A Level Maths Notes: S2 – The Cumulative Distribution Function
A probability distribution is usually defined in terms of it's probability distribution function (if continuous), the probability that it takes a value in a certain range, or probability mass function (if discrete), the probability that it takes a certain value Sometimes it is more convenient to define it in terms of it cumulative distribution function.
If the probability density function for
where
may
be finite or
and
may
be finite or
is
given by
then
the cumulative distribution function, cdf, such that
is given by
if
is
continuous
if
X is discrete.
Example: The continuous quantity
is
uniformly distributed over the interval
The
probability distribution is
The
cumulative distribution function is
Example: The probability distribution of a random variable
is
given in the following table. Construct the cumulative distribution
function.
|
|
0 |
1 |
2 |
3 |
4 |
5 |
|
|
0.10 |
0.05 |
0.00 |
0.25 |
0.15 |
0.45 |
To find the cumulative distribution function, add up the entries
in the
row
as you go along, to give
|
|
0 |
1 |
2 |
3 |
4 |
5 |
|
|
0.10 |
0.15 |
0.15 |
0.40 |
0.55 |
1.00 |
Conversely given a cumulative
distribution function we can find the probability distribution
function by differentiation, or by subtraction each
from
the previous one to give
in
the case of a discrete distribution.
Example: If
then![]()
Example:
is
given in the following table.
|
|
0 |
1 |
2 |
3 |
4 |
5 |
|
|
0.20 |
0.25 |
0.35 |
0.40 |
0.75 |
1.00 |
is
given in the table below.
|
|
0 |
1 |
2 |
3 |
4 |
5 |
|
|
0.20 |
0.25-0.20=0.05 |
0.35-0.25=0.10 |
0.40-0.35=0.05 |
0.75-0.40=0.35 |
1.00-0.75=0.25 |