Scatter Data
Why scatter plots?
Scatter plots map out data points across two variables. They are known for their exceptional versatility and are a great starting point when it comes to data exploration.
For example, if most data points cluster together while a few stray far from the rest. This is a strong indication of outliers in your dataset.
Data entry
If you select to create a scatter plot a table will be automatically generated with an x-axis column and grouping columns for the y-axis values.
Groups are divided into subcolumns where you can enter individual sample / replicate values.
| X-axis | Group A | Group B | Group C |
|---|---|---|---|
| 5.1 | 3.5 | ||
| 4.9 | 3.0 | ||
| 7.0 | 3.2 | ||
| 6.4 | 2.9 | ||
| 6.3 | 3.3 | ||
| 5.8 | 2.7 |
Only 1 x-axis value can be entered per row.
Have groups that do not share x-values? Simply leave the matching y-values blank and they will be ignored by Graphmatik.
Scatter and Line charts share the same data type, so you can seamlessly switch between these chart types without re-entering any data and explore multiple ways of visualizing your dataset.
Key features
- You can plot numbers, dates or times on the x-axis and numerical values on the y-axis
- Subcolumns are for individual samples within groups and are used to calculate error values.
- Leave y-values blank if your groups do not share x-values
Types of scatter plots
You can create 3 types of scatter charts. Select a plot below to learn more.
Statistical analyses supported
- Descriptive statistics
- Least squares regression (linear, polynomial, exponential, logarithmic & power)
- Non-linear regression (logistic & Michaelis–Menten kinetics)
- Interpolation from a standard curve