Bio100 Appendix G Essay
Although basic trends in your data can sometimes be estimated by simply looking at the data points on your scatter plots, quantitative measures of the effects you are studying can only be determined by fitting a curve to your data.
Curve fitting involves producing a statistically derived best-fit line of data points on the graph; not a hand-drawn or estimated line connecting data points.
Once you have plotted your data, a Plot # tab will appear at the top of the Plot Data screen. Clicking on this tab will take you to the curve-fitting functions of LeafLab and allow you to switch between plots that you generate.
1. Click on the Plot 1 tab to enter the curve-fitting view.
• An enlarged view of the …show more content…
• Error SS Value: is an expression of the calculation of the distances of each data point from the fit line. The lower the Error SS value, the more accurate the line in representing the data.
o To find the lowest possible Error SS value, use the up or down arrows to adjust each parameter: the slope, asymptote, or intercept. o Start with the slope; adjust the slope until you have the Error SS value number as low as possible. Stop when your adjustments cause the Error SS value number to increase. o Then, follow the same process with the asymptote and the intercept. o Continue to adjust the parameters until you get the absolute lowest possible Error SS value. The values that give the smallest Error SS value produce the best-fit line for your data points. Note: this value could be as low as 0.2.
3. Save your plot by clicking on the Export Graph button at the left of the screen. A separate window will now open showing your plot and a table with the intercept, slope, asymptote, and Error SS values. You can save this page by going to File and using the Save As feature of your browser.
Summary: What Did This Experiment Tell Us?
The experiment you just performed is representative