To view this video please enable JavaScript, and consider upgrading to a web browser that supports HTML5 video
Save this PDF as:

Size: px
Start display at page:

Transcription

2 Regression estimates. Double sampling. Prerequisites: graduate standing STAT 3500, 7070, 4710/7710, 4760/7760, or STAT Biostatistics (3).Study of statistical techniques for the design and analysis of clinical trials, laboratory studies and epidemiology. Topics include randomization, power and sample size calculation, sequential monitoring, carcinogenicity bioassay and case-cohort designs. Prerequisite: graduate standing and STAT 3500, 7070, 4710/7710, 4760/7760, or ill STAT Applied Survival Analysis (3).Parametric models; Kaplan-Meier estimator; nonparametric estimation of survival and cumulative hazard functions; log-rank test; Cox model; Stratified Cox model; additive hazards model partial likelihood; regression diagnostics; multivariate survival data. Prerequisite: STAT 3500, STAT 7070, STAT 4710/7710 or STAT 4760/7760 or STAT Applied Longitudinal Data Analysis (3).Repeated measurements; event history studies; linear and nonlinear mixed effects models; growth models; marginal mean and rate models; patternmixture models; selection models; non-informative and informative drop-out; joint analysis of longitudinal and survival data. Prerequisites: STAT 3500, STAT 7070, STAT 4710/7710, or STAT 4760/7760 or STAT Applied Statistical Methods for Bioinformatics (3).Random variables; Point estimation; Multiple t-test; Likelihood principle; Analysis of variance; Probabilistic methods for sequence modeling; Gene expression analysis; Protein structure prediction; Genome analysis; Hierarchical clustering and Gene classification. Prerequisites: graduate standing and STAT 3500, 7070, 4710/7710, 4760/7760, or STAT Applied Statistical Models I (3). Introduction to applied linear models including regression (simple and multiple, subset selection, estimation and testing) and analysis of variance (fixed and random effects, multifactor models, contrasts, multiple testing). No credit toward a graduate degree in statistics. Prerequisite: graduate standing and Statistics [STAT] 3500, 7070, 4710/7710, 4760/7760, or STAT Analysis of Variance (3).Study of analysis of variance and related modeling techniques for cases with fixed, random, and mixed effects. Exposure to designs other than completely randomized designs including factorial arrangements, repeated measures, nested, and unequal sample size designs. Prerequisite: graduate standing and STAT 3500, 7070, 4710/7710, 4760/7760, or STAT Experimental Design (3).Examination and analysis of modern statistical techniques applicable to experimentation in social, physical or biological sciences. Prerequisites: STAT 4530/7530. STAT Applied Multivariate Data Analysis (3).Testing mean vectors; discriminant analysis; principal components; factor analysis; cluster analysis; structural equation modeling; graphics. Prerequisites: STAT 3500, STAT 7070, STAT 4710/7710 or STAT 4760/7760. No credit toward a graduate degree in statistics. STAT Applied Spatial Statistics (3).Introduction to spatial random processes, spatial point patterns, kriging, simultaneous and conditional autoregression, and spatial data analysis. Prerequisites: STAT 4510/7510 or Recommended: Basic knowledge of calculus and matrices.

