# Probability and Statistics

Save this PDF as:

Size: px
Start display at page:

## Transcription

1 Probability and Statistics Syllabus for the TEMPUS SEE PhD Course (Podgorica, April 4 29, 2011) Franz Kappel 1 Institute for Mathematics and Scientific Computing University of Graz Žaneta Popeska 2 Faculty of natural sciences and mathematics Ss. Cyril and Methodius University, Macedonia Wilhelm Schappacher 3 Institute for Mathematics and Scientific Computing University of Graz

2 1 1 General goals of the course The course should provide a high level overview on a wide range of statistical methods, data analysis, parameter estimation, test theory and on stochastic processes. It is recommended that the course will be modified in the future in order to focus more on topics which are represented as research topics at the partner universities. 2 Prerequisites on the students side Participating students should be familiar with basic notions of probability theory including measure theory and integration as well as basic statistics. Fundamentals of functional analysis are also required. Of course, English language proficiency is an absolute necessity. 3 Modules of the course PART I: Probability theory and statistics (20 units) Module No. of units Contents I: Review of basic notions in probability theory 7 Fundamentals Bayes theorem, sensitivity, specifity Borel-Cantelli theorem Random variables, distribution functions, density Examples (Bernoulli, binomial etc.) Multi-dimensional normal distributions Expectation, variance, independence, correlation Moment generating functions, characteristic functions Convergence of random variables (almost surely, in probability, in the p-th mean, in distribution) II: Laws of large numbers 4 Weak and strong law of large numbers Central limit theorem III: Data analysis 3 Empirical distribution Quantil plots Regressions IV: Hypothesis testing 6 Hypotheses Power of a test Maximum likelihood test t-test, F-test Parameter free tests continued on next page

3 2 continued from previous page PART II: Parameter estimation (20 units) V: Point estimation theory 3 Output models Assumptions on the measurement process Properties of estimators Fisher information Cramer-Rao theorem VI: Least squares estimators 3 Nonlinear least squares Nonlinear least squares Linear approximation Generalized least squares Numerical methods VII: Maximum likelihood estimation 3 Normal data non-normal data VIII: Bayesian estimation 3 Choice of prior distributions Posterior distributions Highest posterior density regions Normal approximation to posterior density IX: Assymptotic theory 4 Introduction Least squares estimation Maximum likelihood estimation X: Optimal experimental design 4 Introduction Generalized measurement procedures Probability measures on compact sets Optimal design criteria in terms of the Fisher information matrix PART III: Stochastic processes (20 units) XI: Markov chains 3 Construction and properties Examples Transience and recurrence Canonical decomposition Absorption probabilities Limit distributions XII: Renewal theory 4 Counting renewals Renewal reward processes The Renewal Equation The Poisson Process Discrete renewal theory Stationary renewal processes Improper renewal equations continued on next page

4 continued from previous page XIII: Point processes 3 The Poisson Process Transforming Poisson Processes Max-stable and stable random variables More transformation theory Marking and thinning Variants of the Poisson Process The linear birth process as a point process XIV: Continuous time Markov chains 2 Definitions and construction Stability and explosions The Markov property Stationary and limiting distributions Laplace transform methods XV: Brownian motion 3 Introduction and construction of Brownian motion Properties of the standard Brownian motion The reflection principle The distribution of the maximum Brownian motion with drift XVI: Martingales and semimartingales XVII: Stochastic differential equations Total no. of units: 60 3 Introduction Stability properties Examples Stochastic integrals The quadratic variation of a semimartingale Change of variables (Ito s formula) 2 Existence and uniqueness of solutions Stability of stochastic differential equations Stochastic exponentials and linear equations 3 4 Literature [1] Asmussen, S., and Glynn, P. W., Stochastic Simulation, Algorithms and Analysis, Stochastic Modelling and Applied Probability Vol. 57, Springer-Verlag, New York [2] Fedorov, V. V., Theory of Optimal Experiments, Academic Press, New York [3] Florens, J.-P., Marchart, M., and Rolin, J.-M., Elements of Bayesian Statistics, Marcel Dekker, New York [4] Goodwin, G. C., and Payne, R. L., Dynamic System Identification: Experiment Design and Data Analysis, Mathematics in Science and Engineering Vol. 136, Academic Press, New York [5] Lin kov, Y. N., Lectures in Mathematical Statistics, Parts 1 and 2, Translations of Mathematical Monographs Vol. 229, American Mathematical Society, Providence, R.I., [6] Loève, M., Probability Theory I and II, 4th edition, Graduate Texts in Mathematics Vol , Springer-Verlag, New York 1977, [7] Pázman, A., Foundations of Optimum Experimental Design, Mathematics and its Applications (East European Series), Reidel Publ. Comp., Dordrecht 1986.

