Getting the probability distribution of a random variable

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The discussion focuses on calculating the probability distribution, mean, and variance of the discrete random variable Y based on its joint distribution with X. The user successfully computed probabilities for various values of Y, including Pr(Y = 14) = 0.21 and Pr(Y = 22) = 0.23. They seek clarification on how to apply the formula for calculating probabilities, specifically how to define the index i in the summation for Pr(Y = 14). The user proposes assigning values to x_i in a specific order and plans to replicate this method for Y. This exchange highlights the process of deriving probability distributions from joint distributions in statistics.
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Homework Statement
Described below
Relevant Equations
Marginal Probability Equation
X and Y are discrete random variables with the following joint distribution:
1723338968054.png

a) Calculate the probability distribution, mean, and variance of Y.

My attempt:

I have calculated the probability for different values of Y and X using the following equation: ##\text{Pr(Y = y)}## = ##\sum_{i=1}^l## ##\rm{Pr(X = x_i, Y = y)}##. I have arrived at some results, such as ##\text{Pr(Y = 14)} = 0.21##, ##\text{Pr(Y = 22)} = 0.23##, ##\text{Pr(Y = 30)} = 0.30##, ##\text{Pr(Y = 40)} =0.15## and ##\text{Pr(Y = 65)} = 0.11##.

However, I wanted to know how the formula above could be used in calculating the probabilities. What would be ##x_1##? What to put in i in an equation such as ##\text{Pr(Y = 14)}## = ##\sum_{i=?}^?## ##\rm{Pr(X = x_i, Y = 14)}##?
 
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With ##i## as a subscript of ##x## values, it should be ##i=1,2,3##. You can then assign the values of the ##x_i##s in whatever order you want. I would start from the top row to the bottom. ##x_1=1,\ x_2=5,\ x_3=8##.
 
Alright. I will do the same for Y so. Thanks.
 

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