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Descriptive statistics, frequency distributions, probability, binomial and normal distributions, statistical inference, linear regression, and correlation.
Descriptive statistics, frequency distributions, probability, binomial and normal distributions, statistical inference, linear regression, and correlation.
Descriptive statistics, frequency distributions, probability, binomial and normal distributions, statistical inference, linear regression, and correlation.
Statistical analysis, sampling, and experimentation in the agricultural sciences; data collection, descriptive statistics, statistical inference, regression, one fac more...
Statistical analysis and interpretation of data in the biological sciences; probability; distributions; statistical inference for one- and two-sample problems.
Probability concepts; nature of statistical methods; elementary distribution and sampling theory; fundamental ideas relative to estimation and testing hypotheses.
Combinatorial analysis, axioms of probability, conditional probability and independence, discrete and continuous random variables, expectation, limit theorems, additiona more...
Statistical inference: principles and methods, estimation and testing hypotheses, regression and correlation analysis, analysis of variance, computer analysis. more...
08/24/2009-12/11/2009 Credits:
3.0
Prerequisite: STAT 318 or knowledge of basic probability
Random variables; probability density functions; estimation; statistical tests, t-tests; correlation; simple linear regression; one-way analysis of variance; randomize more...
Probability spaces, discrete and continuous random variables, transformations,expectations, generating functions, conditional distributions, law of large numbers, central li more...
Review of distribution models, probability generating functions, transforms, convolutions, Markov chains, equilibrium distributions, Poisson process, birth and death pro more...
Fundamentals and axioms, combinatorial probability, conditional probability and independence, probability laws, random variables, expectation; Chebyshev's inequal more...
Analysis of research data through simple and multiple regression and correlation; polynomial models; indicator variables; step-wise, piece-wise, and logistic regres more...
08/24/2009-12/11/2009 Credits:
3.0
Prerequisite: STAT 500 or equivalent; matrix algebra
Computational foundations of statistics; algorithms for linear and nonlinear models, discrete algorithms in statistics, graphics, missing data, Monte Carlo techniques.
This course introduces data mining and statistical/machine learning, and their applications in information retrieval, database management, and image analysis.
Classical optimal hypothesis test and confidence regions, Bayesian inference, Bayesian computation, large sample relationship between Bayesian and classicalprocedures.
General principles of statistical consulting and statistical consulting experience. Preparation of reports, presentations, and communication aspects of consulting are d more...
Formal courses given on a topical or special interest subject which may be offered infrequently; several different topics may be taught in one year or term.
Formal courses given on a topical or special interest subject which may be offered infrequently; several different topics may be taught in one year or term.
