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The information provided on this page will help students better understand how to select the best "best fit" curve when graphically analyzing datasets. Most analysis software (such as Google Sheets) will allow students to chose from various "trend" lines/curves when they are attempting to draw conclusions about the relationship between dependent and independent variables from an experiment. R-squared values, explained in the Khan Academy article below, typically range from 0 to 1. For introductory purposes, the closer an R-squared value is to 1, the better a best fit curve/line reflects the trend for the relationship between a dataset's dependent and independent variables. Students should try various best fit curves/lines and chose the one that has the R-squared value closest to 1 to represent the trend.
The information provided on this page will help students better understand how to select the best "best fit" curve when graphically analyzing datasets. Most analysis software (such as Google Sheets) will allow students to chose from various "trend" lines/curves when they are attempting to draw conclusions about the relationship between dependent and independent variables from an experiment. R-squared values, explained in the Khan Academy article below, typically range from 0 to 1. For introductory purposes, the closer an R-squared value is to 1, the better a best fit curve/line reflects the trend for the relationship between a dataset's dependent and independent variables. Students should try various best fit curves/lines and chose the one that has the R-squared value closest to 1 to represent the trend.
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