5 4 [8] Protter, Ph. E., Stochastic Integration and Differential Equations, 2nd edition, Springer- Verlag, New York [9] Resnick, S. F., Adventures in Stochastic processes, Birkhäuser, Basel [10] Ross, S., Stochastic Processes, John Wiley, New York [11] Schuss, Z., Theory and Applications of Stochastic Processes, an Analytical Approach, Applied Mathematical Sciences Vol. 170, Springer-Verlag [12] Seber, G.A.F., and Wild, G. A., Nonlinear Regression, John Wiley & Sons, New York [13] Shiryaev, A. N., Probability, 2nd ed., Graduate TExts in Mathematics Vol. 95, Springer- Verlag, New York Teaching The course should be accompanied by homework exercises which should require at most 2 of the afternoon sessions as indicated below. The major part of the afternoon session should be spent by working independently in teams on little projects on practical or pseudo-practical problems. The results also should be presented in the afternoon sessions. During the afternoon session the teacher should be available for questions respectively be present in order to get an impression on performance of the students. Homework exercises and projects for teamwork should also involve programming of algorithms respectively use of available software. The course is planned for 4 weeks, each week from Monday till Friday. This implies that there will be 3 teaching units ( 45 minutes) per day. The following schedule is proposed for each day: 8:00 till 11:00: three units with breaks in between; 11:30 till 12:30: discussion with the teacher; 15:00 till 17:30: work on homework exercises, work in teams on problems posed by the lecturer, presentation of results, respectively Teachers for the course: 6 Grading Part I Part II Part III E. Pancheva F. Kappel W. Schappacher The basis for grading is provided by the performance of students in the following items: a) Exercises for homework involving also numerical computations will be regularly given in order to provide possibilities for a better understanding of the material presented in the course. b) Team projects and presentation of results. c) An oral examination concerning the course. The oral examination could consist of several parts taken at different times and should give the lecturer an impression on how well the student has understood the material of the course. In order to obtain the grade for the course the following weights will be used for the items a), b) and c) from above: Homework exercises 20% Team projects 50% Oral examination 30%

### Institute of Actuaries of India Subject CT3 Probability and Mathematical Statistics

Institute of Actuaries of India Subject CT3 Probability and Mathematical Statistics For 2015 Examinations Aim The aim of the Probability and Mathematical Statistics subject is to provide a grounding in

### Service courses for graduate students in degree programs other than the MS or PhD programs in Biostatistics.

Course Catalog In order to be assured that all prerequisites are met, students must acquire a permission number from the education coordinator prior to enrolling in any Biostatistics course. Courses are

### MATHEMATICAL METHODS OF STATISTICS

MATHEMATICAL METHODS OF STATISTICS By HARALD CRAMER TROFESSOK IN THE UNIVERSITY OF STOCKHOLM Princeton PRINCETON UNIVERSITY PRESS 1946 TABLE OF CONTENTS. First Part. MATHEMATICAL INTRODUCTION. CHAPTERS

### Program description for the Master s Degree Program in Mathematics and Finance

Program description for the Master s Degree Program in Mathematics and Finance : English: Master s Degree in Mathematics and Finance Norwegian, bokmål: Master i matematikk og finans Norwegian, nynorsk:

### Alessandro Birolini. ineerin. Theory and Practice. Fifth edition. With 140 Figures, 60 Tables, 120 Examples, and 50 Problems.

Alessandro Birolini Re ia i it En ineerin Theory and Practice Fifth edition With 140 Figures, 60 Tables, 120 Examples, and 50 Problems ~ Springer Contents 1 Basic Concepts, Quality and Reliability Assurance

### Stephane Crepey. Financial Modeling. A Backward Stochastic Differential Equations Perspective. 4y Springer

Stephane Crepey Financial Modeling A Backward Stochastic Differential Equations Perspective 4y Springer Part I An Introductory Course in Stochastic Processes 1 Some Classes of Discrete-Time Stochastic

### Alabama Department of Postsecondary Education

Date Adopted 1998 Dates reviewed 2007, 2011, 2013 Dates revised 2004, 2008, 2011, 2013, 2015 Alabama Department of Postsecondary Education Representing Alabama s Public Two-Year College System Jefferson

Statistics Graduate Courses STAT 7002--Topics in Statistics-Biological/Physical/Mathematics (cr.arr.).organized study of selected topics. Subjects and earnable credit may vary from semester to semester.

