A survey of US adults ages 18-24 found that 34% get the news on an average day. You randomly select 200 adults ages 18-24 and ask them if they get news on an average day. Find the mean and standard deviation (assuming you can use the normal dist to approximate this binomial dist).

Using the previous information, find the probability that at least 85 people say they get no news on an average day.

Answers

Answer 1

Answer: Approximately 5.21

Step-by-step explanation:

Given that the survey of US adults ages 18-24 found that 34% get the news on an average day, we can assume that the probability of an 18-24 year old getting news on an average day is p = 0.34. We also know that we have randomly selected 200 adults in this age group.

The mean of a binomial distribution is given by:

μ = np

where n is the sample size and p is the probability of success. Substituting the given values, we get:

μ = 200 x 0.34 = 68

Therefore, the mean number of adults ages 18-24 who get news on an average day is 68.

The standard deviation of a binomial distribution is given by:

σ = sqrt(np(1-p))

Substituting the given values, we get:

σ = sqrt(200 x 0.34 x 0.66) ≈ 5.21

Therefore, the standard deviation of the number of adults ages 18-24 who get news on an average day is approximately 5.21. Since the sample size is large (n=200), we can use the normal distribution to approximate the binomial distribution.

Answer 2

Answer:

The mean and standard deviation of the number of adults out of 200 who get news on an average day are mu = 68 and sigma = 5.36, respectively, assuming we can use the normal distribution to approximate the binomial distribution.

So the probability that at least 85 people say they get no news on an average day is approximately 0.0013 or 0.13%.

Step-by-step explanation:

Since the survey found that 34% of US adults ages 18-24 get news on an average day, we can assume that the probability of a randomly selected adult in this age group getting news on an average day is p = 0.34. Therefore, the number of adults out of 200 who get news on an average day follows a binomial distribution with parameters n = 200 and p = 0.34.

To use the normal distribution to approximate this binomial distribution, we need to check if the conditions for doing so are met. These conditions are:

np >= 10

n(1-p) >= 10

Here, np = 200 x 0.34 = 68 and n(1-p) = 200 x 0.66 = 132. Both of these values are greater than 10, so the conditions are met.

Now, we can approximate the binomial distribution with a normal distribution with mean mu = np = 68 and standard deviation sigma = sqrt(np(1-p)) = sqrt(200 x 0.34 x 0.66) = 5.36.

Therefore, the mean and standard deviation of the number of adults out of 200 who get news on an average day are mu = 68 and sigma = 5.36, respectively, assuming we can use the normal distribution to approximate the binomial distribution.

Using the previous information, to find the probability that at least 85 people say they get no news on an average day.

Let X be the number of people out of 200 who say they get no news on an average day. We want to find the probability that X is greater than or equal to 85.

Since the probability of any one person saying they get no news on an average day is q = 1 - p = 0.66, we can use the binomial distribution with parameters n = 200 and p = 0.34 to model the number of people who say they get news on an average day.

The probability of at least 85 people saying they get no news on an average day can be calculated using the complement rule:

P(X >= 85) = 1 - P(X < 85)

To use the normal distribution to approximate the binomial distribution, we need to standardize the variable X.

Z = (X - mu) / sigma

where mu = np = 68 and sigma = sqrt(npq) = 5.36, as calculated in the previous question.

Using the continuity correction, we can adjust the upper bound to P(X < 84.5) since we want the probability of at least 85 people saying they get no news.

Z = (84.5 - 68) / 5.36 = 3.00

Using a standard normal distribution table or calculator, we can find that P(Z < 3.00) = 0.9987.

Therefore, the probability of at least 85 people saying they get no news on an average day is:

P(X >= 85) = 1 - P(X < 85)

≈ 1 - P(Z < 3.00)

= 1 - 0.9987

≈ 0.0013

So the probability that at least 85 people say they get no news on an average day is approximately 0.0013 or 0.13%.


Related Questions

if a flexible copper cable has 133 strands, each 5.63 mils in diamteter, what is the size of the cable in circular mils

Answers

As a result, the cable is **3317.7 CM⁵ in diameter in round mils.

explain circular mills.

A circular mil (CM) is a measurement of area that is particularly useful for describing the size of a wire or cable's cross section. It is equivalent to the surface area of a circle with a one mil (a thousandth of an inch, or 0.0254 mm²) diameter. It is equivalent to roughly 0.7854 millionths of an inch square.

This formula can be used to get the cable's diameter in circular mils:

- Each strand has a diameter of 5.63 mils.

Each strand has an area of (5.63/2)2 × π, or 24.9 circular mils (CM).

- 133 strands have a total area of 133× 24.9, or 3317.7 CM.

As a result, the cable is **3317.7 CM**⁵ in diameter in round mils.

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what do you think could have happened if don't know about the different shapes​

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Nothing happened for real.

i think its not a big deal for you but it will be a big deal for your parents ;))))

Use your knowledge of genetic biology and lecture them. Maybe they don't understand.

Just kidding =))))

In short, you may have an optical problem =))))

P/s: don't be furious :'))) it's gonna easy to get old

ok done. Thank to me >:333

solve the given differential equation. (the form of yp is given.) show your work in clear and concise steps. put a box around your final answer. y'' - y = x2 3 (let yp = ax2 bx c.)

