Search Results

Prism reports the standard error (SE) of best fit parameters determined by nonlinear regression (and the slope and intercept of linear regression).

GraphPad FAQs

... linear regression. One way to do this is with a Lineweaver-Burk plot, which ... Don't use the slope and intercept of a linear regression line to determine values ...

https://www.graphpad.com/guides/prism/latest/curve-fitting/

Is the relationship between each X variable and Y linear? In many experiments, the relationship between X and Y is nonlinear, making multiple regression ...

https://www.graphpad.com/guides/prism/latest/curve-fitting/

Linear transformation distorts the experimental error. Linear regression assumes that the scatter of points around the line follows a Gaussian distribution, and ...

GraphPad FAQs

The goal of linear regression is to adjust the values of slope and intercept to find the line that best predicts Y from X. More precisely, the goal of ...

https://www.graphpad.com/guides/prism/latest/curve-fitting/

Linear regression works by fitting a model that you can use to determine the actual value of Y, given a value of X. This model provides information on the ...

https://www.graphpad.com/guides/prism/latest/curve-fitting/

... regression: •Multiple linear regression (used when Y is continuous). •Poisson regression (used when Y is a count; 0, 1, 2, ...) •Logistic regression (used ...

https://www.graphpad.com/guides/prism/latest/curve-fitting/

Parameter values from multiple regression P values from multiple regression ANOVA table from multiple regression Goodness of fit from multiple regression ...

https://www.graphpad.com/guides/prism/8/curve-fitting/

Standard linear regression assumes that you know the X values perfectly, and all the uncertainty is in Y. It minimizes the sum of squares of the vertical ...

https://www.graphpad.com/guides/prism/latest/curve-fitting/

Prism offers two ways to evaluate the linear dependence of predictors in multiple logistic regression. You may evaluate multicollinearity using variance ...

https://www.graphpad.com/guides/prism/latest/curve-fitting/