The GraphPad Statistics Guide is both a guide to doing statistical analyses with GraphPad Prism 7, and a concise review of statistical principles, emphasizing clear explanations with very little math.
- The essential concepts of statistics
- Ordinal, interval and ratio variables
- When to plot the SD vs SEM
- The most common misunderstanding of P values, and more misunderstandings.
- How to interpret a small P value or a large P value
- An analogy to understand statistical power
- Why Prism doesn't compute the power of tests
- Multiple comparisons traps
- The False Discovery Rate (FDR)
- The lognormal distribution
- A Bayesian perspective on interpreting statistical significance
- Fisher's Least Significant Difference (LSD) test
- Holm-Sidak multiple comparisons
The GraphPad Curve Fitting Guide is both a guide to fitting curves (and lines) with GraphPad Prism 7, and a concise nonmathematical explanation of the principles of linear and nonlinear regression.
New in Prism 7:
- The many uses of global nonlinear regression
- Comparing fits of nonlinear models
- Identifying outliers
- Comparing linear and nonlinear regression
- Comparing linear regression and correlation
- Advice: Avoid Scatchard, Lineweaver-Burke plots, etc.
- Why you shouldn't fit a model to smoothed data
- Interpolating from a standard curve
- Understanding dependency and the covariance matrix
- Plotting a function
- 50% of what? Defining the EC50.
- EC80, EC90, ECanything
- Competitive, noncompetitive and uncompetitive enzyme inhibition