QS

Probability and Statistical Inference

Basic laws of probability—random events, independence and dependence, expectations, Bayes theorem. Discrete and continuous random variables, density, and distribution functions. Binomial and normal models for observational data. Introduction to maximum likelihood estimation and Bayesian inference. One- and two-sample mean problems, simple linear regression, multiple linear regression with two explanatory variables. Applications in economics, quantitative social sciences, and natural sciences emphasized. Prerequisites: MATH21 or equivalent.

Data Analysis and Statistical Inference – Online

Introduction to statistics as a science of understanding and analyzing data. Major themes include data collection, exploratory analysis, inference, and modeling. Focus on principles underlying quantitative research in social sciences, humanities, and public policy. Research projects teach process of scientific discovery and synthesis, critical evaluation of research and statistical arguments. Perspective given on Samuel Wilks’ quote “Statistical thinking will one day be as necessary a qualification for efficient citizenship as the ability to read and write.” Online equivalent to STA101.

Introduction to Biostatistics

Reading and interpretation of statistical analysis from life and health sciences. Topics include: basic concepts and tools of probability, estimation, inference, decisions analysis, and modeling. Emphasizes role of biostatistics in modern society. Taught at Duke Marine Lab in Beaufort. See department website for placement information. Not open to students with credit for another Statistics 100-level course. One course.

Introductory Biostatistics

Reading and interpretation of statistical analysis from life and health sciences. Topics include: basic concepts and tools of probability, estimation, inference, decisions analysis, and modeling. Emphasizes role of biostatistics in modern society. See department website for placement information. Not open to students with credit for another Statistic 100-level course. One course.

Data Analysis and Statistical Inference for Bass Connections

Introduction to statistics as a science of understanding and analyzing data. Major themes include data collection, exploratory analysis, inference, and modeling. Focus on principles underlying quantitative research in Bass Connection theme areas. Prerequisites: MATH21 or AP Statistics credit. Open only to first year students. Not open to students with Statistics credit above STA30. One course. 

Data Analysis and Statistical Inference

Introduction to statistics as a science of understanding and analyzing data. Themes include data collection, exploratory analysis, inference, and modeling. Focus on principles underlying quantitative research in social sciences, humanities, and public policy. Research projects teach the process of scientific discovery and synthesis and critical evaluation of research and statistical arguments. Readings give perspective on why in 1950, S.

Basic Statistics and Quantitative Literacy

Statistical concepts involved in making inferences, decisions, and predictions from data. Emphasis on applications, not formal technique. Prerequisite: Must have taken placement test and placed in STA30. See website for placement info. Director of Undergraduate Studies consent required. Not open to students with Statistics AP credit, Math AP credit, or credit for MATH105L or higher. One course.

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