Before proceeding, you must decide what type of evidence or data is needed to test your hypothesis. In some cases, you can answer your question by making more observations of the phenomenon. For example, you may observe the behavior of butterflies as they pollinate flowers. In other cases, you may find that conducting an experiment in which you manipulate one part of the environment is the best way to answer your question. The nature of the investigation should be matched to the question and the nature of the data needed to address the question. Sincc you will be testing your hypothesis, you should ask yourself how you can best get the evidence needed to make a good decision.
An experiment allows you to control your system so that your conclusions arc less ambiguous. To accomplish diis control, you must consider die factors that may affcct your phenomenon. We call these factors variables; thev can be cither dependent or independent. The value of a dependent variable is determined by the value of an independent variable. For example, the distance traveled by milkweed seed may be dependent on the wind velocity, whereas the reverse is not true. In this ease, the distance is the dependent variable, and the wind velocity is the independent variable. In a controlled experiment, only one independent variable is allowed to changc, while the other independent variables are held constant. The investigator should rccognizc that additional variables may influence the dependent variable but may not be able to be controlled. Any uncontrolled variables should be rccognizcd, and if possible their potential impact should be minimized. Remember, though, that living systems are by nature quite complex and variable. That is why you need to repeat your experiment several times and includc as many replications of the experimental units as you can reasonably handle.
Variables also can be discrete or continuous. A discrete variable is divided into distinct groups, such as dif-
fcrcnt species of plants. A continuous variable has an unlimited number of intermediate values, such as the velocity of the wind or the dry weight of the seeds.
The type of statistical tests to be conductcd should be decided in advance, based on the type of data to be collected. The nature of the data analysis can dictatc the manner in which experimental units arc arranged or randomly selected for measurement. Consulting with a statistician prior to conducting the experiment can save time later. This advance planning will ensure that the experiment is reproducible should you or someone else need to repeat it.
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