4 regression), nonlinear regression. No credit toward a graduate degree in statistics. Prerequisites: Statistics [STAT] 4510/7510 or Graduate standing required. STAT Data Analysis I (3).Applications of linear models including regression (simple and multiple, subset selection, regression diagnostics), analysis of variance (fixed, random and mixed effects, contrasts, multiple comparisons) and analysis of covariance; alternative nonparametric methods. Prerequisite: STAT 4710/7710 or 4760/7760 or STAT Data Analysis II (3).Advanced applications including analysis of designs (e.g. repeated measures, hierarchical models, missing data), multivariate analysis (Hotelling's T2, MANOVA, discriminant analysis, principal components, factor analysis), nonlinear regression, generalized linear models, categorical data analysis. Prerequisite: STAT 8310 or STAT Statistical Consulting (3).Participation in statistical consulting under faculty supervision. Formulation of statistical problems. Planning of surveys and experiments. Statistical computing. Data analysis. Interpretation of results in statistical practice. Prerequisites: STAT 4760/7760 and 8320 or STAT Statistical Theory of Bioinformatics (3).Study of statistical theory and methods underpinning bioinformatics. Topics include statistical theory used in biotechnologies such as gene sequencing, gene alignments, microarrays, phylogentic trees, evolutionary models, proteomics and imaging. Prerequisite: STAT 4760/7760. STAT Bayesian Analysis I (3).Bayes' theorem, subjective probability, non-informative priors, conjugate prior, asymptotic properties, model selection, computation, hierarchical models, hypothesis testing, inference, predication, applications. Prerequisites: STAT 4760/7760 and MATH 4140/7140 or STAT Problems in Statistics for Majors - PhD (cr.arr.).approved reading and study, independent investigations, and reports on approved topics. Prerequisites: graduate standing and instructor's STAT Doctoral Dissertation Research in Statistics (cr.arr.).graded on a S/U basis only. STAT Recent Developments in Statistics (3).The content of the course which varies from semester to semester, will be the study of some statistical theories or methodologies which are currently under development, such as bootstrapping, missing data, non-parametric regression, statistical computing, etc. Prerequisites: STAT 4760/7760 and STAT Statistical Computation and Simulation (3).Random number generation, acceptance/rejection methods; Monte Carlo; Laplace approximation; the EM algorithm; importance sampling; Markov chain Monte Carlo; Metropolis-Hasting algorithm; Gibbs sampling, marginal likelihood. Prerequisites: STAT 4760/7760 or instructor s Graduate standing. STAT Theory of Linear Models (3).Theory of multiple regression and analysis of variance including matrix representation of linear models, estimation, testing hypotheses, model building, contrasts, multiple comparisons and fixed and random effects. Prerequisites: STAT 4760/7760 and MATH 4140/7140, and

5 STAT Advanced Linear Models (3).Advanced topics in the theory and application of linear models. Specific content varies with instructor. Prerequisites: STAT 9310 or STAT Multivariate Analysis (3).Distribution of sample correlation coefficients. Derivation of generalized T-squared and Wishart distributions. Distribution of certain characteristic roots, vectors. Test of hypotheses about covariance matrices and mean vectors. Discriminant analysis. Prerequisites: STAT 4760/7760 and MATH 4140/7140 or STAT Survival Analysis (3).Statistical failure models, Kaplan-Meier estimator, Log-rank test, Cox's regression model, Multivariate failure time date analysis, Counting process approaches. Prerequisites: STAT 4760/7760 or STAT Theory of Nonparametric Statistics (3).Estimation, hypothesis testing, confidence intervals, etc., when functional form of the population distribution is unknown. Prerequisites: STAT 4760/7760 or STAT Data Mining and Machine Learning Methods (3).Approaches to estimating unspecified relationships and findings unexpected patterns in high dimensional data. Computationally intensive methods including splines, classifications, tree-based and bagging methods, support vector machines. Prerequisites: Stat 4110/7110, 4760/7760 and 8320 or STAT Bayesian Analysis II (3).Likelihood principle, decision theory, asymptotic properties, advanced topics in Bayesian analysis at the instructor's discretion. Prerequisites: STAT 8640 and 9710 or STAT Mathematical Statistics I (3).Theory of estimation and tests of hypotheses including sufficiency, completeness and exponential families. Neyman-Pearson lemma, most powerful tests, similarity and invariance. Bayes and minimum variance unbiased estimates. Confidence intervals and ellipsoids. Prerequisite: STAT 4760/7760 or STAT Mathematical Statistics II (3).Asymptotic distributions of maximum likelihood estimators, chi-square and likelihood ratio test statistics. EM algorithm, bootstrap, and introduction to generalized linear models. Prerequisites: STAT 9710, MATH 4700/7700 or STAT Advanced Probability (3).(same as Mathematics 8480). Measure theoretic probability theory. Characteristic functions; conditional probability and expectation; sums of independent random variables including strong law of large numbers and central limit problem. Prerequisites: STAT 4750/7750 or MATH 4700/7700 or STAT Stochastic Processes (3).(same as Mathematics 8680). Markov processes, martingales, orthogonal sequences, processes with independent and orthogonal increments, stationary, linear prediction. Prerequisite: STAT 9810 or

Statistics Graduate Programs Kathleen Maurer, Coordinator of Graduate Studies 146 Middlebush Columbia, MO 65211 573-882-6376 http://www.stat.missouri.edu/ About Statistics The statistics department faculty

