Analyzing a Continuous Random Variable in a Coin-Operated Target Game

In summary: I'm not sure where you're getting stuck - the calculations seem to be correct. The expected distance between a point target and a shot aimed is 1.125.
  • #1
toothpaste666
516
20

Homework Statement


Suppose the distance X between a point target and a shot aimed at the point in a coin-operated target game is a continuous random variable with pdf

f(x) = { k(1−x^2), −1≤x≤1
0, otherwise.

(a) Find the value of k.

(b) Find the cdf of X.

(c) Compute P (−.5 < X ≤ .5).

(d) Find the expected distance between a point target and a shot aimed.

The Attempt at a Solution


a) [itex] k\int_{-1}^1(1-x^2)dx [/itex]

[itex]= k[\int_{-1}^1dx-\int_{-1}^1x^2dx] [/itex]

[itex]= k[x\Big|_{-1}^1-\frac{1}{3}x^3\Big|_{-1}^1] [/itex]

= k(2-2/3) = 1

k(4/3) = 1

k = 3/4b) [itex] \frac{3}{4} \int_{-1}^X(1-x^2)dx [/itex]c) [itex] \frac{3}{4}[x\Big|_{-.5}^{.5}-\frac{1}{3}x^3\Big|_{-.5}^{.5}] [/itex]

= (3/4)(1-(1/3)[2(1/3)(1/8)])

= (3/4)(1-1/36)
= .7292

d) [itex] \frac{3}{4}\int_{-1}^1x(1-x^2)dx [/itex]

[itex] =\frac{3}{4}\int_{-1}^1(x-x^3)dx [/itex]

[itex]= \frac{3}{4}[\int_{-1}^1xdx-\int_{-1}^1x^3dx] [/itex]

[itex]= \frac{3}{4}[\frac{1}{2}x^2\Big|_{-1}^1-\frac{1}{4}x^4\Big|_{-1}^1] [/itex]

= 0am I doing this right?
 
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  • #2
For b), instead of expressing the cdf as an integral, you should actually carry out the integration and express the cdf as a function of X.
 
  • #3
toothpaste666 said:

Homework Statement


Suppose the distance X between a point target and a shot aimed at the point in a coin-operated target game is a continuous random variable with pdf

f(x) = { k(1−x^2), −1≤x≤1
0, otherwise.

(a) Find the value of k.

(b) Find the cdf of X.

(c) Compute P (−.5 < X ≤ .5).

(d) Find the expected distance between a point target and a shot aimed.

The Attempt at a Solution


a) [itex] k\int_{-1}^1(1-x^2)dx [/itex]

[itex]= k[\int_{-1}^1dx-\int_{-1}^1x^2dx] [/itex]

[itex]= k[x\Big|_{-1}^1-\frac{1}{3}x^3\Big|_{-1}^1] [/itex]

= k(2-2/3) = 1

k(4/3) = 1

k = 3/4b) [itex] \frac{3}{4} \int_{-1}^X(1-x^2)dx [/itex]c) [itex] \frac{3}{4}[x\Big|_{-.5}^{.5}-\frac{1}{3}x^3\Big|_{-.5}^{.5}] [/itex]

= (3/4)(1-(1/3)[2(1/3)(1/8)])

= (3/4)(1-1/36)
= .7292

d) [itex] \frac{3}{4}\int_{-1}^1x(1-x^2)dx [/itex]

[itex] =\frac{3}{4}\int_{-1}^1(x-x^3)dx [/itex]

[itex]= \frac{3}{4}[\int_{-1}^1xdx-\int_{-1}^1x^3dx] [/itex]

[itex]= \frac{3}{4}[\frac{1}{2}x^2\Big|_{-1}^1-\frac{1}{4}x^4\Big|_{-1}^1] [/itex]

= 0am I doing this right?

Not for (d), no. You computed ##E X##, but what is wanted is ##E |X|##. Also, I get a different answer for (c).
 
  • #4
for part b)
[itex] F(X) = \frac{3}{4}[x\Big|_{-1}^X-\frac{1}{3}x^3\Big|_{-1}^X] [/itex]

[itex] F(X) = \frac{3}{4} [(X+1) - \frac{1}{3} (X^3 +1)] [/itex]

[itex] F(X) = \frac{3}{4}[X + 1 - \frac{X^3}{3} - \frac{1}{3}] [/itex]

[itex] F(X) = \frac{3}{4}[X - \frac{X^3}{3} + \frac{2}{3}] [/itex]

[itex] F(X) = \frac{3X}{4} - \frac{X^3}{4} + \frac{1}{2} [/itex]

part c) I made a arithmetic error. it comes down to (3/4)(11/12) = .6875

part d)
I am not quite sure how to do this. plugging in |x| wherever there is an x gives me the same answer. should I switch the limits of integration from 0 to 2 instead of -1 to 1?
 
