Roll 2 fair dice, find pdf and cdf

In summary: The pdf is a graph showing the probability of each possible value of x. The x-axis represents the possible values of x, and the y-axis represents the probabilities. In this case, the graph would show a probability of 3/36 for x=0, 5/36 for x=2, 4, or 6, and 6/36 for x=1, 3, or 5. b) The cdf is a graph showing the cumulative probability of x from 0 to a certain value. The x-axis represents the possible values of x, and the y-axis represents the cumulative probability. In this case, the graph would show a probability of 0 for x<0,
  • #1
srk827
1
0
Hi guys. I have a test tomorrow and I am trying to work out the problems on the review sheet, but I can't figure out this one dealing with pdf and cdf.

Roll 2 fair dice and call each outcome (i,j) where i,j = 1,2,...6.
Define: X= {i+j if i+j ≤ 6 ; abs.value(i-j) otherwise}

A) Find and draw the pdf.
B) Find and draw the cdf.



The professor sent us the solutions. I just can't figure out how he got it. The solution he sent was:

a)
f(x)= { 3/36 if x=o; 5/36 if x=2 or 4 or 6; 6/36 if x=1 or 3 or 5}

b) f(x)= {0 if x<0; 3/36 if 0≤x<1; 9/36 if 1≤x<2; 14/36 if 2≤x<3; 20/36 if 3≤x<4; 25/36 if 4≤x<5; 31/36 if 5≤x<6; 1 if x≥6}

Could someone please help me understand the steps to take to get this answer?
 
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  • #2
srk827 said:
Hi guys. I have a test tomorrow and I am trying to work out the problems on the review sheet, but I can't figure out this one dealing with pdf and cdf.

Roll 2 fair dice and call each outcome (i,j) where i,j = 1,2,...6.
Define: X= {i+j if i+j ≤ 6 ; abs.value(i-j) otherwise}

A) Find and draw the pdf.
B) Find and draw the cdf.



The professor sent us the solutions. I just can't figure out how he got it. The solution he sent was:

a)
f(x)= { 3/36 if x=o; 5/36 if x=2 or 4 or 6; 6/36 if x=1 or 3 or 5}

b) f(x)= {0 if x<0; 3/36 if 0≤x<1; 9/36 if 1≤x<2; 14/36 if 2≤x<3; 20/36 if 3≤x<4; 25/36 if 4≤x<5; 31/36 if 5≤x<6; 1 if x≥6}

Could someone please help me understand the steps to take to get this answer?

First find the probabilities of all the individual pairs (i,j). For each pair (i,j), figure out what x must be. Of course, the same x might be obtained for several different pairs (i,j), so you need to be careful. That's it; that's all there is to it.

RGV
 

1. How do you calculate the probability distribution function (PDF) for rolling two fair dice?

To calculate the PDF for rolling two fair dice, you first need to determine the sample space, which consists of all possible outcomes. In this case, the sample space will contain 36 possible outcomes, as there are 6 possible outcomes for the first die and 6 possible outcomes for the second die. Once you have the sample space, you can calculate the probability of each outcome by dividing the number of outcomes by the total number of possible outcomes. The PDF will be a discrete function that assigns a probability to each possible outcome.

2. What is the cumulative distribution function (CDF) for rolling two fair dice?

The CDF for rolling two fair dice is a function that gives the probability that the sum of the two dice will be less than or equal to a given number. It is calculated by taking the sum of the probabilities of all outcomes up to and including the given number. For example, if you roll a 7, the CDF would be the sum of the probabilities of rolling a 2, 3, 4, 5, 6, and 7. The CDF for rolling two fair dice will be a step function, with jumps at each possible outcome.

3. What is the expected value for rolling two fair dice?

The expected value for rolling two fair dice is the sum of all possible outcomes multiplied by their respective probabilities. In other words, it is the average value that you would expect to get if you rolled the two dice an infinite number of times. For two fair dice, the expected value is equal to the sum of the numbers on the two dice, divided by 2. In this case, the expected value would be 7, as there are 36 possible outcomes and the sum of the numbers on the two dice is 252.

4. How do you interpret the PDF and CDF for rolling two fair dice?

The PDF and CDF for rolling two fair dice can be interpreted as tools for understanding the likelihood of different outcomes when rolling two dice. The PDF shows the probability of each individual outcome, while the CDF shows the probability of getting a result less than or equal to a given number. These functions can also be used to calculate the expected value and variance of the outcomes, and to determine the most likely and least likely outcomes.

5. Can the PDF and CDF be used for other types of dice or games?

Yes, the PDF and CDF can be used for any type of dice or game where the outcomes are discrete and have known probabilities. However, the sample space and probabilities will vary depending on the specific game. For example, if you are rolling two biased dice, the probabilities will be different and therefore the PDF and CDF will also be different. It is important to determine the sample space and probabilities before using these functions for other types of dice or games.

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