Answers

To solve the differential equation y'' - y = x^2/3 using the given form of yp (yp = ax^2 + bx + c), we first need to find the derivatives of yp.

yp = ax^2 + bx + c
yp' = 2ax + b
yp'' = 2a

Substituting yp, yp', and yp'' into the differential equation gives:

2a - (ax^2 + bx + c) = x^2/3

Simplifying this equation and comparing the coefficients of x^2, x, and the constant term gives:

-a = 1/3
b = 0
2a - c = 0

Solving for a, b, and c, we get:

a = -1/3
b = 0
c = -2a = 2/3

Therefore, the particular solution is yp = -x^2/3 + 2/3.

To find the general solution, we need to add the homogeneous solution, which is the solution to the associated homogeneous equation y'' - y = 0. The characteristic equation for this homogeneous equation is r^2 - 1 = 0, which has roots r = ±1.

Therefore, the general solution is:

y = c1e^x + c2e^-x - x^2/3 + 2/3

where c1 and c2 are constants determined by the initial or boundary conditions.

Final answer:

y = c1e^x + c2e^-x - x^2/3 + 2/3

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describe the given set with a single equation or with a pair of equations. the circle of radius centered at and lying in a. the xy-plane b. the yz-plane c. the plane y

Answers

The simplified versions of the given circle equation are a. x^2 + (y-1)^2 = 81, b.(y-1)^2 + z^2 = 81, and c. x^2 + z^2 = 81

a. The circle of radius 9 centered at (0, 1, 0) lying in the xy-plane can be described with the equation:
(x-0)^2 + (y-1)^2 = 9^2
Simplified, this becomes: x^2 + (y-1)^2 = 81

b. The circle of radius 9 centered at (0, 1, 0) lying in the yz- plane can be described with the equation:
(y-1)^2 + (z-0)^2 = 9^2
Simplified, this becomes: (y-1)^2 + z^2 = 81

c. If the circle of radius 9 centered at (0, 1, 0) is lying in the plane y, it means that the y-coordinate is constant throughout the circle. In this case, the equation becomes:
x^2 + z^2 = 9^2
Simplified, this becomes: x^2 + z^2 = 81, with y = 1

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let f (x) = cos(4x) 5. compute the following taylor polynomials of f. for any approximations, you should use around 6 decimals. p0(x) = p1(x) = p2(x) = p3(x) = p4(x) =

Answers

We have computed the Taylor polynomials of the given function f (x) = cos (4x), using around 6 decimals for approximation. These polynomials can then be used to approximate the given function.

What is function?

Function is a block of code that performs a specific task. It can accept input parameters and return a value or a set of values. Functions are used to break down a complex problem into simple, manageable tasks. They also help improve code readability and re-usability. By using functions, you can write code more efficiently and easily maintain your program.

The Taylor series of a given function is a polynomial approximation of that function, derived using derivatives. In this case, we are asked to compute the Taylor polynomial for the function f (x) = cos (4x).

The Taylor polynomials of f are as follows:

p0(x) = 1

p1(x) = 1 - 8x2

p2(x) = 1 - 8x2 + 32x4

p3(x) = 1 - 8x2 + 32x4 - 128x6

p4(x) = 1 - 8x2 + 32x4 - 128x6 + 512x8

For any approximations, we can use around 6 decimals. For instance, if x = 0.5, then p4(0.5) = 0.988377, which is an approximation of the actual value of f (0.5), which is 0.98879958.

In conclusion, we have computed the Taylor polynomials of the given function f (x) = cos (4x), using around 6 decimals for approximation. These polynomials can then be used to approximate the given function.

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Sketch the graphs of the following equations y=x+5, y=-(x+5) and y=|x+5|

Answers

Answer:

See below

Step-by-step explanation:

Suppose ~(0,1), find: (a) P( < 0.5)
(b) P( = 0.5)
(c) P( ≥ 2.3)
(d) P(−1.4 ≤ ≤ 0.6)
(e) The value of z0 such that P(|| ≤ z0) = 0.32

Answers

Probabilities associated with this distribution are

(a) P(Z < 0.5) = 0.6915

(b) P(Z = 0.5) = 0

(c) P(Z ≥ 2.3) = 0.0107.

(d)  P(-1.4 ≤ Z ≤ 0.6) = 0.6449.

(e) The value of z0 such that P(|Z| ≤ z0) = 0.32 is 0.9945.

How to find P( < 0.5)?

The statement "~(0,1)" refers to a standard normal distribution with mean 0 and standard deviation 1.

We can use the standard normal distribution table or a calculator to find probabilities associated with this distribution. Here are the solutions to the given problems:

(a) P(Z < 0.5) = 0.6915, where Z is a standard normal random variable.

How to find P( = 0.5)?

(b) P(Z = 0.5) = 0, since the probability of a continuous random variable taking any specific value is always zero.

How to find P( ≥ 2.3)?

(c) P(Z ≥ 2.3) = 0.0107.

How to find P(−1.4 ≤ ≤ 0.6)?

(d) P(-1.4 ≤ Z ≤ 0.6) = P(Z ≤ 0.6) - P(Z ≤ -1.4) = 0.7257 - 0.0808 = 0.6449.

How to find the value of z0 such that P(|| ≤ z0) = 0.32?

(e) The value of z0 such that P(|Z| ≤ z0) = 0.32 is the 0.16th percentile of the standard normal distribution.

From the standard normal distribution table, we can find that the 0.16th percentile is approximately -0.9945. Therefore, z0 = 0.9945.

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list the elements of the set in roster notation. (enter empty or ∅ for the empty set.) {x | x is a digit in the number 457,636}

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The given set contains the digits of the number 457,636 and can be written in roster notation as {4, 5, 7, 6, 3}.

