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How to make a line of best fit in Chart Studio
A line of best fit, also called a trend line or linear regression, is a straight line drawn on a graph that best represents the data on a plot. This line passes through some of the points, all of the points, or none of the points. It can be used to make predictions or to show trends in data. It's a pretty cool feature to add to your plots, so let's get started!
The first step is to head to the Chart Studio workspace and add your data.
After your data's been added, go to GRAPH on the left-hand side, then 'Create'. Choose your 'Chart type', and add your traces using the X and Y dropdown (this section is different depending on the chart type).
Like the way we've styled this plot? For more styling tips, see this tutorial!
When you've finished plotting your data, visit the ANALYSIS section on the left-hand side of your workspace. Click on the blue '+ Analysis' button, then click on the dropdown menu and select 'Fit'.
Select your 'Target Trace' (remember, these are the traces you've set up earlier). You'll then have to select the function you want under 'Function Family'. The dropdown menu has a few to choose from including linear, quadratic, polynomial, and exponential to name a few.
Alternatively, you have the option of adding your own fit function by selecting 'Custom fit function' and entering it in the field. You can also enter your parameters in the 'Constant Estimates' fields.
Your advanced options include fitting to a specific range and/or displaying your fit over a specific range.
The blue 'More' button on the bottom right will display two output options. You have the choice of setting your output with evenly spaced points and using the slider to enter your points, or your points matching your X data.
The last thing to do is click 'RUN' at the bottom. We've chosen the 'Linear' function, and this is what our plot looks like with the line of best fit.
Don't forget to save your graph and show it off to your friends by sharing it. For more information on how to save, share, and export, visit this page!
Instructions : Create a scatter plot using the form below. All you have to do is type your X and Y data and the scatterplot maker will do the rest. Optionally, you can add a title a name to the axes.
How to Use This Scatter Plot Maker?
More about scatterplots : Scatterplots are bivariate graphical devices. The term "bivariate" means that it is constructed to analyze the type of association between to two interval variables \(X\) and \(Y\). The data need to come in the form of ordered pairs \((X_i, Y_i)\), and those pairs are plotted in a set of Cartesian axes.
Typically, a scatterplot is used to assess whether or not the variables \(X\) and \(Y\) have a linear association, but there could be other types of non-linear associations (quadratic, exponential, etc.). The existence of a linear association is assess by establishing how tightly the data are around a straight line.
Data pairs \((X_i, Y_i)\) that are loosely clustered around a straight line have a weak or non-existing linear association, whereas data pairs \((X_i, Y_i)\) that are tightly clustered around a straight line have a strong linear association. Being able to quickly assess the linear association between two variables is one of the main purposes of using a scatter plot generator.
A numerical (quantitative) way of assessing the degree of linear association for a set of data pairs is by calculating the correlation coefficient .
How do you make a scatter plot?
Student often wonder how can they plot a scatter plot. Typically, a scatterplot will be made using some sort of computational software, like Excel. Usually, the styles and color schemes may change a bit, but in general terms the scatter plot you can make with this grapher looks very similar to those provided by Excel or any other different software package.
If you are going to make a scatter plot by hand, then things are a bit more elaborated: You need to deal with the corresponding x and y axes, and their corresponding scales. Then, you need to identify each pair \((X, Y)\), and locate it on the plane, respecting the corresponding scale defined for each of the axes.
How can you describe the correlation of a scatter plot?
A scatterplot is used to assess the degree of linear association between two variables. The stronger the degree of linear association we see, the closer the absolute value of the correlation will be to 1.
In general terms, by looking at the scatterplot we can estimate the strength of the linear association between the two variables, but to get a precise magnitude, we need to compute the numerical value of the corresponding correlation coefficient.
For example, the scatterplot below shows a weak degree of positive linear association, so one would expect the correlation coefficient to be positive but close to zero.
On the other hand, in the scatterplot below we have a moderately strong degree of positive linear association, so one would expect the correlation coefficient to be positive that is relatively close to 1 but not too close.
Finally, in the scatterplot below we have a strong degree of positive linear association, so one would expect the correlation coefficient to be positive that is close to 1.
What other graph makers can I use?
Other graph makers that are available in our site are our Pareto chart maker , pie chart maker, ogive graph and bar chart maker , just to mention a few.