1.
A Bernoulli distribution is a discrete probability distribution which takes value 1 with success probability p and value 0 with failure probability q = 1 - p.
It is the probability of the observed value.
No. Probability must be between 0 and 1.
A probability must needs be a number between 0 and 1 (often expressed as 0% and 100%), inclusive.
1.
A Bernoulli distribution is a discrete probability distribution which takes value 1 with success probability p and value 0 with failure probability q = 1 - p.
It is the probability of the observed value.
No. Probability must be between 0 and 1.
A joint probability can have a value greater than one. It can only have a value larger than 1 over a region that measures less than 1.
A probability must needs be a number between 0 and 1 (often expressed as 0% and 100%), inclusive.
No, we can't expression any negative value as a probability. A probability ranges from 0 to 1 - 0 being the lowest and 1 being the highest.
A value that is between 0 and 1.
If the probability of an event occurring is p, then 1-p represents the probability of the same event not occurring. The value of p must lie between 0 and 1.
A discrete probability distribution is defined over a set value (such as a value of 1 or 2 or 3, etc). A continuous probability distribution is defined over an infinite number of points (such as all values between 1 and 3, inclusive).
It is usually any value between 0.5 and 1.
You should be given p(x) values such as 0.09 0.19 0.14 0.29 you just add these values to get 0.71 subtract 0.71 from 1 to get 0.29 is the answer