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GraphPad Prism - Regression


incl. 19 % VAT

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.


  • 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


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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