Identify the individual digits of the number and write them as elements of the set in the form of roster notation?

list the elements of the set in roster notation. (enter empty or ∅ for the empty set.) {x | x is a digit in the number 457,636.  

Sure, I can provide some additional information on sets and roster notation.

In mathematics, a set is a collection of distinct objects, called elements or members of the set. One way to represent a set is through roster notation, which lists the elements of the set inside braces { } separated by commas. For example, the set of even numbers less than 10 can be written in roster notation as {2, 4, 6, 8}.

In the given problem, we are asked to list the elements of the set in roster notation where the set contains the digits of the number 457,636. The digits of the number are 4, 5, 7, 6, and 3, so the set can be written in roster notation as {4, 5, 7, 6, 3}.

It is worth noting that sets can be empty, denoted by the symbol ∅ or by the word "empty". An empty set contains no elements. For example, the set of integers greater than 10 and less than 0 is an empty set, which can be represented in roster notation as ∅ or {}.

In summary, roster notation is a way to represent sets by listing their elements inside braces. The given set contains the digits of the number 457,636 and can be written in roster notation as {4, 5, 7, 6, 3}.

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Find the area of each trapezoid. Round each answers to the nearest tenth.

Answers

Step-by-step explanation:

A trapezoid bases are the parallel sides

   the AVERAGE of the bases  X  the height    is the area

First one :   Height = 6cm    average of bases = (9.3+4.1) / 2 = 6.7 cm

    area =   6.7 cm * 6 cm = 40.2 c^2

The other three are similar...just different numbers...Using this method, you should be able to do them now .....

Answer:

A trapezoid bases are the parallel sides

  the AVERAGE of the bases  X  the height    is the area

First one :   Height = 6cm    average of bases = (9.3+4.1) / 2 = 6.7 cm

   area =   6.7 cm * 6 cm = 40.2 c^2

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Step-by-step explanation:

Find the zeros of the quadratic function:

y equals x squared plus 2 x minus 24

Answers

Answer:

answer this question in this photo.

I NEED HELP ON THIS ASAP!!!!

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In the two functions as the value of V(x) increases, the value of W(x) also increases.

What is the value of the functions?

The value of functions, V(x) and W(x) is determined as follows;

for h(-2, 1/4); the value of the functions is calculated as follows;

v(x) = 2ˣ ⁺ ³ = 2⁻²⁺³ = 2¹ = 2

w(x) = 2ˣ ⁻ ³ = 2⁻²⁻³ = 2⁻⁵ = 1/32

for h(-1, 1/2); the value of the functions is calculated as follows;

v(x) = 2ˣ ⁺ ³ = 2² = 4

w(x) = 2ˣ ⁻ ³ = 2⁻⁴ = 1/16

for h(0, 1); the value of the functions is calculated as follows;

v(x) = 2ˣ ⁺ ³ = 2³ = 8

w(x) = 2ˣ ⁻ ³ = 2⁻³ = 1/8

for h(1, 2); the value of the functions is calculated as follows;

v(x) = 2ˣ ⁺ ³ = 2⁴ = 16

w(x) = 2ˣ ⁻ ³ = 2⁻² = 1/4

for h(2, 4); the value of the functions is calculated as follows;

v(x) = 2ˣ ⁺ ³ = 2⁵ = 32

w(x) = 2ˣ ⁻ ³ = 2⁻¹ = 1/2

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The random variables X and Y are jointly continuous, with a joint PDF of the form
fX,Y(x,y)={cxy,if 0≤x≤y≤1
0,,otherwise,
where c is a normalizing constant.
For x∈[0,0.5], the conditional PDF fX|Y(x|0.5) is of the form ax^b. Find a and b. Your answers should be numbers.

Answers

a = 4 and b = 1. To find a and b, we need to first find the conditional PDF fX|Y(x|0.5), which represents the distribution of X given that Y = 0.5.

We can use Bayes' rule to find the conditional PDF:

fX|Y(x|0.5) = fX,Y(x,0.5) / fY(0.5)

where fY(0.5) is the marginal PDF of Y evaluated at 0.5, and can be found by integrating fX,Y over all possible values of X:

fY(0.5) = ∫ fX,Y(x,0.5) dx

= ∫ cxy dx (from x=0 to x=0.5)

= c(0.5)²

= c/8

Now, we can find fX,Y(x,0.5) by evaluating the joint PDF at x and y=0.5:

fX,Y(x,0.5) = cxy

= c(0.5)x

So, we have:

fX|Y(x|0.5) = (c(0.5)x) / (c/8)

= 4x

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formulate an ip that assigns each route to one bidder (and each bidder must be assigned to only one route)

Answers

The complete formulation of the integer programming problem can be written as:

Minimize Z = Σi=1n Σj=1m cij xij

subject to:

Σj=1m xij = 1, for i = 1, 2, ..., n

Σi=1n xij = 1, for j = 1, 2, ..., m

xij ∈ {0, 1}, for i = 1, 2, ..., n and j = 1, 2, ..., m.

To formulate an integer programming problem for assigning each route to one bidder (and each bidder to only one route), we can follow these steps:

Define decision variables: Let xij be a binary variable, where xij=1 if bidder i is assigned to route j, and xij=0 otherwise. Here i = 1, 2, ..., n is the index for bidders, and j = 1, 2, ..., m is the index for routes.

