17 courses with the subject STAT, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
Introduction to the field of statistics, including sampling, experiments, measurement, descriptive statistics, probability, inference, correlation, regression and prediction. The emphasis will be on data and concepts rather than on calculations and mathematical theory.
An introductory study of statistical methods with applications to business, economics, education, and the social sciences. Topics covered include: descriptive statistics and graphs, probability and probability distributions, estimation, confidence intervals, hypothesis
Introduction to statistical methods with special emphasis on uses in the natural sciences. Topics will include descriptive statistics, data collection, probability distributions, confidence intervals, hypothesis testing, regression, and analysis of variance. The course
An introduction to the art and science of transforming data into information. Working with data using R and RStudio; data collection, wrangling, modelling, and visualization; data storytelling." Background assumed: N.Y.S. Algebra II or equivalent."
Continuation of STAT 200 . Review of the basics of estimation, confidence intervals and hypothesis testing. Simple and multiple regression, time series, analysis of variance and non-parametric methods. A statistical software package will be used extensively.
Basics of probability; descriptive statistics; discrete and continuous distributions; confidence intervals and tests of hypotheses concerning means and proportions; simple linear regression; statistical software. MATH 210 is recommended, in addition to the prerequisites
Simple linear regression and multiple regression including inference, diagnostics and transformations. One-way and multi-way analysis of variance including inference, diagnostics and transformations. Use of professional statistical software.
Techniques for analyzing categorical response data - confidence intervals, tests of significance for a proportion, the difference of two proportions, contingency tables, regression, odds, odds ratios, logistic regression, logit models, loglinear models and diagnostics.
A first course in probability with selected applications. Definition of probability and basic axioms; calculation of probabilities; mutually exclusive and independent events; conditional probability and Bayes Theorem; discrete random variables and distributions; continu
Multivariate distributions, functions of random variables, sampling distributions and central limit theory, theory of estimation, the method of moment and maximum likelihood, and hypothesis testing.
A continuation of STAT 260 : statistical foundations of data science; bootstrap methods; supervised learning; unsupervised learning; simulation; interactive data graphics; working with spatial data and text; working with large data sets.
Independent study of a selected list of readings approved by the faculty advisor. Departmental approval required.
This is a capstone course for the statistics minor. Students will complete a major statistics project. It will include designing an experiment, collecting the data, analyzing the data, and giving oral and written reports explaining the analysis and conclusions. Departme
Selected readings, discussions, data analysis on a topic in statistics. Permission of department required.
Selected readings, discussions, data analysis on a topic in statistics. Permission of department required.
Study of linear time series, moving averages and auto regressive models. Estimation, confidence intervals, forecasting and data analysis with time series models will be examined.
Development of fundamental mathematical tools and language of quantitative risk management. Multivariate probability distributions including joint, conditional and marginal distributions, probabilities, moments, variance and covariance.
Source: SUNY at Fredonia's catalog, linked per course · table learning_unit · CourseShelf publish 61