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

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

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

C: LEVEL 800 {MASTERS OF ECONOMICS( ECONOMETRICS)}

C: LEVEL 800 {MASTERS OF ECONOMICS( ECONOMETRICS)} 1. EES 800: Econometrics I Simple linear regression and correlation analysis. Specification and estimation of a regression model. Interpretation of regression

Lecture/Recitation Topic SMA 5303 L1 Sampling and statistical distributions

SMA 50: Statistical Learning and Data Mining in Bioinformatics (also listed as 5.077: Statistical Learning and Data Mining ()) Spring Term (Feb May 200) Faculty: Professor Roy Welsch Wed 0 Feb 7:00-8:0

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

Learning outcomes. Knowledge and understanding. Competence and skills

Syllabus Master s Programme in Statistics and Data Mining 120 ECTS Credits Aim The rapid growth of databases provides scientists and business people with vast new resources. This programme meets the challenges

Statistics in Applications III. Distribution Theory and Inference

2.2 Master of Science Degrees The Department of Statistics at FSU offers three different options for an MS degree. 1. The applied statistics degree is for a student preparing for a career as an applied

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

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

Learning outcomes. Knowledge and understanding. Ability and Competences. Evaluation capability and scientific approach

Syllabus Master s Programme in Statistics and Data Mining 120 ECTS Credits Aim The rapid growth of databases provides scientists and business people with vast new resources. This programme meets the challenges

Doctor of Philosophy Program in Statistics International Program Faculty of Science and Technology Thammasat University New Curriculum Year 2004

Doctor of Philosophy Program in Statistics International Program Faculty of Science and Technology Thammasat University New Curriculum Year 2004 1. Curriculum Title Doctor of Philosophy Program in Statistics

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

BayesX - Software for Bayesian Inference in Structured Additive Regression

BayesX - Software for Bayesian Inference in Structured Additive Regression Thomas Kneib Faculty of Mathematics and Economics, University of Ulm Department of Statistics, Ludwig-Maximilians-University Munich

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

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

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.

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

Statistics. Master of Arts (MA) Doctor of Philosophy (PhD) Admission to the University. Required Documents for Applications

University of California, Berkeley 1 Statistics The Department of Statistics offers the master of arts (MA) and doctor of philosophy (PhD) degrees. Master of Arts (MA) The program prepares students for

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

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

Master programme in Statistics

Master programme in Statistics Björn Holmquist 1 1 Department of Statistics Lund University Cramérsällskapets årskonferens, 2010-03-25 Master programme Vad är ett Master programme? Breddmaster vs Djupmaster

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

Direct Admission to the Ph.D. Program in Biostatistics

Rationale Direct Admission to the Ph.D. Program in Biostatistics The University of Texas School of Public Health (UTSPH) Division of Biostatistics is in competition for students with some very fine schools

Curriculum - Doctor of Philosophy

Curriculum - Doctor of Philosophy CORE COURSES Pharm 545-546.Pharmacoeconomics, Healthcare Systems Review. (3, 3) Exploration of the cultural foundations of pharmacy. Development of the present state of

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

Statistics. Degrees Offered. Nature of the Programs FACULTY PROFESSORS ASSOCIATE PROFESSORS ASSISTANT PROFESSOR CLINICAL ASSISTANT PROFESSOR

West Virginia University 1 Statistics Degrees Offered Master of Science Master of Data Science Doctor of Philosophy Nature of the Programs The Department of Statistics offers a Master of Science (M.S.)

Economic Order Quantity and Economic Production Quantity Models for Inventory Management

Economic Order Quantity and Economic Production Quantity Models for Inventory Management Inventory control is concerned with minimizing the total cost of inventory. In the U.K. the term often used is stock

Regression Modeling Strategies

Frank E. Harrell, Jr. Regression Modeling Strategies With Applications to Linear Models, Logistic Regression, and Survival Analysis With 141 Figures Springer Contents Preface Typographical Conventions

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

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

Department of Industrial Engineering

Department of Industrial Engineering Master of Engineering Program in Industrial Engineering (International Program) M.Eng. (Industrial Engineering) Plan A Option 2: Total credits required: minimum 39

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

Master of Science (MS) in Biostatistics 2014-2015. Program Director and Academic Advisor:

Master of Science (MS) in Biostatistics 014-015 Note: All curriculum revisions will be updated immediately on the website http://publichealh.gwu.edu Program Director and Academic Advisor: Dante A. Verme,