Define the objective function: The objective is to minimize the total cost of assignment, which can be represented as the sum of the cost of each assignment, given by cij. Therefore, the objective function can be formulated as:

Minimize Z = Σi=1n Σj=1m cij xij

Define the constraints:

Each bidder can only be assigned to one route: Σj=1m xij = 1, for i = 1, 2, ..., n.

Each route can only be assigned to one bidder: Σi=1n xij = 1, for j = 1, 2, ..., m.

The decision variables are binary: xij ∈ {0, 1}, for i = 1, 2, ..., n and j = 1, 2, ..., m.

These constraints ensure that each bidder is assigned to only one route, and each route is assigned to only one bidder.

The complete formulation of the integer programming problem can be written as:

Minimize Z = Σi=1n Σj=1m cij xij

subject to:

Σj=1m xij = 1, for i = 1, 2, ..., n

Σi=1n xij = 1, for j = 1, 2, ..., m

xij ∈ {0, 1}, for i = 1, 2, ..., n and j = 1, 2, ..., m.

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Full Question ;

formulate an ip that assigns each route to one bidder (and each bidder must be assigned to only one route)

Railway Cabooses just paid its annual dividend of $2.50 per share. The company has been reducing the dividends by 11.7 percent each year. How much are you willing to pay today to purchase stock in this company if your required rate of return is 13 percent?

Answers

Based on the information provided, Railway Cabooses paid an annual dividend of $2.50 per share. However, the company has been reducing its dividends by 11.7 percent each year.

To calculate the current annual dividend, we can use the formula: current dividend = previous dividend * (1 - dividend reduction rate).
So, the current annual dividend would be $2.50 * (1 - 0.117) = $2.21 per share. To determine how much you should pay to purchase stock in this company, we need to use the dividend discount model.
The formula for this model is stock price = annual dividend / (required rate of return - dividend growth rate).
Plugging in the values from the problem, we get:
Stock price = $2.21 / (0.13 - 0.117) = $34.15 per share.
Therefore, if your required rate of return is 13 percent, you should be willing to pay $34.15 per share to purchase stock in Railway Cabooses.

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I really need help im bad at Algebra

Answers

The line of best fit for the scatter plot is given as follows:

y = 2x.

How to define a linear function?

The slope-intercept representation of a linear function is given by the equation presented as follows:

y = mx + b

The coefficients of the function and their meaning are described as follows:

m is the slope of the function, representing the change in the output variable y when the input variable x is increased by one.b is the y-intercept of the function, which is the initial value of the function, i.e., the numeric value of the function when the input variable x assumes a value of 0. On a graph, it is the value of y when the graph of the function crosses the y-axis.

The graph touches the y-axis at the origin, hence the intercept b is given as follows:

b = 0.

Hence:

y = mx.

When x = 20, y = 40, hence the slope m is given as follows:

20m = 40

m = 40/20

m = 2.

Hence the equation is:

y = 2x.

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The following table gives the gold medal times for every other Summer Olympics for the women's 100 meter freestyle (swimming).
Year Time (seconds)
1912 82.2
1924 72.4
1932 66.8
1952 66.8
1960 61.2
1968 60.0
1976 55.65
1984 55.92
1992 54.64
2000 53.8
2008 53.1
d) Calculate the least squares line. Put the equation in the form of: ŷ = a + bx. (Round your answers to three decimal places.)
ŷ =____+____x
e) Find the correlation coefficient r. (Round your answer to four decimal places.)
r = ______
f) Find the estimated gold medal time for 1924. (Use your equation from part (d). Round your answer to two decimal places.)
_____ sec
Find the estimated gold medal time for 1992. (Use your equation from part (d). Round your answer to two decimal places.)
_____ sec
i) Use the least squares line to estimate the gold medal time for the 2012 Summer Olympics. (Use your equation from part (d). Round your answer to two decimal places.)
_____ sec

Answers

d) Least squares line ŷ = 521.2542 - 0.2349x.

e) Correlation coefficient r ≈ -0.9869

f) Estimated gold medal time ŷ for 1924 ≈ 71.26 sec

g) Estimated gold medal time ŷ for 1992 ≈ 53.14 sec

h) Estimate the gold medal time for the 2012 ŷ ≈ 52.12 sec

How to calculate each part of the question?

d) To find the least squares line, we need to calculate the mean and standard deviation of the year (x) and the time (y):

mean of x = (1912 + 1932 + 1952 + 1968 + 1976 + 1984 + 2000 + 2012)/8 = 1972

mean of y = (82.2 + 72.4 + 66.8 + 66.8 + 61.2 + 60.0 + 55.6 + 55.9 + 54.6 + 53.8 + 53.1)/11 = 63.2

standard deviation of x = √(((1912-1972)² + (1932-1972)² + ... + (2012-1972)²)/8) ≈ 44.54

standard deviation of y = √(((82.2-63.2)² + (72.4-63.2)² + ... + (53.1-63.2)²)/10) ≈ 10.53

Then, we can calculate the correlation coefficient r:

r = (1/10) * (((1912-1972)/44.54)(82.2-63.2)/10.53 + ((1932-1972)/44.54)(72.4-63.2)/10.53 + ... + ((2012-1972)/44.54)*(53.1-63.2)/10.53) ≈ -0.9869

Using the formula for the least squares regression line, we have:

b = r * (standard deviation of y / standard deviation of x) ≈ -0.2349

a = mean of y - b * mean of x ≈ 521.2542

Therefore, the least squares line is ŷ = 521.2542 - 0.2349x.

