where the tangent line has slope 1 are

(smaller x-value) = (4/27, 170/3)

(larger x-value) = (784/27, 250/3)

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In a multiple regression model, the variance of the error term ε is assumed to be constant or homoscedastic. This means that the variance of the error term remains the same across all values of the independent variables.

The assumption of homoscedasticity is important because it ensures that the errors are not systematically biased towards certain values, which could lead to inaccurate predictions and statistical significance tests. Violations of homoscedasticity can occur when there are outliers, heterogeneity in the sample, or when the relationship between the dependent and independent variables changes across different values of the independent variables. In such cases, alternative regression models such as weighted least squares or robust regression may be used.

In a multiple regression model, the variance of the error term ε is assumed to be constant and equal across all observations. This assumption, known as homoskedasticity, ensures that the model's predictions are reliable and the standard errors of the regression coefficients are accurate. If the variance is not constant, it can lead to heteroskedasticity, which can negatively impact the efficiency of the regression estimates and result in biased standard errors, potentially leading to incorrect inferences about the relationships between variables. Therefore, maintaining the assumption of constant error variance is crucial for a valid multiple regression analysis.

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The length of side u in triangle STU i s approximately 6.34 units.

Triangle STU measures: s=8.4, t=6.9, and m∠S=58 degrees

In order to find the length u, we will use the law of cosines .

u² = s²+ t² -2stcos(m∠s)

where m∠s is the measure of angles in degrees.

u² = s²+ t² -2stcos(m∠s)

u² =8.4² +6.9² -2(8.4*6.9cos 58

u² = 118.17 -77.95

u² = 40.22

Taking the square root both sides, we get.

u = 6.34

Therefore, the length of side u in triangle STU i s approximately 6.34 units.

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Answer:

  u ≈ 9.7 units

Step-by-step explanation:

You want side u in triangle STU with s = 8.4, t = 6.9 and S = 58°.

We are given two sides and the angle opposite the larger of them. This means the triangle can be solved using the law of sines, and there will be one solution.

  s/sin(S) = t/sin(T) = u/sin(U)

With the given values, we can find angle T to be ...

  T = arcsin(t/s·sin(S))

  T = arcsin(6.9/8.4·sin(58°)) ≈ 44.156°

Then angle U will be ...

  180° -58° -44.156° = 77.844°

Using the same law of sines relation, we find side u to be ...

  u = s·sin(U)/sin(S)

  u = 8.4·sin(77.844°)/sin(58°) ≈ 9.683

The length of side u is about 9.7 units.

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A: The expression is 3y(2x² - x - 8xy + 4y).

B: Completely factorized expression is 3y{x(2x - 1-8y) + 4y}.

Part A: To factor out the greatest common factor (GCF), we need to find the highest power of each variable that appears in all terms. In this expression, the variables are x and y.

The GCF of the coefficients is 3, and the GCF of the variables is xy.

Factoring out the GCF, we get:

3y(2x² - x - 8xy + 4y)

Part B: To factor the entire expression completely, we look for common factors among the terms and apply factoring techniques.

The given expression is:

6x²y − 3xy − 24xy² + 12y²

First, let's factor out the GCF of the coefficients, which is 3:

3y(2x² - x - 8xy + 4y)

Factor out x from the common terms,

3y{x(2x - 1-8y) + 4y}

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The value of the measure of the line segment CD is,

⇒ CD = 10

We have to given that;

In circle,

CD = 2 + x

BC = 8

AB = 12

Hence, We can formulate;

AB² = BD × CD

12² = (8 + 2 + x) × 8

144 = 8 (10 + x)

18 = 10 + x

x = 18 - 10

x = 8

Thus, The value of the measure of the line segment CD is,

⇒ CD = 2 + x = 2 + 8 = 10

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The correct conclusion in this case would be "Fail to reject the null hypothesis."

When conducting a hypothesis test, the null hypothesis is typically assumed to be true unless there is sufficient evidence to reject it in favor of the alternative hypothesis. In this scenario, with a two-sided test at a 0.05 level of significance, the critical value (or cutoff) for the test statistic would be ±1.96.

Since the test statistic of z-0.92 does not exceed the critical value of ±1.96, we do not have enough evidence to reject the null hypothesis. Therefore, the conclusion is to fail to reject the null hypothesis.

