Introduction to probability, univariate and multivariate probability distributions and their properties, distributions of functions of random variables, random samples and sampling distributions. The course emphasizes the implementation of methods/models using SAS and the interpretation of the results from the output. Data management, queries, data cleaning, data wrangling. Stresses use of computer. Meeting End Time. An introduction to using the SAS statistical programming environment. Show Open Classes Only. Prerequisite: (ST305 or ST312 or ST372) and ST307. Extensions to time series and panel data. Consideration of endogeneity and instrumental variables estimation. Design principles pertaining to planning and execution of a sample survey. Regular access to a computer for homework and class exercises is required. This course will introduce many methods that are commonly used in applications. 2023 NC State University Online and Distance Education. office phone: 919.513.0191. The PDF will include all information unique to this page. General statistical concepts and techniques useful to research workers in engineering, textiles, wood technology, etc. Markov Chain Monte Carlo (MCMC) methods and the use of exising software(e.g., WinBUGS). The U.S. Army is a uniformed service of the United States and is part of the Department of the Army, which is one of the three military departments of the Department of Defense. Raleigh, NC 27695-8203 The emphasis in this class is on the practical aspects of statistical modeling. Historical development of mathematical theories and models for growth of one-species populations (logistic and off-shoots), including considerations of age distributions (matrix models, Leslie and Lopez; continuous theory, renewal equation). No credit for students who have credit for ST305. Includes introduction to Bayesian statistics and the jackknife and bootstrap. NC State University Campus Raleigh, NC 27695-7601 (919) 515-1277 This course will allow students to see many practical aspects of data analysis. Most students take one course per semester while others take a full-time load of three courses per semester. Use of statistics for quality control and productivity improvement. Linear models for nonstationary data: deterministic and stochastic trends; cointegration. Measures of population structure and genetic distance. The Master of Statistics degree requires a minimum of 30 semester hours (ten courses). Maximum likelihood estimation, including iterative procedures. Note: the course will be offered in person (Fall) and online (Spring and Summer). A further examination of statistics and data analysis. Topics are based on the current content of the Base SAS Certification Exam and typically include: importing, validating, and exporting of data files; manipulating, subsetting, and grouping data; merging and appending data sets; basic detail and summary reporting; and code debugging. Experimental design as a method for organizing analysis procedures. First of a two-semester sequence in probability and statistics taught at a calculus-based level.
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