Graduate Programs in Statistics Course Titles STAT 100 CALCULUS AND MATR IX ALGEBRA FOR STATISTICS. Differential and integral calculus; infinite series; matrix algebra STAT 195 INTRODUCTION TO MATHEMATICAL

### ANGELO STATE UNIVERSITY/GLEN ROSE HIGH SCHOOL DUAL CREDIT ALGEBRA II AND COLLEGE ALGEBRA/MATH 1302 2015-2016

ANGELO STATE UNIVERSITY/GLEN ROSE HIGH SCHOOL DUAL CREDIT ALGEBRA II AND COLLEGE ALGEBRA/MATH 1302 2015-2016 I. INSTRUCTOR MRS. JAMI LOVELADY Office: 504 Tutorial Hours: Mornings Monday through Friday

### Non-Life Insurance Mathematics

Thomas Mikosch Non-Life Insurance Mathematics An Introduction with the Poisson Process Second Edition 4y Springer Contents Part I Collective Risk Models 1 The Basic Model 3 2 Models for the Claim Number

### INTRODUCTORY STATISTICS

INTRODUCTORY STATISTICS FIFTH EDITION Thomas H. Wonnacott University of Western Ontario Ronald J. Wonnacott University of Western Ontario WILEY JOHN WILEY & SONS New York Chichester Brisbane Toronto Singapore

### DATA ANALYTICS USING R

DATA ANALYTICS USING R Duration: 90 Hours Intended audience and scope: The course is targeted at fresh engineers, practicing engineers and scientists who are interested in learning and understanding data

### STA 4273H: Statistical Machine Learning

STA 4273H: Statistical Machine Learning Russ Salakhutdinov Department of Statistics! rsalakhu@utstat.toronto.edu! http://www.cs.toronto.edu/~rsalakhu/ Lecture 6 Three Approaches to Classification Construct

### Master of Mathematical Finance: Course Descriptions

Master of Mathematical Finance: Course Descriptions CS 522 Data Mining Computer Science This course provides continued exploration of data mining algorithms. More sophisticated algorithms such as support

### AN ACCESSIBLE TREATMENT OF MONTE CARLO METHODS, TECHNIQUES, AND APPLICATIONS IN THE FIELD OF FINANCE AND ECONOMICS

Brochure More information from http://www.researchandmarkets.com/reports/2638617/ Handbook in Monte Carlo Simulation. Applications in Financial Engineering, Risk Management, and Economics. Wiley Handbooks

### Tennessee Wesleyan College Math 131 C Syllabus Spring 2016

Tennessee Wesleyan College Math 131 C Syllabus Spring 2016 I. Course: College Algebra, M131 C Location: Durham 303 Days/Time: MWF 1100-1150 Credit hours: 3 II. III. IV. Instructor: Dr. David J. Ashe Office:

### Operations Research and Financial Engineering. Courses

Operations Research and Financial Engineering Courses ORF 504/FIN 504 Financial Econometrics Professor Jianqing Fan This course covers econometric and statistical methods as applied to finance. Topics

### QUALITY ENGINEERING PROGRAM

QUALITY ENGINEERING PROGRAM Production engineering deals with the practical engineering problems that occur in manufacturing planning, manufacturing processes and in the integration of the facilities and

### Analysis of Financial Time Series

Analysis of Financial Time Series Analysis of Financial Time Series Financial Econometrics RUEY S. TSAY University of Chicago A Wiley-Interscience Publication JOHN WILEY & SONS, INC. This book is printed

### STAT 360 Probability and Statistics. Fall 2012

STAT 360 Probability and Statistics Fall 2012 1) General information: Crosslisted course offered as STAT 360, MATH 360 Semester: Fall 2012, Aug 20--Dec 07 Course name: Probability and Statistics Number

### Applied mathematics and mathematical statistics

Applied mathematics and mathematical statistics The graduate school is organised within the Department of Mathematical Sciences.. Deputy head of department: Aila Särkkä Director of Graduate Studies: Marija

### Fundamentals of Actuarial Mathematics

Fundamentals of Actuarial Mathematics S. David Promislow York University, Toronto, Canada John Wiley & Sons, Ltd Contents Preface Notation index xiii xvii PARTI THE DETERMINISTIC MODEL 1 1 Introduction

### Curriculum Map Statistics and Probability Honors (348) Saugus High School Saugus Public Schools 2009-2010

Curriculum Map Statistics and Probability Honors (348) Saugus High School Saugus Public Schools 2009-2010 Week 1 Week 2 14.0 Students organize and describe distributions of data by using a number of different

