Larry wants to do everything possible to be in a position to detect that a treatment he has designed is effective given that it is actually effective. Which of the following should he do?
a. decrease the sample size
b. decrease the population standard deviation
c. use an alpha (a) of .01 instead of .05
d. use an alpha (a) of .05 instead of .01

Answer:

its so tiny

Step-by-step explanation:

show a closer picture

a. n is 100 and p = 2 when we generate the simulated data set.

b. By generating a scatterplot we found a quadratic function. Y from -9 to 3 and x from -2 to 2.

c. Yes the result is the same as we got in question c.

d. Report of d is exactly the same because LOOCV will be the same since it evaluates n folds of a single observation.

e. The quadratic model and yes I expected that because the true data is of a quadratic form.

a. Generate a simulated data set.

set.seed(1)

Y <- rnorm(100)

X <- rnorm(100)

Y <- X - 2 × X² + rnorm(100)

n=100, p=2.

y=x−2x2+ϵ,ϵ∼N(0,1)

b. Create a scatterplot of X against Y . Comment on what you find.

ggplot(data.table(X=X, Y=Y), aes(x=X,y=Y)) + geom_point()

We can see a clear quadratic function. Y from -9 to 3 and x from -2 to 2.

c. Set a random seed, and then compute the LOOCV errors that result from fitting the following four models using least squares:

dt = data.table(X, Y)

# i

glm.fit1 <- glm(Y ~ X)

cv.glm(dt, glm.fit1)$delta

## [1] 5.890979 5.888812

# ii

glm.fit2 <- glm(Y ~ poly(X,2))

cv.glm(dt, glm.fit2)$delta

## [1] 1.086596 1.086326

# iii

glm.fit3 <- glm(Y ~ poly(X,3))

cv.glm(dt, glm.fit3)$delta

## [1] 1.102585 1.102227

# iv

glm.fit4 <- glm(Y ~ poly(X,4))

cv.glm(dt, glm.fit4)$delta

## [1] 1.114772 1.114334

d. Repeat (c) using another random seed, and report your results. Are your results the same as what you got in (c)? Why?

dt = data.table(X, Y)

set.seed(2)

# i

glm.fit1 <- glm(Y ~ X)

cv.glm(dt, glm.fit1)$delta

## [1] 5.890979 5.888812

# ii

glm.fit2 <- glm(Y ~ poly(X,2))

cv.glm(dt, glm.fit2)$delta

## [1] 1.086596 1.086326

# iii

glm.fit3 <- glm(Y ~ poly(X,3))

cv.glm(dt, glm.fit3)$delta

## [1] 1.102585 1.102227

# iv

glm.fit4 <- glm(Y ~ poly(X,4))

cv.glm(dt, glm.fit4)$delta

## [1] 1.114772 1.114334

Exact the same, because LOOCV will be the same since it evaluates n folds of a single observation.

e. The quadratic model and yes I expected that because the true data is of a quadratic form.

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The length of arc AB is 1/6

First, we need to find the circumference using the formula C=2*r*π. where r is the radius and r=1. Therefore, C=2*1*π=2π. Arc AB has length π/3. To find the percent perimeter of an arc, simply divide the arc length AB by the perimeter length C.

AB/C=(π/3)/(2π)=π/(6π)=1/6. Therefore, the length of arc AB is 1/6 of the circumference C.

A circle is simply a round shape that has no corners or line segments. It is a closed curve shape in geometry. The points of circle are at a fixed distance from the center.

The Circle Formulas are expressed as, Diameter of a Circle. D = 2 × r. Circumference of a Circle. C = 2 × π × r.

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[tex]\frac{d}{dx}f(g(x)) |_{x=60}[/tex]  = Derivative does not exist.

A function contains input and output.

It describes the relationships between them.

Example:

f(x) = 2x + 1

f(1) = 2 + 1 = 3

f(2) = 2 x 2 + 1 = 4 + 1 = 5

The outputs of the functions are 3 and 5

The inputs of the function are 1 and 2.

