Silabus Mathematical Statistics Jurusan Matematika Semester 5 / V

Faculty                        : Mathematics and Natural Sciences

Study Program           : Mathematics Education

Course & Code           : Mathematical Statistics, SMA 328

Credit Hours               : Theory 2 credit, Practice 1 credit

Semester                     : V

Prerequisites & Code : Probability Theory, MAA 318

Lecturer                      : Rosita Kusumawati, M.Sc.

I.    COURSE DESCRIPTION

The course is more focused on probability concepts than statistical mathematics. The materials of  probability  theory  are  combinatorial  methods,  probability,  random  variables  and  their distributions,  joint  distributions,  properties  of  random  variables,  and  functions  of  random variables.

II.   BASED COMPETENCY

The students able to use probability and probability distribution for solving a real problem and mathematics problem which is need the calculation of probability, prove the theorems which related to probability, and find a relationship between distributions, and determine expected value of random variables.

III. ACTIVITIES PLAN

Meeting Based Competency Subject Matter Activities References 1-3 To understand CDF technique, Transformation methods and To gain the ability to compute the CDF of a new variable CDF technique, Transformation methods Discussion & Exercises A: 31-39 B: 1-16 C: 1-113 4-6 To understand sums of random variables, order Statistics Sums of random variables, Order Statistics Discussion & Exercises A: 1-30 B: 22-102 C: 1-113 7-10 To understand the concept of law large number, central limit theorem and its assumptions Sequences of random variables, The central limit theorem, Approximations for the binomial distribution Discussion & Exercises A: 53-83 B: 117-134 11-15 To recognize and learn properties of stochastic convergence Asymptotic normal distributions, Properties of stochastic convergence Discussion & Exercises A: 91-124 B: 134-224 16 Mid Test

17-21	To solve sampling distributions	Sampling distributions, Large- sample properties,	Discussion & Exercises	A: 137-160 B: 232-286
22-26	To explain methods of estimation	Methods of estimation, Criteria for evaluating estimators	Discussion & Exercises	A: 171-188 B: 297-373
27-32	To gain the ability to use to Bayes and minimax estimation methods	Bayes and minimax estimators	Discussion & Exercises	A: 193-214

IV. REFERENCES Compulsory textbooks  :

A.  Bain, Lee J. & Engelhardt, Max. 1992.  Introduction to Probability and Mathematical

Statistics. Belmont: Duxbury Press.

B.  Ross, Sheldon M. 2010. A First Course in Probability. New Jersey: Prentice-Hall.

Suggested reference books         :

C.  Rice, John A., 1995. Mathematical Statistics and Data Analysis. Belmont: Duxbury Press.

V.   EVALUATION

No.	Components	Weight (%)
1.	Participations	5
2.	Assigment	10
3.	Quiz	15
4.	Mid Test	30
6.	Final Test	40
Total		100

Yogyakarta, September 2012

Verified by                                                                                         Lecturer

Head of Department

Dr. Hartono                                                                                         Rosita Kusumawati, M.Sc. 

NIP. 19620329 198702 1 002                                                             NIP. 19800707 200501 2 001