Discrete probability
Discrete random variables and probability distrib
A discrete random variable is a variable that can only take on
values. For example, if you flip a coin twice, you can only get
times, one time, or two times. You can’t get heads 1.5 times, o
The number of heads you can get takes on a discrete set of v
and 2. A continuous random variable, on the other hand, can
value in a certain interval.
In probability distributions for all random variables, the proba
each of the possibilities has to sum to 1, or 100 % .
For example, if I flip a coin twice, I can get any of the followin
HH
HT
TH
TT
There are four possible outcomes, and one of them where I g
so the probability of getting 0 heads is 1/4. In HT and TH I get
the probability of getting 1 heads is 2/4. In HH I get 2 heads, s
probability of getting 2 heads is 1/4.
, 1 2 1
+ + = 1 = 100 %
4 4 4
The fact that a valid probability distribution always sums to 1
to find missing values in our data. For example, if instead we’
that the table below tells us the probability of getting a certa
heads when we flip a coin twice,
Heads Probability
0 0.25
1 0.50
2
we could calculate the missing value by subtracting the know
probabilities from 1.00. So we could say that the probability o
exactly 2 heads is
P(2 heads) = 1.00 − 0.25 − 0.50 = 0.25
And then we could complete the table:
Heads Probability
0 0.25
1 0.50
2 0.25
Discrete random variables and probability distrib
A discrete random variable is a variable that can only take on
values. For example, if you flip a coin twice, you can only get
times, one time, or two times. You can’t get heads 1.5 times, o
The number of heads you can get takes on a discrete set of v
and 2. A continuous random variable, on the other hand, can
value in a certain interval.
In probability distributions for all random variables, the proba
each of the possibilities has to sum to 1, or 100 % .
For example, if I flip a coin twice, I can get any of the followin
HH
HT
TH
TT
There are four possible outcomes, and one of them where I g
so the probability of getting 0 heads is 1/4. In HT and TH I get
the probability of getting 1 heads is 2/4. In HH I get 2 heads, s
probability of getting 2 heads is 1/4.
, 1 2 1
+ + = 1 = 100 %
4 4 4
The fact that a valid probability distribution always sums to 1
to find missing values in our data. For example, if instead we’
that the table below tells us the probability of getting a certa
heads when we flip a coin twice,
Heads Probability
0 0.25
1 0.50
2
we could calculate the missing value by subtracting the know
probabilities from 1.00. So we could say that the probability o
exactly 2 heads is
P(2 heads) = 1.00 − 0.25 − 0.50 = 0.25
And then we could complete the table:
Heads Probability
0 0.25
1 0.50
2 0.25