MATHEMATICS (MAT) Programs Offered. Master of Science. Program Options

Mathematics 117 MATHEMATICS (MAT) 313 Stevenson Hall, (309) 438-8781 Math.IllinoisState.edu Chairperson: George F. Seelinger. Office: 313 Stevenson Hall. Graduate Program Directors: Alberto Delgado, Cynthia

Teaching Biostatistics to Postgraduate Students in Public Health

Teaching Biostatistics to Postgraduate Students in Public Health Peter A Lachenbruch - h s hgeles, California, USA 1. Introduction This paper describes how biostatistics is taught in US Schools of Public

Mathematics & Statistics*

Mathematics & Statistics* MAJOR, MINOR PROFESSOR: Caren L. ASSOCIATE PROFESSOR: Julie M. (chair) VISITING ASSISTANT PROFESSOR: Emese LECTURER: Erin Levering (director of quantitative reasoning center)

List of Ph.D. Courses

Research Methods Courses (5 courses/15 hours) List of Ph.D. Courses The research methods set consists of five courses (15 hours) that discuss the process of research and key methodological issues encountered

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:

Clinical and Translational Science

University of Illinois at Chicago 1 Clinical and Translational Science Mailing Address: School of Public Health (MC 923) 1603 West Taylor Street Chicago, IL 60612-4394 Contact Information: Campus Location:

Machine Learning and Data Analysis overview. Department of Cybernetics, Czech Technical University in Prague. http://ida.felk.cvut.

Machine Learning and Data Analysis overview Jiří Kléma Department of Cybernetics, Czech Technical University in Prague http://ida.felk.cvut.cz psyllabus Lecture Lecturer Content 1. J. Kléma Introduction,

Data, Measurements, Features

Data, Measurements, Features Middle East Technical University Dep. of Computer Engineering 2009 compiled by V. Atalay What do you think of when someone says Data? We might abstract the idea that data are

Information and Decision Sciences (IDS)

University of Illinois at Chicago 1 Information and Decision Sciences (IDS) Courses IDS 400. Advanced Business Programming Using Java. 0-4 Visual extended business language capabilities, including creating

Department/Academic Unit: Public Health Sciences Degree Program: Biostatistics Collaborative Program

Department/Academic Unit: Public Health Sciences Degree Program: Biostatistics Collaborative Program Department of Mathematics and Statistics Degree Level Expectations, Learning Outcomes, Indicators of

Statistical Analysis with Missing Data

Statistical Analysis with Missing Data Second Edition RODERICK J. A. LITTLE DONALD B. RUBIN WILEY- INTERSCIENCE A JOHN WILEY & SONS, INC., PUBLICATION Contents Preface PARTI OVERVIEW AND BASIC APPROACHES

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

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

Bachelor and Master of Science degrees in Mathematics and Statistics at University of Helsinki

Bachelor and Master of Science degrees in Mathematics and Statistics at University of Helsinki Hans-Olav Tylli Department of Mathematics and Statistics University of Helsinki department web-page: http://mathstat.helsinki.fi/index.en.html

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

Silvermine House Steenberg Office Park, Tokai 7945 Cape Town, South Africa Telephone: +27 21 702 4666 www.spss-sa.com

SPSS-SA Silvermine House Steenberg Office Park, Tokai 7945 Cape Town, South Africa Telephone: +27 21 702 4666 www.spss-sa.com SPSS-SA Training Brochure 2009 TABLE OF CONTENTS 1 SPSS TRAINING COURSES FOCUSING

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

Why Taking This Course? Course Introduction, Descriptive Statistics and Data Visualization. Learning Goals. GENOME 560, Spring 2012

Why Taking This Course? Course Introduction, Descriptive Statistics and Data Visualization GENOME 560, Spring 2012 Data are interesting because they help us understand the world Genomics: Massive Amounts

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

: Table of Contents... 1 Overview of Model... 1 Dispersion... 2 Parameterization... 3 Sigma-Restricted Model... 3 Overparameterized Model... 4 Reference Coding... 4 Model Summary (Summary Tab)... 5 Summary

Statistics & Probability PhD Research. 15th November 2014

Statistics & Probability PhD Research 15th November 2014 1 Statistics Statistical research is the development and application of methods to infer underlying structure from data. Broad areas of statistics

Mathematics (MAT) Faculty Mary Hayward, Chair Charles B. Carey Garnet Hauger, Affiliate Tim Wegner

