This course is an introduction to statistics with a focus on data analysis. Topics covered during the first half of the course include confidence intervals, hypothesis testing, and linear regression. The second half of the course concerns time-series with topics including exponential smoothing models, autoregressive and moving average models. Topics and methods in cluster analysis such as K-means cluster analysis and hierarchical cluster analysis will be covered near the end of the semester. Students are introduced to practical data analysis skills using statistical software such as SAS or MATLAB, or using the R programming language.
Not open to students who have completed or are taking STA 3155 or STA 4155.
To see the syllabus, click here.
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