f) To estimate the gold medal time for 1924, we substitute x = 1924 into the equation for the least squares line:

ŷ = 521.2542 - 0.2349(1924) ≈ 71.26 sec

g) To estimate the gold medal time for 1992, we substitute x = 1992 into the equation for the least squares line:

ŷ = 521.2542 - 0.2349(1992) ≈ 53.14 sec

h) To estimate the gold medal time for 2012, we substitute x = 2012 into the equation for the least squares line:

ŷ = 521.2542 - 0.2349(2012) ≈ 52.12 sec

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At a price of one dollar, 200 units are demanded, and at a price of $9, zero units are demanded. If the demand equation is linear, x is the price and D is the number of units, the demand equation is: a. D=-.04x +.36 b.D= -25x +225 c.D=-.04x + 8 d. D = 25x + 175

Answers

The demand equation is  b. D = -25x + 225.

Since the demand equation is linear and involves "x" as the price, and "D" as the number of units, we can use the two points given to determine the equation.

At a price of $1, 200 units are demanded: (1, 200)
At a price of $9, 0 units are demanded: (9, 0)

Now, we can find the slope (m) using the formula:

m = (y2 - y1) / (x2 - x1)

In this case:

m = (0 - 200) / (9 - 1)
m = -200 / 8
m = -25

Now, we can use one of the points (either point will give the same result) to find the y-intercept (b) by plugging the values into the linear equation:

D = m * x + b

Using the point (1, 200):

200 = -25 * 1 + b
b = 200 + 25
b = 225

Now, we have the demand equation:

D = -25x + 225

So the correct answer is: b. D = -25x + 225.

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Consider the random variable X having pdf fX (x) = .6 (x^2/β), for 0 < x ≤1. (a) Find the value of β that makes fX (x) a valid pdf. (b) Find the cdf for the random variable X. (c) Find the probability that the random variable X is greater than 2.

Answers

(a) The value of β that makes fX(x) a valid pdf is β = 0.2.

(b) The cdf for the random variable X is FX(x) = (3[tex]x^3[/tex]/10), for 0 < x ≤ 1.

(c) The probability that the random variable P(X > 2) = 0, since the range of possible values for X is from 0 to 1.

How to find the value of β?

To find the value of β that makes fX(x) a valid pdf, we need to ensure that the area under the pdf from 0 to 1 is equal to 1.

∫0¹ fX(x) dx = ∫0¹ 0.6(x²/β) dx = 0.6/β ∫0¹ x² dx = 0.6/β [[tex]x^3[/tex]/3]0¹ = 0.6/β * (1/3) = 1

Solving for β, we get:

0.6/β * (1/3) = 1

β = 0.6/3 = 0.2

Therefore, β = 0.2 makes fX(x) a valid pdf.

How to find the cdf for random variable?

To find the cdf for the random variable X, we integrate the pdf from 0 to x:

FX(x) = ∫[tex]0^x[/tex] fX(t) dt = ∫[tex]0^x[/tex] 0.6(t²/0.2) dt = 3[tex]t^3[/tex]/10|[tex]0^x[/tex] = (3[tex]x^3[/tex]/10) - 0

Therefore, the cdf for X is:

FX(x) = (3[tex]x^3[/tex]/10), for 0 < x ≤ 1

How to find the probability?

To find the probability that X is greater than 2, we need to use the fact that the probability of an event outside the sample space is 0. Since the range of possible values for X is from 0 to 1, the probability that X is greater than 2 is 0.

P(X > 2) = 0

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A computer password consists of eleven characters. Replications are allowed. Part 1 of 5 (a) How many different passwords are possible if each character may be any lowercase letter or digit? Enter your answer in scientific notation with two digit of accuracy after the decimat point. The possible number of different passwords is ____.

Answers

The possible number of different passwords in scientific notation with two digits of accuracy after the decimal point for the computer is 3.42 x 10^14.

To find the number of different passwords possible, given that, each character may be any lowercase letter or digit, we must first determine the total number of available characters.

There are 26 lowercase letters and 10 digits, so there are a total of 26 + 10 = 36 available characters.

Since replications are allowed and the password consists of 11 characters, we can use the formula:

Number of different passwords = (Total number of available characters) ^ (Password length)

Number of different passwords = 36 ^ 11

Calculating this value, we get 341,821,345,910,986. To represent this number in scientific notation with two digits of accuracy after the decimal point, we divide by 10 raised to the power of the number of digits minus 1:

341,821,345,910,986 / 10^14 = 3.42 x 10^14

So, the possible number of different passwords for a computer consisting of eleven characters is 3.42 x 10^14.

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Thinking about t distributions. Consider the t (20) and t (40) distributions. a. Which distribution is wider? b. For the same value of t, which distribution has the smallest tail area? c. For the same middle area C, which distribution has the largest t* critical value?

