| source Duke (X) |
level |
department Statistics and Decision Sciences (X) |
We are exposed daily to studies concerning health, behavior, attitudes, beliefs, and scientific and technological discoveries. How does one use these data and statistical analyses to guide decision making? This course will help students become educated consumers of data.
Score: 11.952229 Details | Listing | Web page
This course introduces students to advanced statistical modeling techniques via the analysis of data from the social science, the natural sciences, and professional and intercollegiate sports data. The course involves reading journal articles with analyses of data, assignments on statistical methods and data analysis, and working on individual and team data analysis projects. In the process, students learn the basics of advanced statistical modeling, including maximum likelihood and Bayesian approaches; generalized linear models; Markov chains; causal inference; and Monte Carlo methods.
Score: 11.952229 Details | Listing | Web page
Statistics 101 introduces principles in the construction and critique of quantitative arguments for research questions in the social and behavioral sciences and public policy.
Score: 11.952229 Details | Listing | Web page
Statistics 101 introduces principles in the construction and critique of quantitative arguments for research questions in the social and behavioral sciences and public policy.
Score: 11.952229 Details | Listing | Web page
Statistics 101 introduces principles in the construction and critique of quantitative arguments for research questions in the social and behavioral sciences and public policy.
Score: 11.952229 Details | Listing | Web page
Statistics 101 introduces principles in the construction and critique of quantitative arguments for research questions in the social and behavioral sciences and public policy.
Score: 11.952229 Details | Listing | Web page
Statistics 101 introduces principles in the construction and critique of quantitative arguments for research questions in the social and behavioral sciences and public policy.
Score: 11.952229 Details | Listing | Web page
Statistics 101 introduces principles in the construction and critique of quantitative arguments for research questions in the social and behavioral sciences and public policy.
Score: 11.952229 Details | Listing | Web page
Statistics 101 introduces principles in the construction and critique of quantitative arguments for research questions in the social and behavioral sciences and public policy.
Score: 11.952229 Details | Listing | Web page
Statistics 101 introduces principles in the construction and critique of quantitative arguments for research questions in the social and behavioral sciences and public policy.
Score: 11.952229 Details | Listing | Web page
Statistics 101 introduces principles in the construction and critique of quantitative arguments for research questions in the social and behavioral sciences and public policy.
Score: 11.952229 Details | Listing | Web page
Statistics 101 introduces principles in the construction and critique of quantitative arguments for research questions in the social and behavioral sciences and public policy.
Score: 11.952229 Details | Listing | Web page
Statistics 103 covers the basic laws of probability and statistical inference. Topics include: random events, independence and dependence, Bayes theorem, discrete and continuous random variables, density, and distribution functions. Expectations and variances of linear combinations of random variables. Introductions to maximum likelihood estimation and Bayesian inference. Hypothesis testing and confidence intervals, and simple linear regression. Applications in economics and quantitative social sciences, and natural sciences emphasized.
Score: 11.952229 Details | Listing | Web page
Statistics 103 covers the basic laws of probability and statistical inference. Topics include: random events, independence and dependence, Bayes theorem, discrete and continuous random variables, density, and distribution functions. Expectations and variances of linear combinations of random variables. Introductions to maximum likelihood estimation and Bayesian inference. Hypothesis testing and confidence intervals, and simple linear regression. Applications in economics and quantitative social sciences, and natural sciences emphasized.
Score: 11.952229 Details | Listing | Web page
Statistics 103 covers the basic laws of probability and statistical inference. Topics include: random events, independence and dependence, Bayes theorem, discrete and continuous random variables, density, and distribution functions. Expectations and variances of linear combinations of random variables. Introductions to maximum likelihood estimation and Bayesian inference. Hypothesis testing and confidence intervals, and simple linear regression. Applications in economics and quantitative social sciences, and natural sciences emphasized.
Score: 11.952229 Details | Listing | Web page
Statistics 103 covers the basic laws of probability and statistical inference. Topics include: random events, independence and dependence, Bayes theorem, discrete and continuous random variables, density, and distribution functions. Expectations and variances of linear combinations of random variables. Introductions to maximum likelihood estimation and Bayesian inference. Hypothesis testing and confidence intervals, and simple linear regression. Applications in economics and quantitative social sciences, and natural sciences emphasized.
Score: 11.952229 Details | Listing | Web page
Statistics 103 covers the basic laws of probability and statistical inference. Topics include: random events, independence and dependence, Bayes theorem, discrete and continuous random variables, density, and distribution functions. Expectations and variances of linear combinations of random variables. Introductions to maximum likelihood estimation and Bayesian inference. Hypothesis testing and confidence intervals, and simple linear regression. Applications in economics and quantitative social sciences, and natural sciences emphasized.
Score: 11.952229 Details | Listing | Web page
Statistics 113 introduces statistical methods used in engineering.
Score: 11.952229 Details | Listing | Web page
Statistics 113 introduces statistical methods used in engineering.
Score: 11.952229 Details | Listing | Web page
Statistics 113 introduces statistical methods used in engineering.
Score: 11.952229 Details | Listing | Web page
Statistics 113 introduces statistical methods used in engineering.
Score: 11.952229 Details | Listing | Web page
Statistics 113 introduces statistical methods used in engineering.
Score: 11.952229 Details | Listing | Web page
This course is an introduction to the concepts, theory and application of modern statistical inference. Topics eveloped include the basic structure of statistical problems, probability modelling and statistical inference, elements of data analysis and statistical computing, and linear regression modelling. Inference is developed from the viewpoints of modern Bayesian statistical science, with some
Score: 11.952229 Details | Listing | Web page
This course is an introduction to the concepts, theory and application of modern statistical inference. Topics eveloped include the basic structure of statistical problems, probability modelling and statistical inference, elements of data analysis and statistical computing, and linear regression modelling. Inference is developed from the viewpoints of modern Bayesian statistical science, with some
Score: 11.952229 Details | Listing | Web page
This course is an introduction to the concepts, theory and application of modern statistical inference. Topics eveloped include the basic structure of statistical problems, probability modelling and statistical inference, elements of data analysis and statistical computing, and linear regression modelling. Inference is developed from the viewpoints of modern Bayesian statistical science, with some
Score: 11.952229 Details | Listing | Web page