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Credit Course Listing
CQAS-251 Probability and Statistics for Engineers I
Statistics in engineering; enumerative and analytic studies; descriptive statistics and statistical control; sample spaces and events; axioms of probability; counting techniques; conditional probability and independence; distributions of discrete and continuous random variables; joint distributions; central limit theorem. (MATH-182) Class 3, Credit 3 (F, S)
CQAS-252 Probability and Statistics for Engineers II
Point estimation; hypothesis testing and confidence intervals; one- and two-sample inference; introduction to analysis of variance, experimental design, and non-parametric methods.(CQAS-251) Class 3, Credit 3 (F, S)
CQAS-611 Statistical Software
This course is an introduction to two statistical-software packages, SAS and R, which are often used in professional practice. Some comparisons with other statistical-software packages will also be made. Topics include: data structures; reading and writing data; data manipulation, subsetting, reshaping, sorting, and merging; conditional execution and looping; built-in functions; creation of new functions or macros; graphics; matrices and arrays; simulations; select statistical applications. (one of the following: STAT-205, MATH-252, CQAS-252, graduate standing or permission of instructor) Class 3, Credit 3 (F, S) )
CQAS-621 Statistical Quality Control
A practical course designed to provide in-depth understanding of the principles and practices of statistical process control, process capability, and acceptance sampling. Topics include: statistical concepts relating to processes, Shewhart charts for attribute and variables data, CUSUM charts, EWMA charts, process capability studies, attribute and variables acceptance sampling techniques. (one of the following: STAT-145, STAT-205, MATH-252, CQAS-252, graduate standing, or permission of instructor ) Class 3, Credit 3 (F, S)
CQAS-670 Designing Experiments for Process Improvement
How to design and analyze experiments, with an emphasis on applications in engineering and the physical sciences. Topics include the role of statistics in scientific experimentation; general principles of design, including randomization, replication, and blocking; replicated and un-replicated two-level factorial designs; two-level fractional-factorial designs; response surface designs. This course does not count as credit toward the CQAS MS degree. (one of the following: STAT-145, STAT-205, MATH-252, CQAS-252, or permission of instructor) Class 3, Credit 3 (F, S)
CQAS-672 Survey Design and Analysis
This course is an introduction to sample survey design with emphasis on practical aspects of survey methodology. Topics include: survey planning, sample design and selection, survey instrument design, data collection methods, and analysis and reporting. Application areas discussed will include program evaluation, opinion polling, customer satisfaction, product and service design, and evaluating marketing effectiveness. Data collection methods to be discussed will include face-to-face, mail, Internet and telephone. (one of the following: STAT-145, STAT-205, MATH-252, CQAS-252, or permission of instructor) Class 3, Credit 3 (S)
CQAS-682 Lean Six Sigma Fundamentals
This course presents the philosophy and methods that enable participants to develop quality strategies and drive process improvements that are linked to and integrated with business plans. The principles of Lean Six Sigma are presented, making the course a prerequisite for Lean Six Sigma Black Belt certification. (Graduate standing or instructor permission) Class 3, Credit 3 (F, S)
CQAS-683 Lean Six Sigma Project
Students in this course will work on a process improvement opportunity at an organization utilizing the DMAIC (Define, Measure, Analyze, Improve, and Control) approach to problem solving as well as the Lean Six Sigma tools. This course does not count as credit toward the CQAS MS degree. (CQAS-682 corequisite(s): CQAS-621 CQAS-670) Class 3, Credit 3 (F, S)
CQAS-699 Graduate Co-op
See the graduate program coordinator or RIT's Office of Cooperative Education for further details. (Department permission) Credit 0 (F, S, Su)
CQAS-701 Foundations of Experimental Design
This course is an introduction to experimental design with emphases on both foundational and practical aspects. Topics include the role of statistics in scientific experimentation, completely randomized designs, randomized complete block designs, Latin square designs, incomplete block designs, nested designs, general factorial designs, split-plot designs, two-level fractional factorial designs, and response-surface methodology.(One of the following: STAT-205, MATH-252, CQAS-252, or permission of instructor, and CQAS-741 or STAT-305; co-requisite: CQAS-511 or 611 or permission or instructor) Class 3, Credit 3 (F, S)
CQAS-721 Theory of Statistics I
This course introduces the student to the fundamental principles of statistical theory while laying the groundwork for study in the course sequel and future reading. Topics include classical probability, probability mass/density functions, mathematical expectation (including moment-generating functions), special discrete and continuous distributions, and distributions of functions of random variables. (MATH-173 or MATH-282, or permission of instructor; and STAT-205, MATH-252, CQAS-252, graduate standing or permission of instructor) Class 3, Credit 3 (F, S)