Mathematics (MAT) Faculty Mary Hayward, Chair Charles B. Carey Garnet Hauger, Affiliate Tim Wegner About the discipline The number of applications of mathematics has grown enormously in the natural, physical

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

Research Methods Courses

Research Methods Courses ACCTG 501 ADTED 550 ADTED 551 A ED 502 AEE 520 AEE 521 AEREC 510 AEREC 511 APLNG 578 APLNG 581 BB H 505 Research Methods in Accounting Qualitative Research in Adult Ed (Introduction

PhD Epidemiology

PhD Epidemiology 2014-2015 Note: All curriculum revisions will be updated immediately on the website http://publichealth.gwu.edu Application Due Date: December 1st Program Director Sean D. Cleary, PhD,

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

1. Students will demonstrate an understanding of the real number system as evidenced by classroom activities and objective tests

MATH 102/102L Inter-Algebra/Lab Properties of the real number system, factoring, linear and quadratic equations polynomial and rational expressions, inequalities, systems of equations, exponents, radicals,

Test Code MS (Short answer type) 2004 Syllabus for Mathematics. Syllabus for Statistics

Test Code MS (Short answer type) 24 Syllabus for Mathematics Permutations and Combinations. Binomials and multinomial theorem. Theory of equations. Inequalities. Determinants, matrices, solution of linear

Industrial and Systems Engineering Master of Science Program Logistics and Supply Chain Management

Industrial and Systems Engineering Master of Science Program Logistics and Supply Chain Management Department of Integrated Systems Engineering The Ohio State University Logistics is the science of design,

Probability and Statistics

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

SAS Software to Fit the Generalized Linear Model

SAS Software to Fit the Generalized Linear Model Gordon Johnston, SAS Institute Inc., Cary, NC Abstract In recent years, the class of generalized linear models has gained popularity as a statistical modeling

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

Curriculum for to the PhD Program in Pharmacy Administration

Curriculum for to the PhD Program in Pharmacy Administration Course Hours Course Title BSE 5113 3 Principles of Epidemiology BSE 5163 3 Biostatistics Methods I* BSE 5173 3 Biostatistics Methods II* BSE

Name of the module: Multivariate biostatistics and SPSS Number of module: 471-8-4081

Name of the module: Multivariate biostatistics and SPSS Number of module: 471-8-4081 BGU Credits: 1.5 ECTS credits: Academic year: 4 th Semester: 15 days during fall semester Hours of instruction: 8:00-17:00

Ph.D. Biostatistics 2014-2015 Note: All curriculum revisions will be updated immediately on the website http://www.publichealth.gwu.

Columbian College of Arts and Sciences and Milken Institute School of Public Health Ph.D. Biostatistics 2014-2015 Note: All curriculum revisions will be updated immediately on the website http://www.publichealth.gwu.edu

Statistics 3202 Introduction to Statistical Inference for Data Analytics 4-semester-hour course

Statistics 3202 Introduction to Statistical Inference for Data Analytics 4-semester-hour course Prerequisite: Stat 3201 (Introduction to Probability for Data Analytics) Exclusions: Class distribution:

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

Semester 2 Statistics Short courses

Semester 2 Statistics Short courses Course: STAA0001 - Basic Statistics Blackboard Site: STAA0001 Dates: Sat 10 th Sept and 22 Oct 2016 (9 am 5 pm) Room EN409 Assumed Knowledge: None Day 1: Exploratory

Health Policy and Administration PhD Track in Health Services and Policy Research

Health Policy and Administration PhD Track in Health Services and Policy INTRODUCTION The Health Policy and Administration (HPA) Division of the UIC School of Public Health offers a PhD track in Health

Our Philosophy. Authentic Contexts. Provide relevant and meaningful courseware to promote deeper understanding

AcademyR Revolution Analytics partners with leading minds and industry experts to offer professional training courses designed to give your organization a quick start in building high performance analytical

The School of Statistics (Stat)a was established as the Statistical Training Center (later as the Statistical Center) by the BOR at its 565th

School of Statistics PAARALAN ng ESTADISTIKA Location: Magsaysay Avenue, UP Diliman, Quezon City, 0 Philippines Telephone Number: +6-2-928088 Email Address: updstat@yahoo.com Website: www.stat.upd.edu.ph

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

Semester 1 Statistics Short courses

Semester 1 Statistics Short courses Course: STAA0001 Basic Statistics Blackboard Site: STAA0001 Dates: Sat. March 12 th and Sat. April 30 th (9 am 5 pm) Assumed Knowledge: None Course Description Statistical

CHAPTER 6 EXAMPLES: GROWTH MODELING AND SURVIVAL ANALYSIS

Examples: Growth Modeling And Survival Analysis CHAPTER 6 EXAMPLES: GROWTH MODELING AND SURVIVAL ANALYSIS Growth models examine the development of individuals on one or more outcome variables over time.