  • #5
toothpaste666 said:
for part b)
[itex] F(X) = \frac{3}{4}[x\Big|_{-1}^X-\frac{1}{3}x^3\Big|_{-1}^X] [/itex]

[itex] F(X) = \frac{3}{4} [(X+1) - \frac{1}{3} (X^3 +1)] [/itex]

[itex] F(X) = \frac{3}{4}[X + 1 - \frac{X^3}{3} - \frac{1}{3}] [/itex]

[itex] F(X) = \frac{3}{4}[X - \frac{X^3}{3} + \frac{2}{3}] [/itex]

[itex] F(X) = \frac{3X}{4} - \frac{X^3}{4} + \frac{1}{2} [/itex]

part c) I made a arithmetic error. it comes down to (3/4)(11/12) = .6875

part d)
I am not quite sure how to do this. plugging in |x| wherever there is an x gives me the same answer. should I switch the limits of integration from 0 to 2 instead of -1 to 1?

No. Without doing any calculations you can see why ##EX = 0##: it is because ##x f(x)## is an odd function on ##[-1,1]## so integrates to zero automatically. That is NOT the case for ##|x| f(x)##, because this not now an odd function on ##[-1,1]##. I won't say any more.
 
  • #6
d) [itex] \frac{3}{4}\int_{-1}^1|x|(1-x^2)dx [/itex]

[itex] =\frac{3}{4}\int_{-1}^1(|x|-|x|x^2)dx [/itex]

[itex]= \frac{3}{4}[\int_{-1}^1|x|dx-\int_{-1}^1|x|x^2dx] [/itex]

[itex]= \frac{3}{4}[-\int_{-1}^0xdx + \int_0^1xdx-\int_{-1}^0x^3dx + \int_0^1x^3dx] [/itex]

[itex]= \frac{3}{4}[-\frac{1}{2}x^2\Big|_{-1}^0 +\frac{1}{2}x^2\Big|_0^1-\frac{1}{4}x^4\Big|_{-1}^0 +\frac{1}{4}x^4\Big|_0^1] [/itex]

= (3/4) [(1/2) + (1/2) + (1/4) + (1/4)]
= (3/4)(3/2) = 9/8 = 1.125
 
  • #7
toothpaste666 said:
d) [itex] \frac{3}{4}\int_{-1}^1|x|(1-x^2)dx [/itex]

[itex] =\frac{3}{4}\int_{-1}^1(|x|-|x|x^2)dx [/itex]

[itex]= \frac{3}{4}[\int_{-1}^1|x|dx-\int_{-1}^1|x|x^2dx] [/itex]

[itex]= \frac{3}{4}[-\int_{-1}^0xdx + \int_0^1xdx-\int_{-1}^0x^3dx + \int_0^1x^3dx] [/itex]

[itex]= \frac{3}{4}[-\frac{1}{2}x^2\Big|_{-1}^0 +\frac{1}{2}x^2\Big|_0^1-\frac{1}{4}x^4\Big|_{-1}^0 +\frac{1}{4}x^4\Big|_0^1] [/itex]

= (3/4) [(1/2) + (1/2) + (1/4) + (1/4)]
= (3/4)(3/2) = 9/8 = 1.125

This cannot possibly be right: ##|X| \leq 1## for all non-zero probability values, so ##E|X| \leq 1## (and, in fact, ##E|X| < 1## strictly).
 
  • #8
in that case I am lost =[
 

Related to Analyzing a Continuous Random Variable in a Coin-Operated Target Game

1. What is a continuous random variable?

A continuous random variable is a type of variable in statistics that can take on an infinite number of values within a specific range. It is typically represented by a real number and can have any value within its range.

2. How is a continuous random variable different from a discrete random variable?

A discrete random variable can only take on a finite or countably infinite number of values, while a continuous random variable can take on any value within its range. In other words, a discrete random variable can only have specific values, while a continuous random variable can have any value within a certain range.

3. What is the probability density function of a continuous random variable?

The probability density function (PDF) of a continuous random variable is a function that describes the probability of a random variable taking on a specific value within a range. It is represented by a curve on a graph and the total area under the curve is equal to 1.

4. How is the mean of a continuous random variable calculated?

The mean of a continuous random variable is calculated by multiplying each possible value of the variable by its corresponding probability and then summing all of these products. This is also known as the expected value of the random variable.

5. Can a continuous random variable have a probability of 0?

Yes, it is possible for a continuous random variable to have a probability of 0 for a specific value. This means that the likelihood of the variable taking on that value is extremely low, but not impossible.

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