This time, all of the choices are appropriate, even essential.

X and Y axis labels are essential, to describe to a reader exactly what was plotted. To publish this figure you must include a fully informative figure legend, or caption. Usually, but not always, some kind of trendline should be included, to help guide the reader's eye to the relationship.

Axis labels

What information should be included in the X axis label?

Name of the variable
Species studied
Unit of measure
Range of the independent variable

What information should you include in the Y axis label?

Name of the variable
Species studied
Unit of measure
Range of the dependent variable
Dates the measurements were taken

Trend line

You have a wide range of choices for a trend line, including interpolation, curve fits, and a "hand-drawn" trend line. Here are some possibilities. Which will you use for this graph?

line fit

polynomial

exponential

interpolation

freehand

our data

Each type of trend line pictured here is appropriate for certain sets of data, but not for others. No single type of trend line is suitable for all types of data. Look again at our data (lower right image) before you make your decision. NOTE: regardless of the type of trend line you select, it must be confined to the data range. We do not extrapolate a trend line either beyond the highest value of an independent value. We do not take a trend line to the origin unless we have an independent variable at the origin.

Line fit (linear regression)
Polynomial curve
fit
Exponential curve fit
Interpolation
Freehand drawn curve

Previous conclusions

Time is the independent variable, to be plotted on the x axis; height (a measured quantity) is a dependent variable, to be plotted on the y axis. A good choice for plotting these data is to use a scatter plot (XY scatter) of mean values verus time, rather than a scatter plot of raw data; other plot types are not suitable for this kind of data set. We usually must remove some "computer clutter" from a computer-generated graph.