Processing Quantitative Data from Scientific Investigations

Instructor: Marc Chiacchio

Marc has taught Bachelor level students climate science and has a PhD in climate science.

Processing quantitative data from scientific investigations involves using math to understand a scientific concept. In this lesson, we use an Earth science example to explore how data is processed and analyzed to gain scientific understanding.

Instruments of Measurement and Quantitative Data

Imagine a field of crops that is suffering from lack of rain. The farmer who owns the field needs to conduct a scientific investigation to determine how much rain is falling and how much rain is evaporating. In other words, he needs numerical data, also known as quantitative data.

To get the data, the farmer needs to take measurements. There are a lot of different instruments that can be used to obtain numerical measurements, but in this case, the farmer is using a rain gauge and an atmometer.

A rain gauge is an instrument that is placed on the ground so that it can collect and measure rain. Rain gauges usually measure rainfall, or precipitation, in millimeters (mm). An atmometer is an instrument that measures evapotranspiration, which is the amount of water that has evaporated from land surfaces along with the amount of water processed by and evaporated from plants. It also takes measurements in millimeters.

The farmer takes measurements for several weeks and ends up with a lot of quantitative data. His investigation is off to a good start, but before he can draw any conclusions, he must process and analyze the data he obtained.

A rain gauge is an example of an instrument that can be used to collect quantitative data.

Processing Data for Analysis

You may be wondering why the farmer would use two different instruments (a rain gauge and an atmometer). It would probably be easier for the farmer to use just one instrument and study one variable, such as the amount of precipitation, but using two instruments and two variables gives him more information to consider the big picture. Knowing how much rain has fallen and how much water has evaporated allows him to analyze the relationship between the two variables, precipitation and evaporation, and gain a better understanding of its effect on the crops. This is an example of data analysis.

Data analysis involves studying and processing data to draw conclusions about the data and make decisions. To process the data and understand the mathematical relationship between two sets of data, it is important for the data to converted into consistent units of measurement. For example, you wouldn't want to compare inches and yards or ounces and liters. The farmer gets to skip this step because all of his measurements are in the form of millimeters.

Graphing Data for Analysis

It can be easier to process and analyze data if it is displayed in a visual form, such as a graph. In this case, the farmer decides to use an x-y graph, which is a standard analysis graph showing time on the bottom of the graph (x-axis) and the measurement in mm on the vertical axis (y-axis). He uses E to represent evapotranspiration and P to represent precipitation.

A graphical representation of evapotranspiration and precipitation over time
e and p

When the graph is complete, the farmer analyzes the data to see if there is a mathematical relationship between E and P. One of the things he is looking for is an inverse relationship, which occurs when an increase in one number results in a decrease in another number. If P is low when E is high, there is an inverse relationship between the two variables. Understanding this relationship can help the farmer make decisions about when he should check and irrigate his plants for better crop production.

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