### Statistical Modeling by Wavelets

Statistical Modeling by Wavelets BRANI VIDAKOVIC Duke University A Wiley-Interscience Publication JOHN WILEY & SONS, INC. New York / Chichester / Weinheim / Brisbane / Singapore / Toronto Contents Preface

### PROBABILITY AND STATISTICS. Ma 527. 1. To teach a knowledge of combinatorial reasoning.

PROBABILITY AND STATISTICS Ma 527 Course Description Prefaced by a study of the foundations of probability and statistics, this course is an extension of the elements of probability and statistics introduced

### Master of Arts in Mathematics

Master of Arts in Mathematics Administrative Unit The program is administered by the Office of Graduate Studies and Research through the Faculty of Mathematics and Mathematics Education, Department of

### Monte Carlo Methods and Models in Finance and Insurance

Chapman & Hall/CRC FINANCIAL MATHEMATICS SERIES Monte Carlo Methods and Models in Finance and Insurance Ralf Korn Elke Korn Gerald Kroisandt f r oc) CRC Press \ V^ J Taylor & Francis Croup ^^"^ Boca Raton

### STATISTICS COURSES UNDERGRADUATE CERTIFICATE FACULTY. Explanation of Course Numbers. Bachelor's program. Master's programs.

STATISTICS Statistics is one of the natural, mathematical, and biomedical sciences programs in the Columbian College of Arts and Sciences. The curriculum emphasizes the important role of statistics as

### Econometric Analysis of Cross Section and Panel Data Second Edition. Jeffrey M. Wooldridge. The MIT Press Cambridge, Massachusetts London, England

Econometric Analysis of Cross Section and Panel Data Second Edition Jeffrey M. Wooldridge The MIT Press Cambridge, Massachusetts London, England Preface Acknowledgments xxi xxix I INTRODUCTION AND BACKGROUND

### 2014-2015 The Master s Degree with Thesis Course Descriptions in Industrial Engineering

2014-2015 The Master s Degree with Thesis Course Descriptions in Industrial Engineering Compulsory Courses IENG540 Optimization Models and Algorithms In the course important deterministic optimization

### Business Statistics. Successful completion of Introductory and/or Intermediate Algebra courses is recommended before taking Business Statistics.

Business Course Text Bowerman, Bruce L., Richard T. O'Connell, J. B. Orris, and Dawn C. Porter. Essentials of Business, 2nd edition, McGraw-Hill/Irwin, 2008, ISBN: 978-0-07-331988-9. Required Computing

### PCHS ALGEBRA PLACEMENT TEST

MATHEMATICS Students must pass all math courses with a C or better to advance to the next math level. Only classes passed with a C or better will count towards meeting college entrance requirements. If

### Handbook in. Monte Carlo Simulation. Applications in Financial Engineering, Risk Management, and Economics

Handbook in Monte Carlo Simulation Applications in Financial Engineering, Risk Management, and Economics PAOLO BRANDIMARTE Department of Mathematical Sciences Politecnico di Torino Torino, Italy WlLEY

### MATH. ALGEBRA I HONORS 9 th Grade 12003200 ALGEBRA I HONORS

* Students who scored a Level 3 or above on the Florida Assessment Test Math Florida Standards (FSA-MAFS) are strongly encouraged to make Advanced Placement and/or dual enrollment courses their first choices

EC151.02 Statistics for Business and Economics (MWF 8:00-8:50) Instructor: Chiu Yu Ko Office: 462D, 21 Campenalla Way Phone: 2-6093 Email: kocb@bc.edu Office Hours: by appointment Description This course

### Universitatea de Medicină şi Farmacie Grigore T. Popa Iaşi Comisia pentru asigurarea calităţii DISCIPLINE RECORD/ COURSE / SEMINAR DESCRIPTION

Universitatea de Medicină şi Farmacie Grigore T. Popa Iaşi Comisia pentru asigurarea calităţii DISCIPLINE RECORD/ COURSE / SEMINAR DESCRIPTION 1. Information about the program 1.1. UNIVERSITY: GRIGORE

### Summary of Probability

Summary of Probability Mathematical Physics I Rules of Probability The probability of an event is called P(A), which is a positive number less than or equal to 1. The total probability for all possible

### ACTL5101 Probability and Statistics for Actuaries

Australian School of Business School of Risk and Actuarial Studies ACTL5101 Probability and Statistics for Actuaries Course Outline Semester 1, 2014 Part A: Course-Specific Information Please consult Part

