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GraphPad Prism - Regression
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incl. 19 % VAT

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The class covers all methods of regression analysis (linear and nonlinear) which are implemented in GraphPad Prism. Keywords like: linearity, statistical modeling, least squares method, constraints, global fit, model comparisons, dose response curves and enzyme cinetic models will be explained.

Content:

  • Understand statistical principles in regression analysis
  • Master the PRISM interface with respect to linear and nonlinear regression
  • Perform and interpret linear regression
  • Perform and interpret nonlinear regression
  • Professional and fail save data handling, formatting and presentation of graph types specific to regression analysis

Requirements:

You need to be able to master the GraphPad Prism dialog system and output, thus the introductory training Introduction to Data Analysis with GraphPad Prism is a prerequisite. The class also covers the basic statistical know-how needed to understand the different methods.

 

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