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Line graphs are utilized in research reporting when the independent variable on the $$x$$-axis is measured continuously, such as time, or to display correlations between quantitative variables when the independent variable is organized into a small number of distinct levels. Each plotted point on a line graph represents the mean score on the dependent variable for participants at a single level of the independent variable, and these points often include error bars to visualize standard error.

APA Style Line Graphs

Both bar graphs and line graphs serve a fundamental similarity: they illustrate differences in the average score of a dependent variable across the levels of an independent variable. However, the standard convention is to utilize a bar graph for categorical independent variables and a line graph for quantitative or continuous independent variables.

Comparing Bar and Line Graphs

In correlational research, line graphs are commonly used to depict statistical relationships when the variable plotted on the $$x$$-axis has, or is organized into, a small number of distinct values. For example, a line graph can effectively display how the mean of a continuous variable changes across four quartiles of another variable.

Line Graphs in Correlational Research

Researchers use line graphs to plot factorial experiment results when the independent variable assigned to the $$x$$-axis is quantitative and consists of a few distinct levels. Additionally, line graphs are the standard choice for displaying time series data, where the $$x$$-axis represents measurements recorded over a continuous time interval.

Line Graphs in Factorial Designs

An APA-style line graph is particularly useful for presenting experimental results when the independent variable is quantitative or measured continuously. For instance, in the research by Carlson and Conard, a line graph displays the mean scores on a dependent variable for participants at distinct levels of an independent variable. Similar to bar graphs, each data point on the line often includes vertical error bars representing the standard error to visualize variability and statistical significance.

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