| source UC Santa Barbara (X) |
level |
department Statistics and Applied Probability (X) |
Random variables, sampling distribution, estimation hypothesis testing, correlation and regression, other topics from statistics. Computing labs required.
Score: 10.603783 Details | Listing | Web page
An introduction to statistical methods applied to the analysis of economic data. Topics include basic probability, statistical inference and hypothesis testing, correlation and regression. Computing labs with Excel.
Score: 10.603783 Details | Listing | Web page
Introductory statistics specifically for students in life sciences and related areas. Topics include basic probability, random variables, sampling distributions, estimation, hypothesis testing, correlation and regression. Computing labs with Excel.
Score: 10.603783 Details | Listing | Web page
An introduction to the fundamentals of quantitative analysis to enable students to interpret findings of social research so they will be prepared for advanced coursework in sociology and able to intelligently participate as citizens in an increasingly statistically oriented society.
Score: 10.603783 Details | Listing | Web page
Descriptive methods, histograms, measures of central tendency and spread, probability, random variables, mean and variance, binomial and normal distributions, estimating with random confidence, tests of significance, inference for means and proportions, regression and confidence tests of significance.
Score: 10.603783 Details | Listing | Web page
Lectures and discussions on special topics.
Score: 10.603783 Details | Listing | Web page
Statistical methods for model-free data analysis, including use of ranks in comparing means and assessing correlation, computer-based permutation and bootstrap calculations for significance tests and confidence intervals, estimation of lifetime survival curves. Emphasis on scientific applications.
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Concepts of probability; random variables; combinatorial probability; discrete and continuous distributions; joint distributions, expected values; moment generating functions; law of large numbers and central limittheorems.
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Distribution of sample mean and sample variance; t, x2 and F distributions;summarizing data by statistics and graphs; estimation theory for single samples: sufficiency, efficiency, consistency, method of moments, maximum likelihood; hypothesis testing: likelihood ratio, goodness of fit tests; confidence intervals.
Score: 10.603783 Details | Listing | Web page
Hypothesis tests for means of independent samples and paired data; likelihood ratio tests; nonparametric hypothesis tests: sign, rank, and Mann-Whitney tests; chi-squared goodness-of-fit tests and contingency tables; Bayesian methods of estimating parameters and credible intervals.
Score: 10.603783 Details | Listing | Web page
Linear models; least squares theory; one way and two-way analysis of variance; multiple comparison procedures; fixed, random, and mixed effects models; basic designs including completely randomized design, randomized blocks design, imcomplete block designs, Latin squares, factorial and fractional factorial designs; analysis of covariance.
Score: 10.603783 Details | Listing | Web page
An elementary development of the statistical methods used to design and analyze sample surveys. Basic ideas: estimates, bias, variance, sampling and nonsampling errors; simple random sampling with and without replacement; ratio and regression estimates; stratified sampling; systematic sampling; cluster sampling; sampling with unequal probabilities, multistage sampling. Examples from various fields will be discussed to illustrate the concepts including sampling of biological populations, opinion polls, etc.
Score: 10.603783 Details | Listing | Web page
Linear and multiple regression, analysis of residuals, variable and model selection including stepwise regression, and analysis of covariance. Other topics may include logistic regression, probit analysis, nonlinear regression and nonparametric regression, and correlation methods.
Score: 10.603783 Details | Listing | Web page
In depth SAS programming course. Topics include importing/exporting raw data files, manipulating/transforming data, combining SAS data sets, generating reports, handling syntax and logic errors. Provides preparation for the SAS Institute Certified Professional (Base Programming) Examination.
Score: 10.603783 Details | Listing | Web page
Introduction to data mining techniques. Model assessment and performance evaluation. Data preparation. Programming techniques for transforming raw data into a form suitable for predictive modeling. Extracting data to a form that predictive models can utilize. Incorporating non numeric data in predictive models. Techniques for managing exceptional and extreme data. Building predictive models using SAS Enterprise Miner 5 in SAS 9, including decision trees and neural networks.
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Review of probability; queuing theory; waiting models; birth and death processes; applications; inventive theory; Markov chains, applications, anddecision models; computer simulation; component and system reliability; decision analysis; list and area searching.
Score: 10.603783 Details | Listing | Web page
Basics of probability and statistics; minimum use of calculus; use of statistical packages. topics: probability, random variables, expectation, variance, binomial, normal, and other distributions. statistical inference,estimation and confidence intervals, testing, simple and multivariate regression, analysis of variance, non-parametric inference.
Score: 10.603783 Details | Listing | Web page
Basics of probability and statistics; minimum use of calculus; use of statistical packages. Topics: probability, random variables, expectation, variance, binomial, normal, and other distributions. Statistical inference,estimation and confidence intervals, testing, simple and multivariate regression, analysis of variance, non-parametic inference.
Score: 10.603783 Details | Listing | Web page
Topics include, statistical quality control charts for mean, standard deviation, range, fraction defective, and number of defects; sampling by attributes and variables; acceptance sampling, choice of acceptable quality level, average outgoing quality limit and lot tolerance percent defective values.
Score: 10.603783 Details | Listing | Web page
Random walks, Markov chains, Poisson processes, Markov processes; second order processes, Wiener process stochastic differential equations, optimal prediction, spectral distributions; queueing theory, simulation and applications to mathematical finance.
Score: 10.603783 Details | Listing | Web page
Random walks, Markov chains, Poisson processes, Markov processes; second order processes, Wiener process stochastic differential equations, optimal prediction, spectral distributions; queueing theory, simulation and applications to mathematical finance.
Score: 10.603783 Details | Listing | Web page
Describes mathematical methods for estimating and evaluating asset pricing models, equilibrium and derivative pricing, options, bonds, and the term-structure of interest rates. Also introduces finance optimization models for risk management and financial engineering.
Score: 10.603783 Details | Listing | Web page
Introduction to compound interest. Topics include: measurement of interest,annuities certain, varying annuities, amortization schedules, sinking funds, bonds and related securities, depreciation.
Score: 10.603783 Details | Listing | Web page
Introduction to fixed Income Markets. Topics include: measurement of interest, annuities certain, varying annuities, amortization schedules, sinking funds, bonds and related securities, depreciation.
Score: 10.603783 Details | Listing | Web page
Probabilistic and deterministic contingency mathematics in life and health insurance, annuities, and pensions. Topics include: survival distributions and life tables, life insurance, life annuities, net premiums, net premium reserves.
Score: 10.603783 Details | Listing | Web page