When to Use Which Statistical Test

When to Use Which Statistical Test Rachel Lovell, Ph.D., Senior Research Associate Begun Center for Violence Prevention Research and Education Jack, Joseph, and Morton Mandel School of Applied Social Sciences

Modeling and Analysis of Call Center Arrival Data: A Bayesian Approach

Modeling and Analysis of Call Center Arrival Data: A Bayesian Approach Refik Soyer * Department of Management Science The George Washington University M. Murat Tarimcilar Department of Management Science

Quantitative Methods for Finance

Quantitative Methods for Finance Module 1: The Time Value of Money 1 Learning how to interpret interest rates as required rates of return, discount rates, or opportunity costs. 2 Learning how to explain

MATHEMATICS (MAT) Programs Offered. Master of Science. Mathematics

110 Mathematics MATHEMATICS (MAT) 313 Stevenson Hall, (309) 438-8781 Math.IllinoisState.edu Chairperson: George F. Seelinger. Office: 313 Stevenson Hall. Graduate Program Directors: Cynthia Langrall, Michael

Developing a New Freshman Mathematics Course for Biology and Environmental Sciences Majors. Department of Mathematics December 2015

Developing a New Freshman Mathematics Course for Biology and Environmental Sciences Majors. Department of Mathematics December 2015 Programs changing to allow Math 1044 as an alternate to Math 1042: GSTC

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

200609 - ATV - Lifetime Data Analysis

Coordinating unit: Teaching unit: Academic year: Degree: ECTS credits: 2015 200 - FME - School of Mathematics and Statistics 715 - EIO - Department of Statistics and Operations Research 1004 - UB - (ENG)Universitat

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,

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

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

The Applied and Computational Mathematics (ACM) Program at The Johns Hopkins University (JHU) is

The Applied and Computational Mathematics Program at The Johns Hopkins University James C. Spall The Applied and Computational Mathematics Program emphasizes mathematical and computational techniques of

Inferential Statistics

Inferential Statistics Sampling and the normal distribution Z-scores Confidence levels and intervals Hypothesis testing Commonly used statistical methods Inferential Statistics Descriptive statistics are

Analysis of Microdata

Rainer Winkelmann Stefan Boes Analysis of Microdata With 38 Figures and 41 Tables 4y Springer Contents 1 Introduction 1 1.1 What Are Microdata? 1 1.2 Types of Microdata 4 1.2.1 Qualitative Data 4 1.2.2

CHAPTER 3 EXAMPLES: REGRESSION AND PATH ANALYSIS

Examples: Regression And Path Analysis CHAPTER 3 EXAMPLES: REGRESSION AND PATH ANALYSIS Regression analysis with univariate or multivariate dependent variables is a standard procedure for modeling relationships

Applications of Intermediate/Advanced Statistics in Institutional Research

Applications of Intermediate/Advanced Statistics in Institutional Research Edited by Mary Ann Coughlin THE ASSOCIATION FOR INSTITUTIONAL RESEARCH Number Sixteen Resources in Institional Research 2005 Association

MSCA 31000 Introduction to Statistical Concepts

MSCA 31000 Introduction to Statistical Concepts This course provides general exposure to basic statistical concepts that are necessary for students to understand the content presented in more advanced

Faculty of Science School of Mathematics and Statistics

Faculty of Science School of Mathematics and Statistics MATH5836 Data Mining and its Business Applications Semester 1, 2014 CRICOS Provider No: 00098G MATH5836 Course Outline Information about the course

Adequacy of Biomath. Models. Empirical Modeling Tools. Bayesian Modeling. Model Uncertainty / Selection

Directions in Statistical Methodology for Multivariable Predictive Modeling Frank E Harrell Jr University of Virginia Seattle WA 19May98 Overview of Modeling Process Model selection Regression shape Diagnostics

Prerequisite: High School Chemistry.

ACT 101 Financial Accounting The course will provide the student with a fundamental understanding of accounting as a means for decision making by integrating preparation of financial information and written