Search Results for “fit”
Residual Plots
This app is an introduction to the idea of residual plots which help interpret the accuracy of a line of fit by making the pattern in the residuals easier to see. An apparently linear data set is used to show how important the residual plot is. (S-ID 6b)
Least Squares
By showing the residuals and/or the residual squares, experiment with a movable line to minimize the sum of the residual squares. This app helps develop an intuitive feel for the process of fitting a line to data, specifically the Least Squares Regression Line. (S-ID 6c)
Residual Basics
This app allows you to experiment with a movable line on a given data set to find the placement with the smallest possible magnitude for the sum of the residuals. (S-ID 6b)
Least Squares II
This app continues with the ideas of minimizing the squared residuals, but allows you to compare the result to the actual regression line. Students can continue to experiment by randomly generating new data for extra reinforcement. (S-ID 6c)
A Path round an elliptical pool
A path of constant width is build round an elliptical pool. Is the outer edge of the path also an ellipse. Drag the red points to try and fit an ellipse. If you can't decide, try making the width of the pool a lot smaller than the length.
A Ladder Problem
Instead of finding the largest ladder which fits round the corner, our spring-loaded device finds the smallest ladder which gets stuck in the corner.
Residual Plots II
This app helps illustrate how the residual plot relates to the proper choice of a function to fit a particular data set. Students should learn to look for a random, scattered pattern to the location of the residuals, rather than a predictable curve shape. (S-ID 6a)
Parabola and catenary
There isn't much difference between a catenary and its approximate parabola. The catenary is the correct model of an ideal chain. But the parabola fits fairly well too.
