Graphing
Tips for drawing a graph by hand
Besides being able to show trends between variables, plotting data on a graph allows us to predict values for which we have taken no data.
When we predict values that fall within the range of data points taken, it is called interpolation. When we predict values for points outside the range of data taken, it is called extrapolation. Extrapolation over too far a range can be unreliable unless it is certain that the observed relationship between the variables continues. Watch the video to learn how to interpolate and extrapolate. When doing this for tests, always rule in the lines that you used to deduce the answer. |
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Note that a scatter plot is not always the most appropriate graph to use. The nature of each variable affects how the data collected is best displayed.
Continuous numerical variable: A numerical variable that can have any number. If dependent and independent variables are both continuous, then the data can be represented by a scatter plot with a trend line. Discrete numerical variable: A variable that can only take a finite number of values such as the number of springs connected together. These can also be represented by a scatter plot but it often does not make sense to connect the points. Otherwise, a column graph can be used. Categorical variable: Something that can be described by a label and not a number, e.g. colour, or material of construction. These can be displayed as a column graph. |