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Scatter plot maker. Create xy graph online. This website uses cookies to improve your experience, analyze traffic and display ads. Create online graphs and charts. Choose from different chart types, like: line and bar charts, pie charts, scatter graphs, XY graph and pie charts.

Format Graph dialog - XY graphs

Use this dialog to change the look of all the symbols in a data set. If you want to change the look of a single data point, use the right-click menu. You can also change all the symbols in selected data sets.

Double-click on any graph symbol or bar to open the Format Graph dialog.

To change the settings for one data set:

Select a data set from the list, and choose the symbols, lines, and error bars for that data set. Then select another data set and choose settings for that data set. Click OK to redraw the graph with all the changes. Note that a fitted curve is treated as a separate data set.

To change all data sets on the graph for example to make all symbols larger:

Click the Global button at the top right of the Format Axis dialog. Then choose to change all data sets, or a subset of data sets. Changes you make after that will then apply to all selected data sets.

There is a shortcut for changing all -- Hold down the control key. (Note the 'globe' cursor since you are making global changes.)

Style

Choose how to plot error bars. Select SD, SEM, 95% CI, or range. If you created a data table with no Y subcolumns, you won't have any choices here. But, if you entered data into subcolumns, the choices here determine how the replicates or error bars will appear. The Appearance drop-down on the left determines the basic look, with further choices in the Plot drop-down to the right (the choices will depend on what you select in Appearance).

Since it rarely makes sense to choose different error bar (or replicate) choices for different data sets, you will probably want to click Global and then All before changing error bar format.

If you have four or more subcolumns for replicates, Prism will also give you the opportunity (at the bottom of the appearance drop down menu) to plot box-and-whiskers at each X value.

Show symbols

Choose symbol type, size, and color. If you pick an open symbol, also select a border thickness. Check the Clear option if you want point-to-point lines and overlapping points to show through the open symbol. Use the Shape drop-down menu to select one of Prism's symbols. Use the More option on this drop-down to use any character from any font on your computer as a symbol.

Show bars/spikes/drop lines

Use this setting if you want to drop vertical bars from your data points. The bar will start at the X-axis or whatever Y value you choose and go up (or down) to the Y position of the point. This is useful when you want to create a bar graph where each bar’s position is determined by its X value. It is also useful when you want to combine points and bars on one graph as shown below. If you pick the narrowest width for the bars, the bars will actually be spikes suitable for graphing mass spectra.

Show error bars

Choose the format and color of error bars. Choose dotted or solid lines to show an error envelope as in the graph on the right below. Use the Show Area Fill button to add fill between the limits of the error envelope.

Connecting line/curve

Choose the line's color, style (straight vs. staircase), thickness, and pattern (solid, dotted, dashed, etc.). This section includes choices to have your connecting start either at the first data point or the graph origin, whether to leave gaps in the connecting line next to the symbols, and whether to plot lines connecting each replicate for repeated measures in corresponding data sets as in the graph on the bottom row below.

If you choose arrows as connecting lines, it looks best to not also show symbols.

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Don't confuse the connecting line – which always goes from point to point – with a best-fit curve or line created by regression. If you have fit a curve through the data, Prism sees the curve as a separate data set. Select the data set for the values, and choose symbols but no connecting line. Then choose the data set for the curve, and choose a connecting line (curve) with no symbols.

Area fill

Fill below (or above) the point-to-point line that connects your points with a fill. Specify fill color and pattern, and background color. You may need to adjust the front-to-back order of the data sets to get the effect you want.

Plot on which Y axis

Specify which axis to use for each data set. If you choose to plot on the right Y-axis, Prism will create that axis if it doesn’t already exist.

Legend

Select Show legend to create a legend for this data set. Select Label each point with its row title to link the legend to the column title entered on the data table. Uncheck this box if you don’t want the legend to change when you edit the column title. You can also edit the labels in the legend. Double-click on the legend text and type whatever you like. Use the checkbox Revert Legend to Column Titles in the Legend to change the labels back to match the column titles. (This checkbox is only available if you have edited a legend.)

Label each point with its row title

Check this box to include row titles on graph near each data point. You can move each label by selecting it and dragging. Even if you move a label, however, it remembers its position relative to the data point -- so when you change your data, or the size and shape of your graph, the labels will adjust accordingly. Click on any label on the graph and use the Text section of the Prism toolbar to change the size, font, and color of all the labels.

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A Scatter (XY) Plot has points that show the relationship between two sets of data.

In this example, each dot shows one person's weight versus their height.

(The data is plotted on the graph as 'Cartesian (x,y) Coordinates')

Example:

The local ice cream shop keeps track of how much ice cream they sell versus the noon temperature on that day. Here are their figures for the last 12 days:

And here is the same data as a Scatter Plot:

It is now easy to see that warmer weather leads to more sales, but the relationship is not perfect.

Line of Best Fit

We can also draw a 'Line of Best Fit' (also called a 'Trend Line') on our scatter plot:

Try to have the line as close as possible to all points, and as many points above the line as below.

But for better accuracy we can calculate the line using Least Squares Regression and the Least Squares Calculator.

Example: Sea Level Rise

Interpolation and Extrapolation

Interpolation is where we find a value inside our set of data points.

Here we use linear interpolation to estimate the sales at 21 °C.

Extrapolation is where we find a value outside our set of data points.

Here we use linear extrapolation to estimate the sales at 29 °C (which is higher than any value we have).

Careful: Extrapolation can give misleading results because we are in 'uncharted territory'.

As well as using a graph (like above) we can create a formula to help us.

Example: Straight Line Equation

We can estimate a straight line equation from two points from the graph above

Let's estimate two points on the line near actual values: (12°, $180) and (25°, $610)

First, find the slope:

Now put the slope and the point (12°, $180) into the 'point-slope' formula:

y − y₁ = m(x − x₁)

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y − 180 = 33(x − 12)

y = 33(x − 12) + 180

y = 33x− 396 + 180

y = 33x− 216

INTERpolating

Now we can use that equation to interpolate a sales value at 21°:

y = 33×21° − 216 = $477

EXTRApolating

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And to extrapolate a sales value at 29°:

y = 33×29°− 216 = $741

The values are close to what we got on the graph. But that doesn't mean they are more (or less) accurate. They are all just estimates.

Don't use extrapolation too far! What sales would you expect at 0° ?

y = 33×0° − 216 = −$216

Hmmm... Minus $216? We extrapolated too far!

Note: we used linear (based on a line) interpolation and extrapolation, but there are many other types, for example we could use polynomials to make curvy lines, etc.

Correlation

When the two sets of data are strongly linked together we say they have a High Correlation.

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The word Correlation is made of Co- (meaning 'together'), and Relation

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• Correlation is Positive when the values increase together, and
• Correlation is Negative when one value decreases as the other increases

Like this:

(Learn More About Correlation)

Negative Correlation

Correlations can be negative, which means there is a correlation but one value goes down as the other value increases.

It has a negative correlation (the line slopes down)

Note: I tried to fit a straight line to the data, but maybe a curve would work better, what do you think?