2. • Probability
Probability in Statistics refers to the chances of
occurrence of an event among a large number of
possibilities. (a number between 0 and 1 inclusive)
Definitions of Terms:
3. • Random Experiment
It is an action or process that leads to one
of several possible outcomes.
Examples:
Random Experiments
a. Tossing a coin
b. Rolling a dice
c. Drawing a card
from a standard
deck of cards
Possible Outcomes
a. 𝑯𝒆𝒂𝒅, 𝑻𝒂𝒊𝒍
b. 𝟏, 𝟐, 𝟑, 𝟒, 𝟓, 𝟔
c.
𝟏𝟑 𝒄𝒍𝒖𝒃𝒔, 𝟏𝟑 𝒔𝒑𝒂𝒅𝒆𝒔,
𝟏𝟑 𝒉𝒆𝒂𝒓𝒕𝒔,
𝟏𝟑 𝒅𝒊𝒂𝒎𝒐𝒏𝒅𝒔
4. • Sample Space (S)
The list of all possible outcomes of the random
experiment.
Example: S = 𝑎, 𝑏, 𝑐, 𝑑, 𝑒
• Sample Point
each possible outcome in the sample space
(the elements of the sample space)
5. • Cardinality n(S)
It is the total number (k) of sample points of the
sample space.
Example: n(S) = 5
• Event (E)
any subset of the sample space consisting
one or more sample points to which a probability is
assigned
Example: E = 𝑎, 𝑐, 𝑑
6. • Mutually Exclusive Events
Events are said to be mutually exclusive if there
is no opportunity for them to occur simultaneously or if
they have no common sample point. In other words, tw
o events A and B cannot occur simultaneously.
Example: Event A – drawing a King
Event B – drawing an Ace
(from a standard deck of cards)
7. • Complementary Events
Let E denote occurrence of event. The
complement of E denotes the non-occurrence of
event E. It is denoted by E`.
• Independent Events
Two or more events are said to be
independent, in a series of trials if the outcome of
one event does not affect the outcome of the other
event or vice versa. Otherwise, they are dependent
events. Example: tossing a die and tossing a coin (indep.)
parking your vehicle illegally and getting a parking ticket (dep.)
