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julsineya [31]
2 years ago
7

Compute the integral (a) int sin (pi x) dx by letting u = pi x. (b) int e^(x/2) dx by letting u = x/2. Show that you got the cor

rect answer by differentiating the computed function.
Mathematics
1 answer:
Maslowich2 years ago
3 0

Answer:

(a) \int sin(\pi x) dx=-\frac {cos \pi x}{\pi}+c

(b)\int e^\frac{x}{2} dx =2e^\frac{x}{2}+c

Step-by-step explanation:

(a)

\int sin(\pi x) dx

Let u = π x

differentiating with respect to x

du = π dx

\Rightarrow dx=\frac{du}{\pi}

Putting the value of x and dx

=\int sin u \frac{du}{\pi}

=\frac{-cos u}{\pi}+c    [ c is an arbitrary constant]

Now putting the value of u

=-\frac {cos \pi x}{\pi}+c  

(b)

\int e^\frac{x}{2} dx

Let u=\frac{x}{2}

differentiating with respect to x

du= \frac{1}{2} dx

2du = dx

Putting the value of x and dx

=\int e^u.2.du

=2e^u +c

Now putting the value of u

=2e^\frac{x}{2}+c       [ c is an arbitrary constant]

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Company F sells fabrics known as fat quarters, which are rectangles of fabric created by cutting a yard of fabric into four piec
jeka94

Answer:

a) Y 0 1 2

P(Y) 0.58 0.23 0.11

b) mean= 0.45, S.D= 0.6718

c) mean= 1.285, S.D= 8.74

Step-by-step explanation:

a) The following table shows the probability distribution of X:

X 0 1 2 3 4 or more

P(X) 0.58 0.23 0.11 0.05 0.03

Defect >2 = cannot be sold

Y = the number of defects on a fat quarter that can be sold by Company F.

Y = defect that can be sold

Y = Defect less or equal to 2 = 0,1,2

Probability distribution of the random variable Y:

Y 0 1 2

P(Y) 0.58 0.23 0.11

b) mean of Y (μ)

μ = Σ x*P(Y)

= (0*0.58) +(1*0.23)+(2*0.11)

= 0+0.23+0.22 = 0.45

Standard deviation of Y = σ

σ = Σ√(x-mean)^2*P(Y)

= Σ√[(x- μ )^2*P(Y)]

= √[(0-0.45)^2*0.58+ (1-0.45)^2*0.23 + (2-0.45)^2*0.11]

= √[0.11745 + 0.069575 +0.264275

= √(0.4513

σ = 0.6718

Company G:

σ for defect that be sold = 0.66

μ for defect that be sold = 0.40

Difference between μ of F and μ of G

= 0.45-0.40 = 0.05

Difference between σ of F and σ of G

= 0.67-0.66 = 0.01

Selling price of fat quarter without defect = $5

Discount per defect = $1.5

Selling price per defect = 5-1.5 = $3.5

Discount per 2 defect = $1.5*2 = $3

Selling price per defect = 5-3 = $2

Since defect to be sold cannot be greater than 2, let Y = 5,3,2

Probability distribution of the selling price Y:

Y 5 3 2

P(Y) 0.58 0.23 0.11

μ = (5*0.58) +(3.5*0.23)+(2*0.11)

μ = 2.9+0.805+0.22 =1.285

σ = Σ√[(x- μ )^2*P(Y)]

σ = √[(5-1.285)^2*0.58+ (3-1.285)^2*0.23 + (2-1.285)^2*0.11]

σ = 8.00+0.68+0.06 = 8.74

7 0
2 years ago
Jackson goes to the gym 0, 2, or 3 days per week, depending on work demands. The expected value of the number of days per week t
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For a probability distribution the expected value is the summation of product of probabilities with their respective data values. Let x be the probability that Jackson goes gym for 2 days and y be the probability that he goes gym for 3 days.

For the given case we have following values and their probabilities:

0 : 0.1

2 : x

3 : y

So the expected value will be = 0(0.1) + 2(x) + 3(y)

Expected value is given to be 2.05. So we can write the equation as:

2x + 3y = 2.05 (Equation 1)

Also for a probability distribution, the sum of probabilities must always equal to 1. So we can set up the second equation as:

0.1 + x + y = 1

x + y = 0.9 (Equation 2)

From Equation 2 we can write the value of x to be x = 0.9 - y. Using this value in equation 1, we get:

2(0.9 - y) + 3y = 2.05

1.8 - 2y + 3y = 2.05

1.8 + y = 2.05

y = 0.25

Using the value of y in equation 2 we get value of x to be 0.65

Therefore we can conclude that:

The probability that Jackson goes to gym for 2 days is 0.65 and the probability that he goes to gym for 3 days is 0.25

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Answer:

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Step-by-step explanation:

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Which of the following is a counterexample for this conditional statement?
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Imagine you have a data set with 9,987 names. The data set is sorted alphabetically. You want to find out if the name "David Joy
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