### Multivariate Statistical Inference and Applications

Multivariate Statistical Inference and Applications ALVIN C. RENCHER Department of Statistics Brigham Young University A Wiley-Interscience Publication JOHN WILEY & SONS, INC. New York Chichester Weinheim

### Course Text. Required Computing Software. Course Description. Course Objectives. StraighterLine. Business Statistics

Course Text Business Statistics Lind, Douglas A., Marchal, William A. and Samuel A. Wathen. Basic Statistics for Business and Economics, 7th edition, McGraw-Hill/Irwin, 2010, ISBN: 9780077384470 [This

### Applied Multivariate Analysis

Neil H. Timm Applied Multivariate Analysis With 42 Figures Springer Contents Preface Acknowledgments List of Tables List of Figures vii ix xix xxiii 1 Introduction 1 1.1 Overview 1 1.2 Multivariate Models

### Fairfield Public Schools

Mathematics Fairfield Public Schools AP Statistics AP Statistics BOE Approved 04/08/2014 1 AP STATISTICS Critical Areas of Focus AP Statistics is a rigorous course that offers advanced students an opportunity

### Diablo Valley College Catalog 2014-2015

Mathematics MATH Michael Norris, Interim Dean Math and Computer Science Division Math Building, Room 267 Possible career opportunities Mathematicians work in a variety of fields, among them statistics,

### Least Squares Estimation

Least Squares Estimation SARA A VAN DE GEER Volume 2, pp 1041 1045 in Encyclopedia of Statistics in Behavioral Science ISBN-13: 978-0-470-86080-9 ISBN-10: 0-470-86080-4 Editors Brian S Everitt & David

### 3818 - Introduction to Statistics (Online) Syllabus/Course Information

3818 - Introduction to Statistics (Online) Syllabus/Course Information Course Description Econ 3818 is a first course in probability and statistical methods, with an introduction to econometrics. This

### Algebra I Credit Recovery

Algebra I Credit Recovery COURSE DESCRIPTION: The purpose of this course is to allow the student to gain mastery in working with and evaluating mathematical expressions, equations, graphs, and other topics,

### Dirichlet forms methods for error calculus and sensitivity analysis

Dirichlet forms methods for error calculus and sensitivity analysis Nicolas BOULEAU, Osaka university, november 2004 These lectures propose tools for studying sensitivity of models to scalar or functional

### Optimal proportional reinsurance and dividend pay-out for insurance companies with switching reserves

Optimal proportional reinsurance and dividend pay-out for insurance companies with switching reserves Abstract: This paper presents a model for an insurance company that controls its risk and dividend

### THE MULTIVARIATE ANALYSIS RESEARCH GROUP. Carles M Cuadras Departament d Estadística Facultat de Biologia Universitat de Barcelona

THE MULTIVARIATE ANALYSIS RESEARCH GROUP Carles M Cuadras Departament d Estadística Facultat de Biologia Universitat de Barcelona The set of statistical methods known as Multivariate Analysis covers a

### ANGELO STATE UNIVERSITY/GLEN ROSE HIGH SCHOOL TRIGONOMETRY WITH ANALYTIC GEOMETRY MATH 1353 SPRING OF 2016

ANGELO STATE UNIVERSITY/GLEN ROSE HIGH SCHOOL TRIGONOMETRY WITH ANALYTIC GEOMETRY MATH 1353 SPRING OF 2016 I. INSTRUCTOR MRS. JAMI LOVELADY Office: 504 Phone: 254-898-3824 Conference/Planning Period -

### Mathematical Modeling and Methods of Option Pricing

Mathematical Modeling and Methods of Option Pricing This page is intentionally left blank Mathematical Modeling and Methods of Option Pricing Lishang Jiang Tongji University, China Translated by Canguo

### International College of Economics and Finance Syllabus Probability Theory and Introductory Statistics

International College of Economics and Finance Syllabus Probability Theory and Introductory Statistics Lecturer: Mikhail Zhitlukhin. 1. Course description Probability Theory and Introductory Statistics

### Econometrics and Data Analysis I

Econometrics and Data Analysis I Yale University ECON S131 (ONLINE) Summer Session A, 2014 June 2 July 4 Instructor: Doug McKee (douglas.mckee@yale.edu) Teaching Fellow: Yu Liu (dav.yu.liu@yale.edu) Classroom:

### A Simulation-Based lntroduction Using Excel

Quantitative Finance A Simulation-Based lntroduction Using Excel Matt Davison University of Western Ontario London, Canada CRC Press Taylor & Francis Croup Boca Raton London New York CRC Press is an imprint