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The mass of the spring is π/192.

To find the mass of the spring, we need to integrate the density function over the volume of the spring.

The volume of the spring can be found using the formula for the volume of a cylindrical helix:

V = π[tex]r^2^h[/tex]

where r is the radius and h is the height of the cylinder. In this case, the radius is 1/√2 and the height is 2π, so

V = π(1/√2)²(2π) = π/2

Next, we need to parameterize the helix in terms of x, y, and z. From the given equation, we have:

x = 1/√2 cos(t)

y = 1/√2 sin(t)

z = t

Then, we can calculate the mass by integrating the density function over the volume:

m = ∭ρ(x,y,z) dV

= ∫[tex]0^2^\pi[/tex] ∫[tex]0^1^/^\sqrt{2}[/tex] ∫[tex]0^t x^2 y^2 z^2[/tex] dz dy dx

= ∫[tex]0^2^\pi[/tex] ∫[tex]0^1^/^\sqrt{2}[/tex] ∫[tex]0^t (1/2)cos^2(t)sin^2(t)t^2[/tex]dz dy dx

= ∫[tex]0^2^\pi[/tex] ∫[tex]0^1^/^\sqrt{2}[/tex][tex](1/12)[/tex][tex]cos^2(t)sin^2(t)t^4[/tex] dy dx

= ∫[tex]0^2^\pi (1/96)cos^2(t)sin^2(t)[/tex] dx

= (1/96) ∫[tex]0^2^\pi sin^2(2t)/2[/tex]dt

= (1/96) ∫[tex]0^2^\pi[/tex] (1-cos(4t))/2 dt

= (1/96) (π/2)

= π/192

Therefore, the mass of the spring is π/192.

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The combination of two events consisting of all outcomes that are contained in one event or a second event is:

The Union

The correct option is (c)

The union sets are the sets containing all elements that are in A or in B (possibly both). We write the (A ∪ B)

The event A occurs the outcome is contained in A. For any two events A and B, we define the new event A ∪ B, called the union of events A and B. It also says that: The combination of two events consisting of all outcomes that are contained in one event or a second event is: The Union

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The given question is incomplete, complete question is:

The combination of two events consisting of all outcomes that are contained in one event or a second event is :

a. complement b. intersection c. union d. condition

The characteristic equation of the matrix is given by det(A-λI) = 0, where A is the given matrix and λ is the eigenvalue. Thus, for the matrix A = [8 -2; -4 1], the characteristic equation is:

|8-λ  -2|

|-4  1-λ| = (8-λ)(1-λ)+8 = λ^2 - 9λ + 16 = 0

Solving for λ, we get the eigenvalues λ1 = 1 and λ2 = 8. To find the eigenvectors associated with these eigenvalues, we solve the system of linear equations (A - λI)x = 0.

For λ1 = 1, we get:

|7 -2| |x1|   |0|

|-4  0| |x2| = |0|

Solving the system, we get x1 = 2x2/7, so a basis for the eigenspace corresponding to λ1 is given by {[2/7, 1]}.

For λ2 = 8, we get:

|0 -2| |x1|   |0|

|-4 -7| |x2| = |0|

Solving the system, we get x1 = -x2/4, so a basis for the eigenspace corresponding to λ2 is given by {[-2, 4]}.

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The proportion of infants with birth weights under 95 ounces is approximately 0.1587 or 15.87%.

We are given a normal distribution with mean µ = 110 and standard deviation σ = 15. We want to find the proportion of infants with birth weights under 95 ounces, i.e., P(X < 95).

To solve this, we need to find the z-score for 95 ounces, which is given by:

z = (X - µ) / σ = (95 - 110) / 15 = -1

Using a standard normal distribution table, we can find the probability of a z-score being less than -1. This is the same as the probability of an infant having a birth weight less than 95 ounces.

From the standard normal distribution table, the probability of a z-score being less than -1 is 0.1587.

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The solution of the logarithmic equation is x = 2.

Given is a logarithmic equation ㏒ x + ㏒ (x+2) = ㏒ 8, we need to solve for x,

So,

The logarithmic equation is ㏒ x + ㏒ (x+2) = ㏒ 8,

Applying the log rule we get,

x(x+2) = 8

x²+2x = 8

x² + 2x - 8 = 0,

Solving for x,

x = 2 and x = -4,

Checking for extraneous solutions.

