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 = ax2 + 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