In Origin 2025b, we introduced five new quality charts designed to enhance data analysis and visualization. These include the Symmetry Plot, the Run Chart, the CDF Plot, the Interaction Plot, the Main Effects Plot.
The following sample graphs can be accessed by going to the menu Help:Learning Center and search for 2025b.
- Symmetry Plot
A Symmetry Chart is used to visualize the symmetry or asymmetry of data distributions around a central axis. It consists of mirrored line plots and histograms that reflect data values on either side of a reference line. This chart type is ideal for comparing paired datasets, such as male versus female populations, before-and-after results, or symmetrical structures in scientific analysis. The clear visual alignment helps to easily identify imbalances, correlations, and patterns in the data.
- Run Chart
A Run Chart is a simple line graph that displays data points in chronological order, often used to monitor changes over time. It helps to identify trends, shifts, or cycles in the data by plotting individual observations along a time axis. A central reference line, typically representing the median or average, is often included to highlight deviations from the norm.
- CDF Plot
A CDF (Cumulative Distribution Function) Chart shows the cumulative probability of a variable across its range of values. It plots the probability that a given value is less than or equal to a specified threshold. CDF Charts are particularly useful for understanding the distribution and percentile ranks of data.
- Interaction Plot
An Interaction Plot is used to visualize the interaction effects between two or more independent variables on a dependent variable. It displays the means of the dependent variable for each combination of independent variables. Parallel lines suggest little or no interaction, while non-parallel lines indicate that the effect of one variable depends on the level of another.
- Main Effects Plot
A Main Effects Plot is used to illustrate the effect of individual independent variables on a dependent variable. Each factor is plotted on the x-axis, and the average response of the dependent variable is plotted on the y-axis. A steeper slope in the line indicates a stronger effect on the response, while a flat line suggests minimal impact.
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