Probability distributions are tables that give the probabilities for things like rolling a die, or tossing a coin. One can construct one using the tree diagram for tossing the coin previously shown.
Say we want to construct a probability distribution for a variable H representing the number of heads that occur in three tosses.
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H = number of heads that occur in three tosses
We can make a table as follows:
H |
Probability of this occurring |
0 |
1/8 |
1 |
3/8 |
2 |
3/8 |
3 |
1/8 |
Note how the probability column adds up to 1. Probability distributions should add up to 1. Sometimes this information is shown in a graph instead of a table.
Binomial distributions
Binomial distributions come about from situations where there are only two possible outcomes – such as tossing a coin, when you can only get heads or tails.
So far we can do questions like:
If I toss a coin three times, what is the probability of getting 2 heads then a tail?
To answer this question, we could just look at our tree diagram and see that it is 1/8.
What about:
If I toss a coin three times, what is the probability of getting exactly 2 heads?
This is more complicated, because we could get the following combinations which would all be counted as two heads and a tail:
HTH
HHT
THH
The overall probability of this occurring would be .
Another way of doing this is to use a general expression for binomial probability (‘bi’ meaning ‘two’):
Probability of x desired successes in n trials
= number of possible ways this can occur .
‘s’ is the probability of a (s)uccess happening in any one trial
‘f’ is the probability of a success not happening in any one trial, it is the probability of (f)ailure in any one trial.
To illustrate this, let’s use a coin example again.
What is the probability of two heads exactly occurring in three tosses? |
Solution |
A success is a head occurring. The desired outcome is two successes exactly. So: x = 2 The number of trials is 3. Number of possible ways this can occur is 3 (HTH, THH, HHT).
This confirms our previous answer. |