1. 1 Pertemuan 07 Hitung Peluang Matakuliah: I0134 – Metoda Statistika Tahun: 2005 Versi: Revisi

2. 2 Learning Outcomes Pada akhir pertemuan ini, diharapkan mahasiswa akan mampu : Mahasiswa dapat menghitung dan menyusun sebaran peluang kejadian.

3. 3 Outline Materi Ruang contoh dan Peluang kejadian Kejadian gabungan dan irisan Kejadian komplementasi Kaidah Penghitungan

4. 4 Probability is: l A measure of uncertainty l A measure of the strength of belief in the occurrence of an uncertain event l A measure of the degree of chance or likelihood of occurrence of an uncertain event l Measured by a number between 0 and 1 (or between 0% and 100%)

5. 5 Types of Probability l Objective or Classical Probability –based on equally-likely events –based on long-run relative frequency of events –not based on personal beliefs – is the same for all observers (objective) –examples: toss a coins, throw a die, pick a card

6. 6 Types of Probability (2) l Subjective Probability –based on personal beliefs, experiences, prejudices, intuition - personal judgment –different for all observers (subjective) –examples: Super Bowl, elections, new product introduction, snowfall

7. 7 Basic Definitions l Set - a collection of elements or objects of interest –Empty set (denoted by  ) l a set containing no elements –Universal set (denoted by S) l a set containing all possible elements –Complement (Not). The complement of A is –a set containing all elements of S not in A

8. 8 –Intersection (And) – a set containing all elements in both A and B –Union (Or) – a set containing all elements in A or B or both Basic Definitions

9. 9 Mutually exclusive or disjoint sets – sets having no elements in common, having no intersection, whose intersection is the empty set Partition – a collection of mutually exclusive sets which together include all possible elements, whose union is the universal set Basic Definitions

10. 10 Partition AB B A A Sets: Diagrams

11. 11 Process that leads to one of several possible outcomes *, e.g.: –Coin toss Heads,Tails –Throw die 1, 2, 3, 4, 5, 6 –Pick a card AH, KH, QH,... – Introduce a new product Each trial of an experiment has a single observed outcome. The precise outcome of a random experiment is unknown before a trial. * Also called a basic outcome, elementary event, or simple event Experiment

12. 12 l Sample Space or Event Set –Set of all possible outcomes (universal set) for a given experiment l E.g.: Throw die –S = (1,2,3,4,5,6) l Event –Collection of outcomes having a common characteristic l E.g.: Even number –A = (2,4,6) –Event A occurs if an outcome in the set A occurs l Probability of an event –Sum of the probabilities of the outcomes of which it consists l P(A) = P(2) + P(4) + P(6) Events : Definition

13. 13 For example: –Throw a die Six possible outcomes (1,2,3,4,5,6) If each is equally-likely, the probability of each is 1/6 =.1667 = 16.67% Probability of each equally-likely outcome is 1 over the number of possible outcomes –Event A (even number) P(A) = P(2) + P(4) + P(6) = 1/6 + 1/6 + 1/6 = 1/2 for e in A Equally-likely Probabilities (Hypothetical or Ideal Experiments)

14. 14 l Range of Values l Complements - Probability of not A l Intersection - Probability of both A and B –Mutually exclusive events (A and C) : l Range of Values l Complements - Probability of not A l Intersection - Probability of both A and B –Mutually exclusive events (A and C) : Basic Rules for Probability

15. 15 Selamat Belajar Semoga Sukses.