Introduction > Step-by-Step Statistics > Analysing Your Data

Analysing Your Data When you've finished collecting your data, you may find that you've got a mass of numbers that on their own don't really mean anything. If you average out (mean) your treatments you can produce a graph or table that demonstrates what effect your treatments have had on your experiment. But how do you know that treatment a is really different from treatment b? Statistical analyses will give you an indication of whether your results could have happened by 'chance' or if what you are recording is directly related to the treatment you have imposed. Although the mean value is important, it doesn't tell you the whole story - you need to know how much deviation there is from the mean.  Basic statistical tests will help you decide how relevant your differences between treatments are. Exercise If you apply a treatment eg a chemical to a plant, how you can be confident the reduction in root number is directly related to the effects of the chemical?

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