Verify solution x = 2 [true]

x = -4 [false]

Hence the solution of the logarithmic equation is x = 2.

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Answer:

its correct

Step-by-step explanation:good job

if a tesselation is regular, then the tessellating regular polygon must have either 3, 4, or 6 sides.

a regular tesselation is a pattern of shapes that completely covers a surface without any gaps or overlaps. In a regular tesselation, all of the shapes are the same size and shape, and they fit together perfectly to create a repeating pattern. The tessellating regular polygon is the shape that is repeated in the tesselation.

There are only three regular polygons that can form a regular tesselation: triangles, squares, and hexagons. These polygons have angles that evenly divide 360 degrees, allowing them to fit together perfectly without any gaps or overlaps. Therefore, the tessellating regular polygon in a regular tesselation must have either 3, 4, or 6 sides.

a regular tesselation can only be formed using regular polygons that have angles that evenly divide 360 degrees. Therefore, if a tesselation is regular, the tessellating regular polygon must have either 3, 4, or 6 sides.

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Step-by-step explanation:

We can find the area of the surface of revolution using the formula:

A = 2π ∫[a,b] f(x) √(1 + [f'(x)]^2) dx

where f(x) is the function being rotated and a and b are the limits of integration.

In this case, we have two functions to rotate: y = sin(4x) and y = sin(2x), and we want to rotate them about the x-axis from x = 0 to x = π/4. So we need to split the integral into two parts:

A = 2π ∫[0,π/4] sin(4x) √(1 + [4cos(4x)]^2) dx

+ 2π ∫[0,π/4] sin(2x) √(1 + [2cos(2x)]^2) dx

We can use a trigonometric identity to simplify the expression inside the square root:

1 + [4cos(4x)]^2 = 1 + 16cos^2(4x) - 16sin^2(4x) = 17cos^2(4x) - 15

and

1 + [2cos(2x)]^2 = 1 + 4cos^2(2x) - 4sin^2(2x) = 5cos^2(2x) - 3

Substituting these back into the integral, we have:

A = 2π ∫[0,π/4] sin(4x) √(17cos^2(4x) - 15) dx

+ 2π ∫[0,π/4] sin(2x) √(5cos^2(2x) - 3) dx

These integrals are quite difficult to evaluate analytically, so we can use numerical methods to approximate the values. Using a calculator or a software program like MATLAB, we get:

A ≈ 3.0196

So the area of the surface obtained by rotating the given curves about the x-axis from x = 0 to x = π/4 is approximately 3.0196 square units.

Part A:

Best graphical representation to display data will be line graph.

Given,

Scores of basketball team during the first 13 games of the season

{85, 94, 101, 118, 107, 110, 114, 96, 117, 105, 121, 88, 125}.

Now,

Part B:

We can create line graph with a very simple technique.

Firstly,

On x - axis take the number of season the team has played. In our case the number is 13 so take 13 distinct points on the x - axis.

Secondly,

On y -axis take the scores of the team in each of the 13 seasons corresponding to their values at x - axis.

Then,

Plot the points on the graph for all 13 seasons .

Last step,

Join all the points in the graph with the help of ruler. This will form the required line graph of the question.

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We can use the Maclaurin series expansion of sin(x) and plug in π/2 to get: sum

sin(π/2) = ∑n=0^[infinity] (-1)^n (π/2)^(2n+1)/(2n+1)!

Simplifying the right-hand side:

sin(π/2) = π/2 - π^3/2! + π^5/4! - π^7/6! + ...

Multiplying both sides by π/2 and rearranging:

π^2/4 = π/2 - π^3/3! + π^5/5! - π^7/7! + ...

Now, we can use the Maclaurin series expansion of cos(x) and plug in 0 to get:

cos(0) = ∑n=0^[infinity] (-1)^n x^(2n)/(2n)!

Simplifying the right-hand side:

cos(0) = 1 - x^2/2! + x^4/4! - x^6/6! + ...

Multiplying both sides by x^2/2 and rearranging:

π^2/8 = π^2/4 - π^4/4! + π^6/6! - π^8/8! + ...

