Finding Patterns in Your Data

Today you will learn how to look at data and spot patterns, important features, and mistakes.

Data is the information you collect during an investigation, like numbers you measure or things you observe. Imagine your class grows bean plants on the classroom windowsill. Every Monday you measure each plant with a ruler and write the height in your science notebook. After five weeks, you have a whole table full of numbers. Those numbers are your data, but numbers alone do not tell you much until you study them.

So you look closely. You notice that every plant got taller each week. That is a pattern, which is something that repeats or changes in a steady way. You also notice one plant grew much taller than all the others. That is a significant feature, which means a part of the data that stands out and makes you curious. Maybe that plant sat in the sunniest spot. A feature like that can lead you to a new question.

Then you spot something strange. In week three, one plant shows a height of forty centimeters, but in week four it shows nine centimeters. Plants do not shrink like that. This is probably a source of error, which is a mistake in how the data was measured, recorded, or collected. Maybe someone held the ruler wrong or wrote the number in the wrong row. Good scientists do not hide errors. They point them out and, if they can, measure again.

Looking for patterns, features, and errors helps you trust your results. It also helps you explain your thinking with evidence instead of guessing.

Try it: If a classmate records the daily temperature outside in Houston in July as 95 degrees, 97 degrees, 94 degrees, and 12 degrees, which number should you question, and why might that mistake have happened?