Master of Applied Statistics

Transcription

1 COLLEGE OF SCIENCE AND MATHEMATICS Master of Applied Statistics Rationale Several workers in business, government, schools and industries find themselves assigned to jobs which require skills in statistical methods. Among them are those working in planning, research, teaching, and in offices which are storage of information needed to be summarized and analyzed. To illustrate some cases, we have: (1) an economist who is tasked to produce the weekly consumer price, analyze trends, and forecast prices for the succeeding weeks; (2) a graduate in sociology conducting a household survey on current political and economic issues; (3) a chemical engineer who is asked to diagnose the quality of a company s product using quality control techniques; and (4) a marine biologist facing a problem as to what experimental design to adopt for his/her internationally funded research project. These are some of the numerous cases of professionals who are not trained on statistical methods needed in preparation for their jobs. Apparently these types of workers are placed in jobs where Statistics becomes a second or alternative career. Objectives The Master of Applied Statistics program aims to 1. provide a strong foundation in statistical methods; 2. introduce the methods for computing and data management. Admission Requirements In addition to the requirements of the University for admission into the MSU IIT Graduate School, an applicant for the degree of Master of Applied Statistics (MAS) program must have a bachelor s degree in any discipline and must have completed at least 24 units of mathematics including the standard calculus sequence. Degree Requirements 1. Complete a total of 39 units of course work which include 26 units of core courses 3 units of elective, 4 units of seminar courses, and 6 units of thesis work. 2. Successful defense of a thesis which is a research work on the application of statistical methods and evaluation of the methods used.

2 Summary of Courses A. Core courses (26 units requirement) Stat 201 Statistical Methods I 3 units Stat 221 Statistical Computing 3 units Stat 231 Statistical Theory 3 units Stat 252 Statistical Methods II 3 units Stat 232 Statistical Inference 3 units Stat 242 Sampling Techniques 3 units Stat 243 Data Collection & Management 2 units Stat 256 Statistical Methods II 3 units Stat 258 Multivariate Methods 3 units B. Elective (3 units requirement) An elective course Is chosen, with the consent of the adviser and program coordinator, from any of the following areas: Behavioral and Social Sciences such as Socio 285 Socio 286 Socio 287 Socio 288 Ethnomethodology Quantitative Sociology Data Processing Advanced Statistics Management Science such as BA 222 BA 223 Quantitative Methods Quantitative Methods II Life Sciences such as Stat 233 Biostatistics Statistics such as Stat 257 Stat 236 Stat 255 Stat 262 Stat 253 Exploratory Data Analysis Stochastic Processes Categorical Data Analysis Non parametric Statistical Techniques Time Series Analysis C. Seminar courses (4 units requirement) Stat 290 Seminar Course in Statistics I 2 units Stat 291 Seminar Course in Statistics II 2 units

3 A student is required to attend and participate in seminars in Statistics where he/she must prepare and present his/her thesis proposal. D. Research Stat 300 Master s Thesis 6 units E. Summary of units Core courses 26 units Elective 3 units Seminar courses 4 units Thesis 6 units Total 39 units Master of Applied Statistics Curriculum FIRST YEAR First Semester Units Lec Lab Stat 201 Statistical Methods I Stat 221 Statistical Computing Stat 231 Statistical Theory I Second Semester Total 9 Stat 252 Statistical Methods II Stat 242 Sampling Techniques Stat 232 Statistical Inference Stat Elective Total 12

4 SECOND YEAR First Semester Stat 243 Data Collection & Management Stat 256 Statistical Methods III Stat 258 Multivariate Methods Stat 290 Seminar Course in Stat.I Total 10 Second Semester Stat 300 Master's Thesis 6 Stat 291 Seminar Course in Stat. II 2 Total 8 Stat 200 Mathematics in Statistics 5 units This course is intended for those who do not meet the mathematics admission requirement of the program. It covers topics on differential calculus, integral, calculus, and matrices. Stat 201 Statistical Methods 1 3 units This is a survey course in basic statistical methods which includes broad topics on frequency distribution; measures of central tendency, dispersion, kurtosis, skewness, association and relationship; sampling and theoretical distributions, estimation; tests of hypothesis; one way ANOVA and some non parametric methods. Stat 220 Statistical Computing (2 units lec/1unit lab) 3 units Introduction to computers and its operating system; principles of programming, DOS program, statistical programming with familiarization to available statistical softwares. Prereq: Adviser s consent Stat 221 Statistical Computing (2 units lec/1 unit lab) 3 units Computer programming using any high level language (Pascal, Fortran, Basic, C, etc.) Programming in SAS, SPSS, and other statistical softwares.