### Requisite Approval must be attached

Requisite Approval must be attached CITRUS COMMUNITY COLLEGE DISTRICT DEPARTMENT Mathematics COURSE NUMBER MATH 148 TITLE Intermediate Algebra I THIS COURSE IS CLASSIFIED AS: DEGREE APPLICABLE UNIT VALUE

### Advances in Stochastic Models for Reliability, Quality and Safety

Advances in Stochastic Models for Reliability, Quality and Safety Waltraud Kahle Elart von Collani Jürgen Franz Uwe Jensen Editors Birkhäuser Boston Basel Berlin Preface List of Contributors List of Tables

### Contents. List of Figures. List of Tables. List of Examples. Preface to Volume IV

Contents List of Figures List of Tables List of Examples Foreword Preface to Volume IV xiii xvi xxi xxv xxix IV.1 Value at Risk and Other Risk Metrics 1 IV.1.1 Introduction 1 IV.1.2 An Overview of Market

### COURSE SYLLABUS. Intermediate Algebra DMTH 0200. 2-2 - 3 Lecture - Lab - Credit. Prerequisite

COURSE SYLLABUS Intermediate Algebra 2-2 - 3 Lecture - Lab - Credit Prerequisite Beginning Algebra or a MATH THEA/ACCUPLACER score at the Remediation Standard This syllabus has been reviewed and is current

### Business Analytics. Methods, Models, and Decisions. James R. Evans : University of Cincinnati PEARSON

Business Analytics Methods, Models, and Decisions James R. Evans : University of Cincinnati PEARSON Boston Columbus Indianapolis New York San Francisco Upper Saddle River Amsterdam Cape Town Dubai London

### ESTDESC - Descriptive Statistics

Coordinating unit: Teaching unit: Academic year: Degree: ECTS credits: 2015 250 - ETSECCPB - Barcelona School of Civil Engineering 751 - ECA - Department of Civil and Environmental Engineering BACHELOR'S

HAROLD CAMPING i ii iii iv v vi vii viii ix x xi xii 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52

### 67 204 Mathematics for Business Analysis I Fall 2007

67 204 Mathematics for Business Analysis I Fall 2007 Instructor Asõkā Rāmanāyake Office: Swart 223 Office Hours: Monday 12:40 1:40 Wednesday 8:00 9:00 Thursday 9:10 11:20 If you cannot make my office hours,

### Statistical Rules of Thumb

Statistical Rules of Thumb Second Edition Gerald van Belle University of Washington Department of Biostatistics and Department of Environmental and Occupational Health Sciences Seattle, WA WILEY AJOHN

### TABLE OF CONTENTS CHAPTER NO. TITLE PAGE NO. ABSTRACT iii LIST OF TABLES LIST OF FIGURES LIST OF ABBREVIATIONS

ix TABLE OF CONTENTS CHAPTER NO. TITLE PAGE NO. ABSTRACT iii LIST OF TABLES x LIST OF FIGURES xii LIST OF ABBREVIATIONS xiv 1 INTRODUCTION 1 1.1 ENTERPRISE RESOURCE PLANNING (ERP) AN OVERVIEW 1 1.2 AIM

### Masters of Engineering in MIE Certificate Program in Financial Engineering

Masters of Engineering in MIE Certificate Program in Financial Engineering March 2, QFRM 2012 Roy H. Kwon University of Toronto Masters of Engineering at MIE The Master of Engineering program prepares

### SAS Certificate Applied Statistics and SAS Programming

SAS Certificate Applied Statistics and SAS Programming SAS Certificate Applied Statistics and Advanced SAS Programming Brigham Young University Department of Statistics offers an Applied Statistics and

### AN INTRODUCTION TO NUMERICAL METHODS AND ANALYSIS

AN INTRODUCTION TO NUMERICAL METHODS AND ANALYSIS Revised Edition James Epperson Mathematical Reviews BICENTENNIAL 0, 1 8 0 7 z ewiley wu 2007 r71 BICENTENNIAL WILEY-INTERSCIENCE A John Wiley & Sons, Inc.,

### UNDERGRADUATE DEGREE DETAILS : BACHELOR OF SCIENCE WITH

QATAR UNIVERSITY COLLEGE OF ARTS & SCIENCES Department of Mathematics, Statistics, & Physics UNDERGRADUATE DEGREE DETAILS : Program Requirements and Descriptions BACHELOR OF SCIENCE WITH A MAJOR IN STATISTICS

### Introduction to Financial Models for Management and Planning

CHAPMAN &HALL/CRC FINANCE SERIES Introduction to Financial Models for Management and Planning James R. Morris University of Colorado, Denver U. S. A. John P. Daley University of Colorado, Denver U. S.

