Detailed Course Information |
Fall 2015
Oct 22, 2025 |
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| PHP 2550 - Practical Data Analysis |
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Covers practical skills required for successful analysis of scientific data including statistical programming, data management, exploratory data analysis, simulation and model building and checking. Tools will be developed through a series of case studies based on different types of data requiring a variety of statistical methods. Modern regression techniques such as cross-validation, bootstrapping, splines and bias-variance tradeoff will be emphasized. Students should be familiar with statistical inference as well as regression analysis. The course will use the R programming language.
0.000 OR 1.000 Credit hours 0.000 OR 1.000 Lecture hours 0.000 Lab hours Levels: Graduate, Undergraduate Schedule Types: Lab, Primary Meeting Public Health Department Restrictions: Must be enrolled in one of the following Levels: Graduate Prerequisites: Graduate level PHP 2511 Minimum Grade of S and Graduate level PHP 2510 Minimum Grade of S |
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