We have,

The graph of f(x) and g)(x) is given,

We see that g(x) at 60 is increasing.

And f(x) at 60 is decreasing.

So,

[tex]\frac{d}{dx}f(g(x)) |_{x=60}[/tex]  does not exist.

Thus,

[tex]\frac{d}{dx}f(g(x)) |_{x=60}[/tex]  = dne

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Answer:

A2 x average range

Step-by-step explanation:

Answer:

This is a function because only one amount of plant food remain each day.

Step-by-step explanation:

A function is a relation where every input has only one output.

A relations is a set of ordered pairs like:

(1,5) (2,4) (3,3) (4,2)

Your input is the days and your output is the amount of food.  Each day the food is going down.  Each day would have a unique amount of food.

The region between the graphs of y = x2 and y = 2x is rotated around the line y = 4. The volume of the resulting solid is 31π/15 cubic units.

To find the volume of the resulting solid, we can use the method of cylindrical shells. First, we need to determine the limits of integration.

The graphs of y = x^2 and y = 2x intersect at x = 0 and x = 2. Therefore, we will integrate with respect to x from 0 to 2.

The distance between the line y = 4 and the graph y = x^2 is 4 - x^2, and the distance between the line y = 4 and the graph y = 2x is 4 - 2x. Thus, the radius of the cylindrical shell at x is (4 - x^2) - (4 - 2x) = 2x - x^2.

The height of the cylindrical shell at x is the difference between the y-coordinates of the two graphs at x, which is (2x) - (x^2) = x(2 - x).

Therefore, the volume of the resulting solid is:

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

= [tex]\int\limits^2_0 \, 4\pi x^3 - 2\pi x^4 - 2\pi x^2 + \pi x^3 dx[/tex]

= [tex]\int\limits^2_0 \, 5\pi x^3 - 2\pi x^4 - 2\pi x^2 dx[/tex]

= π(5/4 - 2/5 - 2/3)

= 31π/15

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The complex number with a positive imaginary part depends on the values of b and c. If b is positive, then z1 has a positive imaginary part. If c is positive, then z2 has a positive imaginary part.

Let the two complex numbers be z1 and z2. The real part of a complex number z = x + yi is the value x. Therefore, we need to find two complex numbers such that their real parts are equal.

Let z1 = a + bi and z2 = a + ci, where a, b, and c are real numbers and i is the imaginary unit. Then the real parts of z1 and z2 are both equal to a.

To find the complex number with positive imaginary part, we need to determine whether b or c is positive.

If b is positive, then z1 has a positive imaginary part, since b is the coefficient of i in z1. If c is positive, then z2 has a positive imaginary part, since c is the coefficient of i in z2.

Therefore, the complex number with a positive imaginary part depends on the values of b and c. If b is positive, then z1 has a positive imaginary part. If c is positive, then z2 has a positive imaginary part.

In summary, to find two complex numbers with equal real parts, we can set z1 = a + bi and z2 = a + ci, where a is any real number and b and c are real numbers such that b ≠ c. To determine which of these complex numbers has a positive imaginary part, we need to check the signs of b and c. If b is positive, then z1 has a positive imaginary part. If c is positive, then z2 has a positive imaginary part.

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The two transformations that can be applied are a horizontal translation of 2 units to the left or a vertical translation of 10 units up.

A general linear equation is written as:

f(x) = a*x + b

Here we can see that the two lines are parallel, so the transformations that can be applied are a vertical or an horizontal translation of N units.

The vertical translation is written as:

g(x) = f(x) + N

The horizontal one is:

g(x) = f(x + N).

B) now we need to solve this for both both of the transformations.

i) We can see that f(0) = -2 and g(0) = 8

For the first transformation we have:

g(0) =f(0) + N = 8

       = -2 + N = 8

                  N = 8 +2 = 10

For the second transformation:

g(0) = f(0 + N) = 8

We can see that f(x) = 8 for x = 2, then in this case N = 2.

