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Looking for patterns in data lies at the heart of being a scientist. You should communicate the patterns that you see in your lab report.

For example, if you are doing the experiment on stretching a spring, you should notice that as the mass on the spring increases, the stretch of the spring also increases. There should be a sentence in your lab report that states this explicitly.

Eventually, you’ll use the slope to quantify this relationship, but you should look for the general pattern. If you notice that doubling the mass doubles the stretch, mention that too. Include information on whether the graph has a positive or negative trend. These are the patterns we look for first, then we start doing the mathematical analysis of the trendline.

Once you make your graph, describe it’s shape. Is it linear, close to linear, parabolic, or some other curved shape? You’ll eventually state the equation of best fit (trendline equation), but describe the general shape first. Thinking about this will help you pick the right trendline to apply to the data.

If the data isn’t following the pattern you would expect from the equation being studied, think about whether or not the variables in your equation are the ones you are graphing. Do you need to do further manipulation of the data to get it into the right form. For example, you may have measured the mass, but does the equation include the force of gravity?

Looking for patterns in data starts the moment you start the experiment. Keep your eye out for any trends that you notice and include it in the data analysis/results section of your lab report.