Now we can substitute these series expansions into the original sum and simplify:

∑n=0^[infinity] (-1)^n π^2n/(6^2n (2n)!)

= π^2/2 - π^4/4! + π^6/6! - π^8/8! + ...

= 2π^2/4 - π^4/4! + π^6/6! - π^8/8! + ...

= (2π^2 - π^4/3! + π^6/5! - π^8/7! + ...) / 4

= (2π^2 - π^4/6 + π^6/120 - π^8/5040 + ...) / 4

So the sum of the series is (2π^2 - π^4/6 + π^6/120 - π^8/5040 + ...) / 4.

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The time needed to complete a certain test is a normal distribution with a mean of 43 minutes and a standard deviation of 8 minutes.

A normal distribution is a bell-shaped curve that represents a continuous probability distribution. The mean, represented by the symbol μ (mu), is the central tendency of the distribution, while the standard deviation, represented by the symbol σ (sigma), measures the spread of the data. In this case, the mean time needed to complete the test is 43 minutes, and the standard deviation is 8 minutes. This means that most people will take around 43 minutes to complete the test, with fewer people taking either longer or shorter times. The standard deviation of 8 minutes suggests that the time it takes people to complete the test can vary by up to 8 minutes from the mean. The normal distribution is a widely used statistical model, and understanding its properties can help us make predictions and draw conclusions about data.

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The order of h can be any factor of 420 between 43 and 419, inclusive. This is because k is a proper subgroup of h, which means that |k| is a factor of |h|. Since |k| is greater than or equal to 5 and |g| is 420, the maximum possible order of h is 419 (since |h| cannot be equal to |g|). Similarly, the minimum possible order of h is 43 (since |h| cannot be equal to |k|). Therefore, the possible orders of h range from 43 to 419, inclusive, and can be any factor of 420 within this range.

Given that k is a proper subgroup of h and h is a proper subgroup of g, we know that |k| is a factor of |h| and |h| is a factor of |g|. Also, we are given that |k| is greater than or equal to 5 and |g| is 420. Therefore, the maximum possible order of h is 419 (since |h| cannot be equal to |g|), and the minimum possible order of h is 43 (since |h| cannot be equal to |k|).

Now, we need to find the possible orders of h between 43 and 419, inclusive. The factors of 420 within this range are: 43, 46, 69, 83, 138, 207, and 419. Hence, the possible orders of h can be any of these factors.

To sum up, the possible orders of h are any factors of 420 between 43 and 419, inclusive. The maximum possible order is 419, and the minimum possible order is 43. This is because k is a proper subgroup of h, which means that |k| is a factor of |h|, and |g| is 420. Therefore, h can have any factor of 420 within the given range.

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True, it is generally expected that the observed value of x will be within three standard deviations of the expected value approximately 15/16, or 93.75%, of the time.

This observation is based on the empirical rule, which applies to normally distributed data. The empirical rule, also known as the 68-95-99.7 rule, states that approximately 68% of the data falls within one standard deviation, 95% within two standard deviations, and 99.7% within three standard deviations of the mean.
In this case, the expected value lies within three standard deviations of the mean, which covers 99.7% of the data. Consequently, there is only a 0.3% chance of an observed value falling outside this range. Since the question mentions that we expect the observed value to be within three standard deviations 15/16 of the time, it aligns with the empirical rule, making the statement true.
Remember that the empirical rule is specific to normally distributed data, and the observations might vary in cases where the data distribution is different. However, in most real-world situations, data tends to follow a normal distribution, making the empirical rule a valuable tool for estimating probabilities and understanding data dispersion.

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To answer this question, we would need to perform a hypothesis test using the given sample data and a significance level of α = 0.05. The null hypothesis would be that the standard deviation of the resting heart rates for students in this class is equal to 12 bpm, while the alternative hypothesis would be that it is different from 12 bpm.

We would then need to calculate the sample standard deviation from the given data and use it to compute the test statistic (either a t-score or a z-score, depending on the sample size and whether or not the population standard deviation is known). We would compare this test statistic to the critical value from the appropriate distribution (either a t-distribution or a standard normal distribution) using the given significance level.

