Module designation | Mathematical Statistics (MAS316) | ||||||||||||||
Semester(s) in which the module is taught | 5th | ||||||||||||||
Person responsible for the module | Dr. Miswanto, M.Si. | ||||||||||||||
Language | Indonesian | ||||||||||||||
Relation to curriculum | Compulsory / elective / specialisation | ||||||||||||||
Teaching methods | Lectures, Discussions and Assignments | ||||||||||||||
Workload (incl. contact hours, self-study hours) | 4×170 minutes (4×50 minutes lecture and lesson, 4×60 minutes structural activities, 4×60 minutes self-study) per week for 16 weeks | ||||||||||||||
Credit points | 4 CP (6,4 ECTS) | ||||||||||||||
Required and recommended prerequisites for joining the module | Multivariable Calculus (MAA203) | ||||||||||||||
Module objectives/intended learning outcomes | General Competence (Knowledge) Being able to determine the distribution of the specified random variable. Specific Competence : students are able to 1. calculate the probability 2. determine pdf for a random variable 3. determine the special distribution 4. determine the distribution of two random variables 5. determine CDF and MGF of the distribution of random variable 6. determine the distribution of random variable transformation 7. determine the distribution of order statistics 8. determine the estimation of the distribution parameters of the random variable | ||||||||||||||
Content | Introduction to permutation and Combination theory, Introduction to Probability Theory, Conditional probability, Bayes’ Rule, Random variables, Expectation and Variance Properties, MGF, Characteristic function, Probability Distribution, Special distribution, Joint distribution, Function of random variables, CDF method, Transformation method, MGF method, sequence statistics, sampling distribution, and parameter estimation theory. | ||||||||||||||
Examination forms | Essay | ||||||||||||||
Study and examination requirements | Students are considered to pass if they at least have got a final score 40 (D). Final score is calculated as follow: 10% softskill + 20% assignment + 35% midterm + 35% final exam. Final index is defined as follow:
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Reading list | 1. Bain J,B & Engelhardt,M.,1992,Introduction to Probability & Mathematical Statistics, California. 2. Sahoo, Prasanna, Probability and Mathematical Statistics, Department of Mathematics University of Louisville, Louisville, ky 40292 USA. |
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