This document defines key probability concepts and formulas: 1. It defines sample space, trials, and events for a probability problem. A sample space is all possible outcomes, a trial is a single outcome, and an event is a subset of outcomes. 2. It gives the formula for probability of an event as the number of outcomes in the event divided by the total number of outcomes. Expected frequency is the probability of an event times the number of trials. 3. It discusses the probability of complementary events, mutually exclusive events, mutually independent events, and conditional events along with the corresponding formulas.

1. Kelompok 2 :
1. Ahmad Tuflikhun N. (03)
2. Herdianto Mandiri P. (16)
3. Rachmanta Isa A. (22)
4. Wahyu Dwi P. (26)

2. B. 1. Definition of Trial, Sample Space, and Event
- Sample Space: A set of all the possible result
from a trial.
- Trial: A member of the sample space.
- Event: Part of the sample space.

3. B. 2. Probability of an Event
B. 2. a. Definition of Probability
If E is an event with , then probability of event
E which notated by is defined as:
note:
n(E) = number of elements in an event E
n(S) = number of sample points in the sample space of S
or number of member of S
SE 
 EP
   
 Sn
En
EP 

4. B. 2. b. Expectation of an Event’s Frequency
An expected frequency of an events is a result of
the multiplication between number of trials and
the probability of the possible event will be
happened in a trial.
Mathematically:
   EnxPEfh 

5. C. 1. Probability of The Complementary of an Event
In the following figure, an event of E is defined in a
sample space of S, so that the event outside E is called
COMPLEMENT of an event E and notated by P.
E
S
SPE 
     SnPnEn 
    1 PPEP
   EPPP 1

6. C. 2. Probability of Mutually Events
If A and B are mutually exclusive,
If A and B are not mutually exclusive,
AA BB
Two events are mutually
exclusive
Two events are not mutually
exclusive
     BPAPBAP 
       BAPBPAPBAP 

7. C. 3. Probability of Mutually Independent Events
The first event does not affect to the probability
of the second one.
Example :
-Probability in drawing a dice
-Probability in drawing coin
The probability of the event A and B that written
as for A and B mutually independent
is formulated by:
 BAP 
     BxPAPBAP 

8. C. 4. Probability of the Conditional Event
The first event will affect the probability of
the second event.
Example :
-Probability in drawing a red ball from the bag
which contain 5 yellow baall & 5 red ball.
The probability of the event that A and B
happened, which written as , in the
case that A and B are two conditional evenrs, is
formulated as:
     ABxPAPBAP 
 BAP 