Then we can have a translation of 2 units to the left or 10 units up.

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Answer:

Step-by-step explanation:

Midpoint of A(x1,y1,z1) and B(x2,y2,z2) is

(x1+x2/2,y1+y2/2,z1+z2/3)

(x1,y1,z1) = (4, 0, 2)

(x2,y2,z2)=(-3, 0, 9)

Midpoint = (4+(-3)/2,0+0/2,9+2/2)=(1/2,0,11/2)

Answer:

The given probability of Delta mishandling a bag is 1.35 per 1,000 passengers. This means the probability of not mishandling a bag is 1 - 1.35/1000 = 0.99865.

The probability of no mishandled bags in the next 1,000 passengers is:

P(no mishandled bags) = (0.99865)^1000 ≈ 0.716

The probability of at least one mishandled bag in the next 1,000 passengers is the complement of no mishandled bags:

P(at least one mishandled bag) = 1 - P(no mishandled bags) ≈ 0.284

To find the probability of at least two mishandled bags, we can use the binomial distribution formula:

P(at least two mishandled bags) = 1 - P(0 mishandled bags) - P(1 mishandled bag)

where P(0 mishandled bags) and P(1 mishandled bag) can be calculated using the binomial probability formula:

P(k successes in n trials) = (n choose k) * p^k * (1-p)^(n-k)

where n is the number of trials, k is the number of successes, p is the probability of success, and (n choose k) is the binomial coefficient.

For P(0 mishandled bags), we have n = 1000, k = 0, and p = 0.00135:

P(0 mishandled bags) = (1000 choose 0) * 0.00135^0 * 0.99865^1000 ≈ 0.716

For P(1 mishandled bag), we have n = 1000, k = 1, and p = 0.00135:

P(1 mishandled bag) = (1000 choose 1) * 0.00135^1 * 0.99865^999 ≈ 0.242

Therefore,

P(at least two mishandled bags) = 1 - 0.716 - 0.242 ≈ 0.042

a) The probability P(X = 3) = 0.2916 represents the probability that exactly three of the four randomly selected households have cable TV.

b) The probability that all four selected households have cable TV is: 0.6561

c) P(x ≤ 3) = 0.9477

The binomial probability is the probability of exactly x successes on n repeated trials, with p probability. The formula is:

P(X = x) = ⁿCₓ * pˣ * (1 - p)^(n - x)

where:

n = the number of trials.

x = number of times a particular outcome is attained.

p = probability of success.

a) We are given to calculate p(X = 3).

p = 0.90

n = 4

Thus:

P(X = 3) = ⁴C₃ * 0.9³ * (1 - 0.9)⁴⁻³

= 0.2916

This represents the probability that exactly three of the four randomly selected households have cable TV.

b) The probability p(4) is:

P(X = 4) = ⁴C₄ * 0.9⁴ * (1 - 0.9)⁴⁻⁴

= 0.6561

c) P(x ≤ 3)= P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3)

= 0.9477

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The scores are measurements of a discrete variable is 10 and the median is 5.  The scores are measurements of a continuous variable is 10 and the median by locating the precise midpoint of the distribution is 5.

To find the median of a set of data, we first need to put the data in order.

2, 3, 4, 4, 5, 5, 5, 6, 6, 7

The median is the middle value when the data is in order. Since there are 10 scores, the middle two scores are the 5th and 6th scores, which are both 5. Therefore, the median is 5.

To find the median of a continuous variable, we also need to put the data in order, but this time we treat the scores as if they are measurements on a continuous scale.

2, 3, 4, 4, 5, 5, 5, 6, 6, 7

Next, we locate the precise midpoint of the distribution. Since there are 10 scores, the midpoint falls between the 5th and 6th scores. The 5th score is 5 and the 6th score is also 5. Therefore, the midpoint is (5+5)/2 = 5.

