Graphing Data Section 1 3 Identifying Variables When

Graphing Data Section 1 -3

Identifying Variables • When performing an experiment it is important that you only change one variable at a time • Variable – any factor that might affect the behavior of an experimental setup • Independent variable - the factor that is changed or manipulated during the experiment • Dependent variable - the factor that depends on the independent variable

Line graph • Line of best fit – the line drawn as close to all the data points as possible • This line can be used to predict future trends in the data • This line is a better representation for the predictions than any one point that makes up the line

Linear Relationships • Linear relationship – when the line of best fit between two variables is a straight line • Ex: y = mx + b • To find the linear equation between two variables you have to find the y-intercept and the slope • Y-intercept – where the line crosses the y-axis • Slope – rise over run, or the change in y divided by the change in x

Non-linear Relationships • Quadratic Relationship – exists when one variable depends on the square of the other • Any relationship that is not a straight line falls into this category • Ex: y = ax 2 + bx + c

Inverse Relationship • Inverse Relationship – results when one variable depends on the inverse of the other • Ex: y = a/x

Predicting Values • You can use relationships from formulas or graphs to predict future values of the experiment • When doing this, the data you are inputting cannot be very far outside of the data you used for the experiment or the formula may not contain that data • Ex: the formula for the stretch of a spring is only good until there is enough weight to break it