TI2102


TI2102 PROBABILISTIC THEORY
Credits: 2 Course Coordinator:
Contact hours:

 

Twohour class session each week Instructor(s): DI, MAK
Textbook(s) and other supplemental materials
  1. Walpole, R.E., R.H. Myers, S.L. Myers, & K. Ye, 2002, Probability and Statistics for Engineers & Scientists, Prentice-Hall
  2. Evan, D.H, 1992, Probability and Its Applications for Engineers, ASQC Press & Marcel Dekker Inc
  3. Feller, W, 1968, An Introduction to Probability Theory and Its Appplications, John Wiley & Sons
  4. Ross, S.M, 1998, A First Course in Probability, Prentice-Hall International
Course information Pengantar statistika dan teori probabilitas; pengertian ruang sampel dan kejadian; probabilitas obyektif, empiris, dan subyektif; variabel random; fungsi padat/massa peluang dan distribusi probabilitas gabungan untuk variabel random majemuk; probabilitas marginal; probabilitas bersyarat; teorema Bayes dan teorema Chebysev; ekspektasi dan variansi; distribusi probabilitas variabel tunggal diskrit teoritis; distribusi probabilitas variabel tunggal kontinu teoritis; transformasi fungsi variabel random dan fungsi pembangkit momen; distribusi sampling; distribusi t; distribusi chi-square; dan distribusi F sebagai pengantar menuju statistika inferensi.
Introduction to statistics and probability theory, definition of events and sample space, objective, empirical and subjective probability, random variable, probability density and mass function, joint probabilistic distribution for multiple random variable, marginal probability, conditional probability, Bayes and Chebysev Theorem, expectation and variance, theoretical discrete single variable probability distribution; theoretical continue single variable probability distribution; moment generating function and random variable function transformation, sampling distribution, t distribution, chi-square distribution and F distribution as an introduction to inference statistics.
Pre-requisite

  • MA1101 Mathematics 1A
  • MA1201 Mathematics 2A
Co-requisite
Required Course
Learning outcomes Mahasiswa memahami dan mampu menerapkan konsep-konsep dalam teori probabilitas dalam membantu memecahkan permasalahan-permasalahan yang berhubungan dengan disiplin teknik industri
To develop an understanding of and apply probability concepts in order to be able to solve industrial engineering problems.
Student Outcomes

a

b c d e f g h i j k
R R              

 

 

Lecture/Lab Topics Covered

Week Topics
1 Introduction
2 Sample Space and Events
3-4 Basic Concept of Probability
5 PDF and CDF
6 Marginal and Conditional Distribution
7 Expectancy and Variance
8 Midterm Test
9-10 Discrete Distribution
11-12 Continuous Distribution
13 Random Variable Function
14-15 Continuous Probability Distribution
16 Final Test