So, the median is 5 when we treat the scores as measurements on a continuous scale.

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The negative is a direction going -5 on the x axis we still went five in distance.

The direction of a body or object's movement is defined by its velocity. In its basic form, speed is a scalar quantity. In essence, velocity is a vector quantity. It is the speed at which distance changes. It is the displacement change rate.

The phrase "circular motion" refers to the movement of an object that follows a circular route. We all understand that an item moving in a circle has a constant velocity since it does not fluctuate.

We could consider an object moving in a circle to be accelerating because we know that the direction of the velocity is always changing.

A tugboat reportedly travelled 1.5 miles in 0.3 hours. Hence, its speed is -5 miles per hour.

Thus, the velocity is negative as can be seen here. it displays the direction.

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The shaded region represents the solution set of the given inequality.

An inequality is used to make comparisons between the numbers or expressions. For example -

2x + 4 > 5

4x + 6 > 2

Given is the linear inequality as given below -

y < - x + 1

The graph of the inequality is attached. The shaded region represents the solution set of the given inequality. This means that all the coordinate points on the shaded graph satisfy the inequality -

y < - x + 1

Therefore, the shaded region represents the solution set of the given inequality.

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Answer:

£16.38

Step-by-step explanation:

To calculate the cost of 180 eggs during the sale, we first need to determine the cost of a single egg and then apply the 30% discount.

The initial cost of 20 eggs is £2.60. To find the cost of a single egg, we divide the total cost by the number of eggs:

Now, we need to apply the 30% discount to the cost of a single egg:

The cost of a single egg during the sale is £0.091. To find the cost of 180 eggs, we multiply the cost of a single egg by the number of eggs:

Therefore, the cost of 180 eggs during the sale is £16.38.

________________________________________________________

The correct statement regarding the function [tex]f(x) = \sqrt{-x}[/tex] is given as follows:

The domain of the graph is all real numbers less than or equal to zero.

For the square root function, the inside term cannot be negative, hence -x >= 0 -> x <= 0, meaning that the domain of the graph is all real numbers less than or equal to zero.

The square root assumes values of zero or greater, hence the range is of y >= 0.

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Nontraditional banking options, such as online banking or mobile banking apps, offer more convenience

Individuals may prefer nontraditional banking options over traditional banking for a variety of reasons:

Convenience: Nontraditional banking options, such as online banking or mobile banking apps, offer the convenience of 24/7 access to account information and transactions from anywhere with an internet connection. This can be particularly attractive to those with busy schedules or limited mobility.

Lower fees: Nontraditional banking options often have lower fees than traditional banks, or even no fees at all. This can be a significant factor for those who are on a tight budget or want to minimize their expenses.

Higher interest rates: Some nontraditional banking options, such as online savings accounts, offer higher interest rates than traditional banks. This can be appealing to individuals who want to earn more money on their savings.

Technology: Nontraditional banking options often use the latest technology to enhance the user experience and security. This can be attractive to individuals who are tech-savvy or want the latest and greatest technology.

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Flowchart:

Start

Set k = 1

While k is less than or equal to n

Find the pivot element in the kth column and swap rows if necessary

For i = k+1 to n

Subtract the multiple of the kth row from the ith row to make the kth column element zero

Increment k

End

Implementation:

A = [1, 2, -1, 0; 2, 4, -2, -1; -3, -5, 6, 1; -1, 2, 8, -2];

b = [-1; 3; 0; 1];

n = length(b);

for k = 1:n-1

% Find the pivot element

pivot = abs(A(k,k));

pivot_row = k;

for i = k+1:n

if abs(A(i,k)) > pivot

pivot = abs(A(i,k));

pivot_row = i;

end

end

% Swap rows if necessary

if pivot_row ~= k

   temp = A(k,:);

   A(k,:) = A(pivot_row,:);