### Government of Russian Federation. Faculty of Computer Science School of Data Analysis and Artificial Intelligence

Government of Russian Federation Federal State Autonomous Educational Institution of High Professional Education National Research University «Higher School of Economics» Faculty of Computer Science School

### Total Credits: 30 credits are required for master s program graduates and 51 credits for undergraduate program.

Middle East Technical University Graduate School of Social Sciences Doctor of Philosophy in Business Administration In the Field of Accounting-Finance Aims: The aim of Doctor of Philosphy in Business Administration

### Nonparametric adaptive age replacement with a one-cycle criterion

Nonparametric adaptive age replacement with a one-cycle criterion P. Coolen-Schrijner, F.P.A. Coolen Department of Mathematical Sciences University of Durham, Durham, DH1 3LE, UK e-mail: Pauline.Schrijner@durham.ac.uk

### APPLIED MISSING DATA ANALYSIS

APPLIED MISSING DATA ANALYSIS Craig K. Enders Series Editor's Note by Todd D. little THE GUILFORD PRESS New York London Contents 1 An Introduction to Missing Data 1 1.1 Introduction 1 1.2 Chapter Overview

### Analytically Tractable Stochastic Stock Price Models

Archil Gulisashvili Analytically Tractable Stochastic Stock Price Models 4Q Springer Contents 1 Volatility Processes 1 1.1 Brownian Motion 1 1.2 s Geometric Brownian Motion 6 1.3 Long-Time Behavior of

### 11. Time series and dynamic linear models

11. Time series and dynamic linear models Objective To introduce the Bayesian approach to the modeling and forecasting of time series. Recommended reading West, M. and Harrison, J. (1997). models, (2 nd

### RUTHERFORD HIGH SCHOOL Rutherford, New Jersey COURSE OUTLINE STATISTICS AND PROBABILITY

RUTHERFORD HIGH SCHOOL Rutherford, New Jersey COURSE OUTLINE STATISTICS AND PROBABILITY I. INTRODUCTION According to the Common Core Standards (2010), Decisions or predictions are often based on data numbers

### Advanced Signal Processing and Digital Noise Reduction

Advanced Signal Processing and Digital Noise Reduction Saeed V. Vaseghi Queen's University of Belfast UK WILEY HTEUBNER A Partnership between John Wiley & Sons and B. G. Teubner Publishers Chichester New

Ronald Christensen Advanced Linear Modeling Multivariate, Time Series, and Spatial Data; Nonparametric Regression and Response Surface Maximization Second Edition Springer Preface to the Second Edition

BASIC PROGRAM FOR THE COURSE STATISTICS APPLIED TO BUSINESS ADMINISTRATION Degree: BA (ADE) Course: 2nd Semester: second Credits: 6 Type: Core Code: 25837 Department of Applied Economics III (Econometrics

### COURSE PLAN BDA: Biomedical Data Analysis Master in Bioinformatics for Health Sciences. 2015-2016 Academic Year Qualification.

COURSE PLAN BDA: Biomedical Data Analysis Master in Bioinformatics for Health Sciences 2015-2016 Academic Year Qualification. Master's Degree 1. Description of the subject Subject name: Biomedical Data

### Basic Black-Scholes: Option Pricing and Trading

Basic Black-Scholes: Option Pricing and Trading BSc (HONS 1 st Timothy Falcon Crack Class), PGDipCom, MCom, PhD (MIT), IMC Contents Preface Tables Figures ix xi xiii 1 Introduction to Options 1 1.1 Hedging,

### Probability Concepts Probability Distributions. Margaret Priest (margaret.priest@wgc.school.nz) Nokuthaba Sibanda (nokuthaba.sibanda@vuw.ac.