CQAS-722 Theory of Statistics II
Building on foundations laid in the first course, this second course in statistical theory answers some of the "How?" and "Why?" questions of statistics. Topics include the sampling distributions and the theory and application of point and interval estimation and hypothesis testing. CQAS-721) Class 3, Credit 3 (F, S)
CQAS-741 Regression Analysis
A course that studies how a response variable is related to a set of predictor variables. Regression techniques provide a foundation for the analysis of observational data and provide insight into the analysis of data from designed experiments. Topics include happenstance data versus designed experiments, simple linear regression, the matrix approach to simple and multiple linear regression, analysis of residuals, transformations, weighted least squares, polynomial models, influence diagnostics, dummy variables, selection of best linear models, nonlinear estimation, and model building. (One of the following: STAT-205, MATH-252, CQAS-252, graduate standing, or permission of instructor; co-requisite: CQAS-511 or CQAS-611 or permission of instructor) Class 3Credit 3 (F, S)
CQAS-747 Principles of Statistical Data Mining I
This course covers topics such as clustering, classification and regression trees, multiple linear regression under various conditions, logistic regression, PCA and kernel PCA, model-based clustering via mixture of gaussians, spectral clustering, text mining, neural networks, support vector machines, multidimensional scaling, variable selection, model selection, k-means clustering, k-nearest neighbors classifiers, statistical tools for modern machine learning and data mining, naïve Bayes classifiers, variance reduction methods (bagging) and ensemble methods for predictive optimality. (CQAS-511, or 611, CQAS-722, CQAS-741, or permission of instructor) Class 3, Credit 3 (F, S)
CQAS-751 Nonparametric Statistics
The emphasis of this course is how to analyze certain designs when the normality assumption cannot be made, with an emphasis on applications. This includes certain analyses of ranked data and ordinal data. The course provides a review of hypothesis testing and confidence-interval construction. Topics include: sign and Wilcoxon signed-rank tests, Mann-Whitney and Friedman tests, runs tests, chi-square tests, rank correlation, rank order tests; and Kolmogorov-Smirnov statistics. (CQAS-701 or equivalent) Class 2, Credit 2 (Su)
CQAS-756 Multivariate Analysis
Multivariate data are characterized by multiple responses. This course concentrates on the mathematical and statistical theory that underlies the analysis of multivariate data. Some important applied methods are covered. Topics include matrix algebra, the multivariate normal model, multivariate t-tests, repeated measures, MANOVA principal components, factor analysis, clustering, and discriminant analysis. (MATH-241, CQAS-721, CQAS-511 or 611, or permission of instructor) Class 3, Credit 3 (F, S)
CQAS-762 SAS Database Programming
This course focuses on the SAS programming language to read data, create and manipulate SAS data sets using Structured Query Language (SQL), creating SAS macros, and SAS programming efficiency. This course covers the material required for "SAS Base Programming" and "SAS Advanced Programming" certification exams. (CQAS-511 or 611) Class 3, Credit 3 (F, S)
CQAS-773 Time Series Analysis and Forecasting
This course is designed to provide the student with a solid practical hands-on introduction to the fundamentals of time series analysis and forecasting. Topics include stationarity, filtering, differencing, time series decomposition, time series regression, exponential smoothing, and Box-Jenkins techniques. Within each of these we will discuss seasonal and nonseasonal models (CQAS-741) Class 3, Credit 3 (F, S)
CQAS-784 Categorical Data Analysis
The course develops statistical methods for modeling and analysis of data for which the response variable is categorical. Topics include: contingency tables, matched pair analysis, Fisher's exact test, logistic regression, analysis of odds ratios, log linear models, multi-categorical logit models, ordinal and paired response analysis. (CQAS-741) Class 3, Credit 3 (F, S)
CQAS-789 Special Topics
This course provides for the presentation of subject matter of specialized value in the field of applied statistics not offered as a regular part of the program. (Graduate status) Class 3, Credit 1-3 (F, S)
CQAS-790 Thesis
For students working toward the MS degree who are writing a research thesis. (Department approval) Credit variable 1-6 (F, S, Su)
CQAS-792 Capstone
This course is designed to provide a capstone experience for MS students at the end of the graduate studies, and will require a synthesis of knowledge obtained from earlier coursework. (CQAS-511 or 611, CQAS-701, CQAS-722, and CQAS-741or STAT-305) Class 3, Credit 3 (F, S)
CQAS-795 Graduate Seminar
This course provides for one or more semesters of study and research activity. This course is required for all first-year full-time funded students in the MS program, (Department approval) Credit 0 (F, S)
CQAS-799 Independent Study
Credit will be assigned at the discretion of the department. A written proposal of the work involved will be required of the candidate, and may be modified at the discretion of the faculty involved before approval is given to proceed. (Department approval) Credit variable 1-3 (F, S)
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