# 1-D Spatial Data

One-dimensional spatial data is very common in all geoscience related disciplines. Spatial trends or patterns are of key interest. The graph at left is a gamma ray well log from Reading the Rocks from Wireline Logs (more info) , put out by the Kansas Geological Survey. Geoscientists typically use gamma ray logs to infer shale content versus depth.

As another example, the image at left shows the vertical profile of both ozone (on July 8 and October 6) and temperature (October 6) over the South Pole. Plotting several variables on the same plot can help make comparisons easier and can also help infer causal relationships between variables. Note that the lowest ozone concentrations are located where temperatures are low enough to allow Polar Stratospheric Clouds to form.

A working knowledge of fundamental statistics (mean, variance, standard deviation, and correlation, and linear regression or trend analysis) is an important aspect of working with bivariate data. learn more here

Graphs are often used to help students visualize data. Having students make their own graphs, read data/information from graphs, and describe graphs in their own words are all important "Using Data" learning objectives. learn more here