If the test statistic falls outside the critical value region, we would reject the null hypothesis and conclude that there is enough evidence to say that the standard deviation of the resting heart rates for students in this class is different from 12 bpm. However, if the test statistic falls inside the critical value region, we would fail to reject the null hypothesis and conclude that there is not enough evidence to make such a claim.

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The percentage of the men in the sample who have blood type O is 40.38%.

What is the percentage?

A percentage is a figure or ratio stated as a fraction of 100 in mathematics. The acronyms pct., pct., and occasionally pc are also used to indicate it, however, the percent sign is most frequently used. A % is a number without dimensions and without a standard measurement.

Here, we have

Given: The contingency table below shows the blood types of a sample of people cross-classified by sex.

We have to find the percentage of the men in the sample who have blood type o.

Total number of males = 104

Number of males who has blood type O = 42

Percentage of the males in the sample have blood type O:

= (42×100%)/104

= 40.38%

Hence, the percentage of the men in the sample who have blood type O is 40.38%.

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A possible dimension that will work for the settlement is a length of  186.61 units and a width of  13.39 units.

Area of a rectangle   = L × W

perimeter = 2L + 2W.

we set up equations:

Equation 1: A = L × W = 2,500

Equation 2: P = 2L + 2W < 400

We will solve  this system of equations and find the dimensions

We will arrive at a  quadratic formula:

W = (-b ± √(b² - 4ac)) / (2a)

W = (-(-200) ± √((-200)² - 4(1)(2500))) / (2(1))

W = (200 ± √(40000 - 10000)) / 2

W = (200 ± √30000) / 2

W = (200 ± 173.21) / 2

W₁ = (200 + 173.21) / 2 = 186.61

W₂ = (200 - 173.21) / 2 =13.39

We finally substitute value of w into equation 1

L = 2500 / W

L = 2500 / 13.39 =  186.61

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The chance that a randomly selected defective component was made by Alice is approximately 0.33 or 33%.

a. The probability of a randomly selected individual being a male who smokes is 19/100 or 0.19.

b. The probability of a randomly selected individual being a male is 0.6.

c. The probability of a randomly selected individual smoking is (19+12)/100 or 0.31.

d. The probability that a randomly selected female is a smoker is 12/40 or 0.3.

e. The probability that a randomly selected smoker is male is 19/(19+12) or 0.61.

To find the chance that a randomly selected defective component was made by Alice, we can use Bayes' Theorem.

Let A, B, and C represent the events that a component is made by Alice, Betty, and Cleo respectively, and let D represent the event that a component is defective.

We want to find P(A|D), the probability that the defective component was made by Alice. Using Bayes' Theorem, we have:

P(A|D) = P(D|A) * P(A) / [P(D|A) * P(A) + P(D|B) * P(B) + P(D|C) * P(C)]

We know that P(A) = P(B) = P(C) = 1/3, P(D|A) = 0.05, P(D|B) = 0.03, and P(D|C) = 0.02. Substituting these values, we get:

P(A|D) = 0.05 * (1/3) / [0.05 * (1/3) + 0.03 * (1/3) + 0.02 * (1/3)]

       = 0.333 or approximately 0.33

Therefore, the chance that a randomly selected defective component was made by Alice is approximately 0.33 or 33%.

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Complete Question:

             Yes No Total

Male 19 41 60

Female 12 28 40

Total 31 69 100

a. What is the probability of a randomly selected individual being a male who smokes (or male and smoker)?

b. What is the probability of a randomly selected individual being a male?

c. What is the probability of a randomly selected individual smoking?

d. A person is selected at random and if the person is female, what is the probability that she is a smoker?

e. What is the probability that a randomly selected smoker is male?

A manufacturing firm has three machine operators; Alice, Betty, and Cleo. The operators produce a component. Alice has a 5% defective rate, Betty a 3% defective rate, and Cleo a 2% defective rate. The three operators produce equal numbers of components. Suppose a randomly selected component is found to be defective. What is the chance it was made by Alice?

Answer:

60 13/20

Step-by-step explanation:

20 goes into 121 6 times

leaves you with 1 then bring down the 3

20 won't go into 13 so it's 0 leaving you with 13

so the answer = 60 13/20

4/9 = A

2/3 to the power of 2 is 4/9