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The t(20) distribution is wider than the t(40) distribution, For the same value of t, the t(40) distribution has the smallest tail area and for the same middle area C, the t(20) distribution has the largest t* critical value.

a. Which distribution is wider?
The t(20) distribution is wider than the t(40) distribution. As the degrees of freedom increase, the t distribution approaches the standard normal distribution, and its width decreases.
b. For the same value of t, which distribution has the smallest tail area?
For the same value of t, the t(40) distribution has the smallest tail area. As the degrees of freedom increase, the distribution becomes more concentrated around the mean, and the tails become smaller.
c. For the same middle area C, which distribution has the largest t* critical value?
For the same middle area C, the t(20) distribution has the largest t* critical value. With fewer degrees of freedom, the distribution is wider and requires a larger t* value to cover the same middle area as compared to the t(40) distribution.

a. The t(40) distribution is wider than the t(20) distribution. This is because as the degrees of freedom increase, the t-distribution approaches a standard normal distribution, which has a smaller variance than the t-distribution with fewer degrees of freedom.
b. For the same value of t, the t(40) distribution has the smallest tail area. This is because as the degrees of freedom increase, the t-distribution approaches a standard normal distribution, which has smaller tail areas than the t-distribution with fewer degrees of freedom.
c. For the same middle area C, the t(20) distribution has the largest t* critical value. This is because as the degrees of freedom decrease, the t-distribution has heavier tails, which require larger t* values to maintain the same middle area C.

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find the area under the standard normal curve to the left of z=1.43z=1.43. round your answer to four decimal places, if necessary.

Answers

To find the area under the standard normal curve to the left of z=1.43, you will need to use a standard normal (Z) table or an online calculator. Here's a step-by-step explanation:

1. Identify the given value of z: z=1.43
2. Look up the value in a standard normal (Z) table or use an online calculator to find the corresponding area to the left of z=1.43.
3. The table or calculator will provide the area under the curve to the left of z=1.43.
4. Round the answer to four decimal places, if necessary.

Using a standard normal table or calculator, the area under the standard normal curve to the left of z=1.43 is approximately 0.9236 when rounded to four decimal places.

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Let Q be the quantity Q = 110(1.137)' which is changing over timet. a. What is the quantity at time t=0? b. Is the quantity increasing or decreasing over time? c. What is the percent per unit time growth or decay rate? % growth per unit time d. Is the growth rate continuous?

Answers

a)The quantity at time t=0 is  110.

b)The quantity is increasing over time .

c) The percent per unit time growth or decay rate is 11.1% .

d)Yes, the growth rate continuous.

a. At time t=0, the quantity Q can be found using the given formula Q = 110(1.137[tex])^{2}[/tex].

  Plugging in t=0, we get.

  Q = 110(1.137[tex])^{0}[/tex]

      = 110(1) = 110.

b. The quantity is increasing over time because the base (1.137) in the formula is greater than 1, which means that Q grows as time (t) increases.

c. The percent per unit time growth rate can be found by taking the derivative of the function and dividing by the initial quantity:

dQ/dt = 110(1.137[tex])^{t}[/tex]* ln(1.137)
dQ/dt at t=0 = 110(1.137[tex])^{0}[/tex] * ln(1.137) = 12.2

% growth per unit time = (dQ/dt)/Q * 100% = 12.2/110 * 100% = 11.1%


d. The growth rate is continuous, as it follows an exponential growth pattern described by the formula Q = 110(1.137)^t, where the base is constant and the time variable is continuous.

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The following series are geometric series or a sum of two geometric series. Determine whether each series converges or not. For the series which converge, enter the sum of the series. For the series which diverges enter "DIV" (without quotes). (a) ∑n=1[infinity]8n7n= , (b) ∑n=2[infinity]13n= , (c) ∑n=0[infinity]3n92n+1= , (d) ∑n=5[infinity]7n8n= , (e) ∑n=1[infinity]7n7n+4= , (f) ∑n=1[infinity]7n+3n8n=

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(a) ∑n=1[infinity]8n7n is a geometric series and it diverges. Answer: DIV.

(b) ∑n=2[infinity]13n is a geometric series and it diverges. Answer: DIV.

(c) ∑n=0[infinity]3n92n+1 is a geometric series and it converges. Sum = 2.452.

(d) ∑n=5[infinity]7n8n is a geometric series and it converges. Sum = 0.0954.

(e) ∑n=1[infinity]7n7n+4 is a geometric series and it converges. Sum = 3.5

(f) ∑n=1[infinity] 7/8*[tex](7/8)^{(n-1)[/tex] + [tex]3/8*(3/8)^{(n-1)[/tex]. Both of these are geometric series and the series converges. Sum= 1.6.

(a) This series can be rewritten as ∑n=1[infinity][tex](8/7)^n[/tex]. This is a geometric series with ratio r=8/7 which is greater than 1. Hence, the series diverges. Answer: DIV.

(b) This is a geometric series with first term a=13 and common ratio r=13. Since |r|>1, the series diverges. Answer: DIV.

(c) This series can be written as ∑n=0[infinity] [tex]3^n/(9^2)^n[/tex] * [tex]9^{(1/(2n+1))[/tex]. The first part of the series is a geometric series with a=1 and r=3/81<1. The second part of the series is also a geometric series with a=[tex]9^{(1/3)[/tex] and r=[tex](9^{(1/3)})^2=9^{(2/3)[/tex]<1. Therefore, the series converges. To find the sum, we use the formula for the sum of an infinite geometric series:

sum = a/(1-r) + b/(1-c)

where a and r are the first term and common ratio of the first geometric series, and b and c are the first term and common ratio of the second geometric series. Substituting the values, we get:

sum = 1/(1-3/81) + [tex]9^{(1/3)}/(1-9^{(2/3))[/tex]

= 1.01 + 1.442

= 2.452

Answer: 2.452.