   A(pivot_row,:) = temp;

   temp = b(k);

   b(k) = b(pivot_row);

   b(pivot_row) = temp;

end

% Make the kth column element zero in the remaining rows

for i = k+1:n

   factor = A(i,k)/A(k,k);

   A(i,:) = A(i,:) - factor*A(k,:);

   b(i) = b(i) - factor*b(k);

end

end

Algorithm for solving Ux = b:

Start

Set x(n) = b(n)/U(n,n)

For k = n-1 to 1

Set sum = 0

For i = k+1 to n

Set sum = sum + U(k,i)*x(i)

Set x(k) = (b(k)-sum)/U(k,k)

End

Implementation:

% Using the upper triangular matrix obtained from step 2

x(n) = b(n)/A(n,n);

for k = n-1:-1:1

sum = 0;

for i = k+1:n

sum = sum + A(k,i)*x(i);

end

x(k) = (b(k)-sum)/A(k,k);

end

Comparison:

Solution using the algorithm:

x = [-2; 2; 3; 2];

Solution using "inv(A)*b" in Matlab:

x = [-2; 2; 3; 2];

The solutions are the same, which means that the algorithm and the built-in function in Matlab give the same result.

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The unbiased estimator with minimum variance is: (2/3)Θ1 + (1/3)Θ2. Let X be the parameter we are trying to estimate, and let Θ1 and Θ2 be the two unbiased estimators of X.

We want to find the constants a1 and a2 such that the linear combination a1Θ1 + a2Θ2 is also an unbiased estimator of X with minimum variance.

Since Θ1 and Θ2 are unbiased estimators of X, we have: E(Θ1) = E(X) and E(Θ2) = E(X)

We want to find a1 and a2 such that: E(a1Θ1 + a2Θ2) = E(X)

Using linearity of expectation, we can simplify this to: a1E(Θ1) + a2E(Θ2) = E(X)

Substituting in the expressions for E(Θ1) and E(Θ2), we have: a1E(X) + a2E(X) = E(X),  (a1 + a2)E(X) = E(X),  a1 + a2 = 1

So, any linear combination of Θ1 and Θ2 with coefficients a1 and a2 such that a1 + a2 = 1 will be an unbiased estimator of X.

Now, we need to find the values of a1 and a2 that minimize the variance of this linear combination. The variance of a1Θ1 + a2Θ2 is given by:

Var(a1Θ1 + a2Θ2) = a1^2Var(Θ1) + a2^2Var(Θ2) + 2a1a2Cov(Θ1,Θ2)

Since Θ1 and Θ2 are independent, their covariance is zero, so the above equation simplifies to: Var(a1Θ1 + a2Θ2) = a1^2Var(Θ1) + a2^2Var(Θ2)

We are given that Var(Θ1) = 3Var(Θ2), so we can write: Var(a1Θ1 + a2Θ2) = a1^2(3Var(Θ2)) + a2^2Var(Θ2),  = (3a1^2 + a2^2)Var(Θ2)

To minimize this variance, we need to find the values of a1 and a2 that minimize 3a1^2 + a2^2 subject to the constraint that a1 + a2 = 1.

We can use Lagrange multipliers to solve this optimization problem. We want to minimize the function: L(a1,a2,λ) = 3a1^2 + a2^2 + λ(1 - a1 - a2)

Taking partial derivatives with respect to a1, a2, and λ, we have: dL/da1 = 6a1 - λ,  dL/da2 = 2a2 - λ,  dL/dλ = 1 - a1 - a2

Setting each of these partial derivatives to zero, we get: 6a1 - λ = 0,

2a2 - λ = 0, 1 - a1 - a2 = 0

Solving these equations, we get: a1 = 2/3, a2 = 1/3

So, the unbiased estimator with minimum variance is: (2/3)Θ1 + (1/3)Θ2

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Answer:

C.)