5 Prerequisite: Stat 220 or adviser s consent Stat 231 Statistical theory 3 units This is a course on introductory probability with applications which includes the basic probability structure, the concept of random variables, distribution function, the treatment of expectation and introduction of some special distributions such as binomial, poisson, etc. Stat 232 Statistical Inference 3 units This course involves foundation topics of inference such as methods of estimation, hypothesis testing, sampling distribution. Prerequisite: Stat 201 and Stat 231 Stat 233 Biostatistics 3 units Stat 236 Stochastic Processes 3 units Markov Chains, transition and absolute probabilities, irreducible Markov Chains, stationary stochastic sequences, Markov processes, discontinuous and continuous transitions, non Markovian processes, stationary and stochastic processes. Stat 242 Sampling Techniques 3 units Simple random sampling, stratified random sampling, ratio estimators, regression estimators, systematic sampling, single stage cluster sampling, two stage cluster sampling. Prerequisite: Stat 201 and Stat 231 Stat 243 Data Collection and Management (1 unit lec/ This course includes the study of sample survey design; planning a survey; preparation of questionnaires; processing a data and preparation of reports. Prerequisite: Stat 201 Stat 252 Statistical Methods II This course is a sequel to Statistical Methods I and covers topics in regression analysis and introduction to time series analysis. Regression analysis includes topics on simple linear regression, multiple linear regression, selecting the best regression and regression

6 diagnostics. Time series analysis includes topics on exponential smoothing, introduction to Box Jenkins method and forecasting. Prerequisite: Stat 201 Stat 253 Time Series Analysis (2 units lec Time series, stationary time series, autocorrelation, moving average process, autoregressive time series, prediction, estimation for moving average and autoregressive time series, regression, trend and seasonality, Box Jenkins methodology, forecasting. and Stat 231 Stat 255 Categorical Data Analysis 3 units Categorical data, cross classification tables, analysis using log linear and logit models; casual analysis, incomplete cross classified tables. Stat 256 Statistical Methods III This is an introductory course in experimental designs. It covers topics on principles of experimentation, complete randomized designs, randomized complete block designs, latin square design and other designs. Stat 257 Exploratory Data Analysis (2 units lec/1 unit lab) 3 units Displaying and summarizing batches; re expressing data, analyzing two and three way tables, robust and resistant measures, regression. Stat 258 Multivariate Methods (2 units lec/1 unit lab) 3 units This is an introductory course in multivariate methods that includes matrix operations in multivariate data, multivariate normal distribution, inferences in multivariate data and multivariate techniques such as principal component analysis, factor analysis, discriminant and classification analysis and clustering. Stat 262 Non Parametric Statistical Techniques 3 units Binomial Test, Chi squared one sample test, Kolmogorov Smirnov one sample test, one sample Runs test, sign test, Wilcoxon matched pairs, rank test, median test, Kolmogorov Smirnov two sample test, Wald Wolfowitz run test, Cochran s Q test. Prerequisite: Stat 231

7 Stat 271 Special Topics in Statistics 3 units This course includes any topic of interest in Statistics which are not listed as regular course. This course maybe taken more than once provided that different topics are discussed. Stat 290 Seminar Course in Statistics I 2 units This course is designed to introduce the students to topics that are not covered in other statistics courses. It requires the student to attend and participate in Statistics seminars. Prerequisite: Instructors consent Stat 291 Seminar course in Statistics II 2 units This is the course in which the student prepares and presents his/her thesis proposal. Stat 300 Master s thesis 6 units This is a research work on the application of statistical methods and evaluation of the methods used.