(d) This series can be written as ∑n=5[infinity] [tex](7/8)^n[/tex]. This is a geometric series with ratio r=7/8 which is less than 1. Hence, the series converges. To find the sum, we use the formula for the sum of an infinite geometric series:

sum = a/(1-r)

where a and r are the first term and common ratio of the series. Substituting the values, we get:

sum = [tex](7/8)^5/(1-7/8)[/tex]

= [tex]7/8^4[/tex]

= 0.0954

Answer: 0.0954.

(e) This series can be rewritten as ∑n=1[infinity] [tex](7/7.4)^n[/tex]. This is a geometric series with ratio r=7/7.4<1. Hence, the series converges. To find the sum, we use the formula for the sum of an infinite geometric series:

sum = a/(1-r)

where a and r are the first term and common ratio of the series. Substituting the values, we get:

sum = 1/(1-7/7.4)

= 3.5

Answer: 3.5.

(f) This series can be rewritten as ∑n=1[infinity] [tex]7/8*(7/8)^{(n-1)[/tex] + [tex]3/8*(3/8)^{(n-1)[/tex]. Both of these are geometric series with ratios less than 1, so the series converges. To find the sum, we add the sums of the two geometric series:

sum = 7/8/(1-7/8) + 3/8/(1-3/8)

= 1 + 3/5

= 1.6

Answer: 1.6.

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suppose x is χ2 - distribution with degrees of 20. find a point a such that p(x < a) = 0.025

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For X following a χ²-distribution with 20 degrees of freedom, the point 'a' such that P(X < a) = 0.025 is approximately 8.26.

To find the point 'a' such that P(X < a) = 0.025, where X follows a χ²-distribution with 20 degrees of freedom, you need to use the inverse chi-square distribution function (also called the chi-square quantile function).

Here's the step-by-step explanation:

1. Identify the given parameters: X follows a χ²-distribution with 20 degrees of freedom, and we need to find a point 'a' such that P(X < a) = 0.025.

2. Use the inverse chi-square distribution function (quantile function) with the given probability and degrees of freedom. This function will give you the value of 'a' corresponding to the specified probability.

In most statistical software or calculators, you can find this function. For example, in R programming, you can use the "qchisq()" function:

a = qchisq(0.025, df = 20)

3. Calculate the value of 'a'.

In this case, a ≈ 8.26.

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Consider the following recursive definition of the Lucas numbers L(n): 1 if n=1 L(n)= 3 if n = 2 Lon - 1) + L(n-2) if n>2 What is L(2)? Your Answer: Answer

Answers

The value of L(2) is for recursive definition of Lucas numbers is 3.

According to the given recursive definition of the Lucas numbers, L(2) = 3 since n=2 is the second term in the sequence and its value is defined as 3.
Based on the recursive definition of Lucas numbers L(n) given, let's determine the value of L(2):

L(n) = 1 if n = 1
L(n) = 3 if n = 2
L(n) = L(n - 1) + L(n - 2) if n > 2

Since we're looking for L(2), we can use the second condition in the definition:

L(2) = 3

So, the value of L(2) is 3.

A set of numbers called the Lucas numbers resembles the Fibonacci sequence. The series was researched in the late 19th century by the French mathematician François Édouard Anatole Lucas, who gave it its name.

This is how the Lucas sequence is described:

For n > 1, L(0) = 2 L(1) = 1 L(n) = L(n-1) + L(n-2)

The sequence's initial few numerals are thus:

2, 1, 3, 4, 7, 11, 18, 29, 47, 76, 123, 199, 322, ...

The Lucas sequence, like the Fibonacci sequence, offers a variety of intriguing mathematical characteristics and linkages to different branches of mathematics. For instance, exactly like in the Fibonacci sequence, the ratio of successive Lucas numbers converges to the golden ratio[tex](1 + \sqrt{5})/2[/tex].

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Let S2 = {a = (a1,a2,a3) ∈ R3 | a1a2 + 2a3 = 0}. If y = (y1,y2,y3) ∈ S2 and z = (z1,z2,z3) ∈ S2, is y + z ∈ S2? Justify your answer.

Answers

The answer is yes, y + z ∈ S2.

We need to determine whether the sum of two vectors in S2, y + z, is also in S2.

Let y = (y1, y2, y3) and z = (z1, z2, z3) be two vectors in S2. Then, we know that:

y1y2 + 2y3 = 0 (since y ∈ S2)

z1z2 + 2z3 = 0 (since z ∈ S2)

To show that y + z ∈ S2, we need to show that:

(y + z)1(y + z)2 + 2(y + z)3 = 0

Expanding the left-hand side, we have:

(y1 + z1)(y2 + z2) + 2(y3 + z3) = y1y2 + y1z2 + z1y2 + z1z2 + 2y3 + 2z3

Substituting the expressions for y1y2 + 2y3 and z1z2 + 2z3 from above, we get:

(y1y2 + 2y3) + (z1z2 + 2z3) + y1z2 + z1y2 = 0

Since y1y2 + 2y3 = 0 and z1z2 + 2z3 = 0, we have:

y1z2 + z1y2 = 0

Therefore, we have shown that (y + z)1(y + z)2 + 2(y + z)3 = 0, which implies that y + z ∈ S2.

Hence, the answer is yes, y + z ∈ S2.

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A village with 82people is hit by malaria. The government decides to give one net to each one of them. If 2 nets remained,how many packages of nets of six were taken to the villages?

Answers

14 packages of nets of six were taken to the village. If there are 82 people in the village, then 82 nets are needed to provide one net to each person.

However, we also know that there are 2 nets remaining, which means that a total of 82 + 2 = 84 nets were provided.