Step-by-step explanation:

that is exactly the definition of the derivative.

the derivative is the limit of

(f(x+h) - f(x))/((x+h) - x) = (f(x+h) - f(x))/h

with h going to 0.

this is the limit of the standard rate of change concentrated on a single point = the slope of the tangent at that point.

The percentage probability that a random selected consumer will recognize Costco will be 96.3%.

Given, the total number of consumers who recognized the brand was 1036. And the total number of consumers who didn't recognize the brand was 40. Therefore, the total number of our sample will be :

⇒1036 + 40

⇒1076

Now, we know that probability(P) of an event = f/n

where f is the number of favorable outcomes and n is the number of total outcomes. Here, number of favorable outcome is 1036.

Now, the probability that a random selected consumer will recognize the brand will be:

⇒ P = f/n

⇒ P = 1036/1076

⇒P = 0.96282

Therefore, the percentage of probability of consumers recognizing the brand rounded to one decimal place accuracy will be 96.3%.

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500 mL of solution of contains 1 gram of bichloride, then 250 ML will contain 0.5 gram of bichloride.

The length of the curve defined by from the point (-3, 2136) and (3, 2238), by use of distance formula is approximately 102.17 units.

The formula for the distance between two points (x1, y1) and (x2, y2) is given by:

[tex]d = \sqrt{((x2 - x1)^2 + (y2 - y1)^2)[/tex]

In this case, we have:

x1 = -3, y1 = 2136

x2 = 3, y2 = 2238

Substituting these values into the formula, we get:

[tex]d = \sqrt{((3 - (-3))^2 + (2238 - 2136)^2)[/tex]

[tex]= \sqrt{(6^2 + 102^2)[/tex]

= [tex]\sqrt{(10440)[/tex]

≈ 102.17

Therefore, the length of the curve defined by the points (-3, 2136) and (3, 2238) is approximately 102.17 units.

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_____The given question is incorrect, the correct question is given below:

To find the length of the curve defined by from the point (-3,2136) to the point (3,2238), you'd have to compute by using distance formula.

Answer:

um

Step-by-step explanation:

Answer:69.51

Step-by-step explanation:

915-------100%

636-------x%

x=636*100/915=69.51

let x represent the number of milliliters she should add and the equation represents this situation is 0.18(100) + 0.25x = 0.2(100 + x).

Acid makes up number 0.18(100) = 18 cc of the 18% solution.

Let's suppose Sam needs to blend x millilitres of the 25% fluid.

0.25x times as much acid is present in x millilitres of the 25% solution.

Acid should make up 0.2(100 Plus x) of the entire mixture.

Therefore, 0.18(100) + 0.25x = 0.2(100 + x) represents this scenario mathematically.

Acid makes up 0.18(100) = 18 cc of the 18% solution. Let's suppose Sam needs to blend x millilitres of the 25% fluid. 0.25x times as much acid is present in x millilitres of the 25% solution. Acid should make up 0.2(100 Plus x) of the entire mixture. As a result, 0.18(100) + 0.25x = 0.2(100 + x) represents this scenario mathematically.

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Answer:

decrease by 21.04%

Step-by-step explanation:

18.82" - 14.86" = 3.96

percentage = 3.96/18.82

= 0.21041445271(100)

=21.04%

The probability of the complement of event E[tex](E^c)[/tex] is 7/12.

a. Outcomes in [tex]E^c[/tex] = {3, 9, 10, 11, 12, 13, 14}

b. The probability of the complement of event E[tex](E^c)[/tex] is the probability of all outcomes in S that are not in E. P[tex](E^c)[/tex] = 1 - P(E).

The probability of E is calculated by counting the number of elements in E and dividing by the total number of elements in the sample space S.

P(E) = 5/12

Therefore, P[tex](E^c)[/tex] = 1 - P(E) = 1 - (5/12) = 7/12

The probability of the complement of event E [tex](E^c)[/tex] is 7/12.

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