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This graduate level course provides an introduction to the basic concepts of probability, common distributions, statistical methods, and data analysis. It is intended for graduate students who have one undergraduate statistics course and who wish to revi…
This graduate level course offers an introduction into regression analysis. A researcher is often interested in using sample data to investigate relationships, with an ultimate goal of creating a model to predict a future value for some dependent variabl…
This is a graduate level course in analysis of variance (ANOVA), including randomization and blocking, single and multiple factor designs, crossed and nested factors, quantitative and qualitative factors, random and fixed effects, split plot and repeated…
The course will cover most of the material in the text, Chapters 1-15. The students will be required to use statistical computer software to complete many homework assignments and the project.
Course ObjectivesTo develop a critical approach to the analysis of contingency tables To examine the basic ideas and methods of generalized linear models To link logit and log-linear methods with generalized linear models To develop basic facility in the…
Students completing this course should be able to:Select appropriate methods of multivariate data analysis, given multivariate data and study objectives; Write SAS and/or Minitab programs to carry out multivariate data analyses; Interpret results of mult…
The aim of this course is to cover sampling design and analysis methods that would be useful for research and management in many field. A well designed sampling procedure ensures that we can summarize and analyze data with a minimum of assumptions and co…
The course examines the methods used in epidemiologic research, including the design of epidemiologic studies and the collection and analysis of epidemiological data. Epidemiology is the study of the distribution and determinants of human disease and hea…
Data mining and statistical learning methods use a variety of computational tools for understanding large, complex datasets. In some cases, the focus is on building models to predict a quantitative or qualitative output based on a collection of inputs. I…
This is a graduate level survey course that stresses the concepts of statistical design and analysis in biomedical research, with special emphasis on clinical trials. SAS for Windows statistical software will be used throughout the course for data analys…
Time series data are intriguing yet complicated information to work with. While this course will provide students with a basic understanding of the nature and basic processes used to analyze such data, you will quickly realize that this is a small first…
STAT 580 (2 credits) and STAT 581 (1 credit) are two separate courses that are taken one after the other; STAT 580 one semester followed by STAT 581 a subsequent semester. Students enroll in the online courses at the end of their program of study. (…
Users of statistics -- researchers, government agencies like the Census Bureau and the Bureau of Labor Statistics, companies like the automakers and drug industry, etc. -- make extensive use of the computer in applying statistical methods to their proble…
STAT 414 focuses on the theory of introductory probability. The course goals are:To learn the theorems of basic probability. To learn applications and methods of basic probability. To develop theoretical problem-solving skills.
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