Random variable Consider the random variable X with probability distribution given in the table below X= x -1 1 2 3 5 6 P(X = x) 0.2 p(1) p(2) p(3) 0.2 p(6) Find the values for the missing probabilities for the outcomes X = 1, 2, 3, and 6 You are given the following relations between the unknown probabilities. The two least likely outcomes are X=1 and X=6, and these have the same probability. ( p(1) = p(6) ) The outcome X=3 is four times as likely as X=1 ( p(3) = 4* p(1) ) The outcome X=2 is six times as likely as X=1 ( p(2) = 6* p(1) )
Contingency Table
A contingency table can be defined as the visual representation of the relationship between two or more categorical variables that can be evaluated and registered. It is a categorical version of the scatterplot, which is used to investigate the linear relationship between two variables. A contingency table is indeed a type of frequency distribution table that displays two variables at the same time.
Binomial Distribution
Binomial is an algebraic expression of the sum or the difference of two terms. Before knowing about binomial distribution, we must know about the binomial theorem.
Random variable
Consider the random variable X with
| X= x | -1 | 1 | 2 | 3 | 5 | 6 |
| P(X = x) | 0.2 | p(1) | p(2) | p(3) | 0.2 | p(6) |
Find the values for the missing probabilities for the outcomes X = 1, 2, 3, and 6
You are given the following relations between the unknown probabilities.
The two least likely outcomes are X=1 and X=6, and these have the same probability.
( p(1) = p(6) )
The outcome X=3 is four times as likely as X=1
( p(3) = 4* p(1) )
The outcome X=2 is six times as likely as X=1
( p(2) = 6* p(1) )
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