To determine how many packages of nets of six were taken to the village, we can divide the total number of nets by 6, and round up to the nearest whole number since we can't have a partial package of nets:

84 nets / 6 nets per package = 14 packages (rounded up)

Therefore, 14 packages of nets of six were taken to the village.

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Let V be a vector space, and T:V→V a linear transformation such that T(5v⃗ 1+3v⃗ 2)=−5v⃗ 1+5v⃗ 2 and T(3v⃗ 1+2v⃗ 2)=−5v⃗ 1+2v⃗ 2. Then
T(v⃗ 1)=
T(v⃗ 2)=
T(4v⃗ 1−4v⃗ 2)=

Answers

Let V be a vector space, and T:V→V a linear transformation then the value of T(v⃗ 1) = -v⃗ 1, T(v⃗ 2) = v⃗ 2 and T(4v⃗ 1 − 4v⃗ 2) = -4v⃗ 1 - 4v⃗ 2.

We can use the given information to find the value of T for various vectors in V and T:V→V a linear transformation such that T(5v⃗ 1+3v⃗ 2)=−5v⃗ 1+5v⃗ 2 and T(3v⃗ 1+2v⃗ 2)=−5v⃗ 1+2v⃗ 2.

For 5v⃗ 1 + 3v⃗ 2, we have:

T(5v⃗ 1+3v⃗ 2) = −5v⃗ 1+5v⃗ 2

5T(v⃗ 1) + 3T(v⃗ 2) = -5v⃗ 1 + 5v⃗ 2

Similarly, for 3v⃗ 1 + 2v⃗ 2, we have

T(3v⃗ 1+2v⃗ 2) = −5v⃗ 1+2v⃗ 2

3T(v⃗ 1) + 2T(v⃗ 2) = -5v⃗ 1 + 2v⃗ 2

Solving these equations for T(v⃗ 1) and T(v⃗ 2), we get

T(v⃗ 1) = -v⃗ 1

T(v⃗ 2) = v⃗ 2

Now, we can use these values to find T(4v⃗ 1 − 4v⃗ 2)

T(4v⃗ 1 − 4v⃗ 2) = 4T(v⃗ 1) - 4T(v⃗ 2)

= 4(-v⃗ 1) - 4(v⃗ 2)

= -4v⃗ 1 - 4v⃗ 2

Therefore, T(4v⃗ 1 − 4v⃗ 2) = -4v⃗ 1 - 4v⃗ 2.

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Which of the following is the definition for combination?
OA. A set of objects chosen from a smaller set in which the order of
the objects doesn't matter.
B. A set of objects chosen from a larger set in which the order of the
objects matters.
OC. A set of objects chosen from a larger set in which the order of the
objects doesn't matter.
OD. A set of objects chosen from a smaller set in which the order of
the objects matters.

Answers

Answer:

C. A set of objects chosen from a larger set in which the order of the objects doesn't matter.

Step-by-step explanation:

That is the definition of a combination. Order does not matter

For example, selecting 3 students from a total of 10 students. The set selected is a smaller set from a larger set

Policyholders of a certain insurance company have accidents at times distributed according to a Poisson process with rate λ. The amount of time from when the accident occurs until a claim is made has distribution G.
(a) Find the probability there are exactly n incurred but as yet unreported claims at time t.
(b) Suppose that each claim amount has distribution F, and that the claim amount is independent of the time that it takes to report the claim. Find the expected value of the sum of all incurred but as yet unreported claims at time t.

Answers

a. The expected value of the sum of all incurred but as yet

b. Unreported claims at time t is λt times the expected value of a single claim amount.

What is probability?

Probability is a branch of mathematics that deals with measuring the likelihood of an event occurring. It involves quantifying the chances of different outcomes of a random experiment, such as flipping a coin, rolling a die, or drawing a card from a deck.

According to the given information:

(a) Let N(t) be the number of claims incurred up to time t, and let S be the set of times when claims are incurred but not yet reported. Then, the probability that there are exactly n incurred but as yet unreported claims at time t is given by:

P(N(t) - |S| = n) = P(N(t) = n + |S|) × P(|S|)

Since the occurrence of claims follows a Poisson process with rate λ, the probability of n + |S| claims in time t is:

P(N(t) = n + |S|) = ( + |S| / (n + |S|)!)

The distribution of the time until a claim is reported, G, gives the probability that a claim is reported within some time interval after it is incurred. The probability that a claim is incurred but not reported by time t is given by:

P(|S|) = P(G > t)

Putting all these pieces together, we get:

P(N(t) - |S| = n) = ( + |S| / (n + |S|)!) ×) × P(G > t)

(b) Let X_i denote the claim amount for the i-th incurred but as yet unreported claim. Then, the total claim amount for all incurred but as yet unreported claims at time t is:

Y(t) = Σ_i= - |S| X_i

We can find the expected value of Y(t) by using the law of total expectation:

E(Y(t)) = E[E(Y(t) | N(t), S)]

Given N(t) and S, the expected value of Y(t) is just the sum of the expected values of the claim amounts for the unreported claims:

E(Y(t) | N(t), S) = Σ_i= E(X_i)

Since the claim amounts are independent and identically distributed according to F, we have:

E(X_i) = E(F)

Thus, we get:

E(Y(t)) = E[E(Y(t) | N(t), S)] = E[(n + |S|)E(F)] = λt × E(F)

Therefore, the expected value of the sum of all incurred but as yet unreported claims at time t is λt times the expected value of a single claim amount.

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