Probability Concepts Probability Distributions Margaret Priest (margaret.priest@wgc.school.nz) Nokuthaba Sibanda (nokuthaba.sibanda@vuw.ac.nz) Our Year 13 students who are most likely to want to continue

### Univariate and Multivariate Methods PEARSON. Addison Wesley

Time Series Analysis Univariate and Multivariate Methods SECOND EDITION William W. S. Wei Department of Statistics The Fox School of Business and Management Temple University PEARSON Addison Wesley Boston

### LAGUARDIA COMMUNITY COLLEGE CITY UNIVERSITY OF NEW YORK DEPARTMENT OF MATHEMATICS, ENGINEERING, AND COMPUTER SCIENCE

LAGUARDIA COMMUNITY COLLEGE CITY UNIVERSITY OF NEW YORK DEPARTMENT OF MATHEMATICS, ENGINEERING, AND COMPUTER SCIENCE MAT 119 STATISTICS AND ELEMENTARY ALGEBRA 5 Lecture Hours, 2 Lab Hours, 3 Credits Pre-

### Applied Computational Economics and Finance

Applied Computational Economics and Finance Mario J. Miranda and Paul L. Fackler The MIT Press Cambridge, Massachusetts London, England Preface xv 1 Introduction 1 1.1 Some Apparently Simple Questions

### Course Name: College Algebra - MML Course Number: Math 1513 Semester: Fall 2011. Instructor s Name: Hours Credit: 3

Course Name: College Algebra - MML Course Number: Math 1513 Semester: Fall 2011 Instructor s Name: Hours Credit: 3 Office Phone: Office Hours: I. Course Description: Quadratic equations, functions and

### Monte Carlo Methods in Finance

Author: Yiyang Yang Advisor: Pr. Xiaolin Li, Pr. Zari Rachev Department of Applied Mathematics and Statistics State University of New York at Stony Brook October 2, 2012 Outline Introduction 1 Introduction

### Statistics for Experimenters

Statistics for Experimenters Design, Innovation, and Discovery Second Edition GEORGE E. P. BOX J. STUART HUNTER WILLIAM G. HUNTER WILEY- INTERSCIENCE A JOHN WILEY & SONS, INC., PUBLICATION FACHGEBIETSBGCHEREI

### Third Edition. Philippe Jorion GARP. WILEY John Wiley & Sons, Inc.

2008 AGI-Information Management Consultants May be used for personal purporses only or by libraries associated to dandelon.com network. Third Edition Philippe Jorion GARP WILEY John Wiley & Sons, Inc.

### MEU. INSTITUTE OF HEALTH SCIENCES COURSE SYLLABUS. Biostatistics

MEU. INSTITUTE OF HEALTH SCIENCES COURSE SYLLABUS title- course code: Program name: Contingency Tables and Log Linear Models Level Biostatistics Hours/week Ther. Recite. Lab. Others Total Master of Sci.

### ECON 523 Applied Econometrics I /Masters Level American University, Spring 2008. Description of the course

ECON 523 Applied Econometrics I /Masters Level American University, Spring 2008 Instructor: Maria Heracleous Lectures: M 8:10-10:40 p.m. WARD 202 Office: 221 Roper Phone: 202-885-3758 Office Hours: M W

### Schneps, Leila; Colmez, Coralie. Math on Trial : How Numbers Get Used and Abused in the Courtroom. New York, NY, USA: Basic Books, 2013. p i.

New York, NY, USA: Basic Books, 2013. p i. http://site.ebrary.com/lib/mcgill/doc?id=10665296&ppg=2 New York, NY, USA: Basic Books, 2013. p ii. http://site.ebrary.com/lib/mcgill/doc?id=10665296&ppg=3 New

### Pricing and calibration in local volatility models via fast quantization

Pricing and calibration in local volatility models via fast quantization Parma, 29 th January 2015. Joint work with Giorgia Callegaro and Martino Grasselli Quantization: a brief history Birth: back to

### UNIVERSITY of MASSACHUSETTS DARTMOUTH Charlton College of Business Decision and Information Sciences Fall 2010

UNIVERSITY of MASSACHUSETTS DARTMOUTH Charlton College of Business Decision and Information Sciences Fall 2010 COURSE: POM 500 Statistical Analysis, ONLINE EDITION, Fall 2010 Prerequisite: Finite Math

### How will the programme be delivered (e.g. inter-institutional, summerschools, lectures, placement, rotations, on-line etc.):

Titles of Programme: Hamilton Hamilton Institute Institute Structured PhD Structured PhD Minimum 30 credits. 15 of Programme which must be obtained from Generic/Transferable skills modules and 15 from

### Logistic Regression (1/24/13)

STA63/CBB540: Statistical methods in computational biology Logistic Regression (/24/3) Lecturer: Barbara Engelhardt Scribe: Dinesh Manandhar Introduction Logistic regression is model for regression used

### Graduate Certificate in Systems Engineering

Graduate Certificate in Systems Engineering Systems Engineering is a multi-disciplinary field that aims at integrating the engineering and management functions in the development and creation of a product,