In our fertilizer experiment, for instance, we'll measure the weight of our corn crops (in kilograms) after a set growing period. Measure this data at a set time or, in other cases, at regular intervals. Know beforehand when you will collect data and what kind of data you will collect. A good hypothesis for our fertilizer example is: "Corn crops supplemented with 1 pound of nitrogen per bushel will result in a greater yield mass than equivalent corn crops grown with differing nitrogen supplements." A hypothesis also takes into account the ways that the experimental parameters will be measured. Typically, a hypothesis is expressed as a quantitative declarative sentence.Remember that despite your best research work, your hypothesis may very well not be supported by your results - in this case, you've still expanded your knowledge in the sense that you have proven that your prediction was not correct. Base your hypothesis on the results of similar experiments conducted by peers in your field, or, if you're tackling a problem that hasn't been well-studied, base it on whatever combination of literature research and recorded observation you can find. It shouldn't be a blind guess - good hypotheses are informed by the background research you performed and/or preliminary data you may have already generated in the lab when choosing your experiment's topic. A hypothesis is essentially a prediction of the experiment's result. He would also grow the exact same number and species of corn crops at the same time and in the same type of soil in each replication of his experiment. He would make sure the chemical composition of his fertilizers used did not differ in some way besides its nitrogen concentration - for instance, he would not use a fertilizer with a higher concentration of magnesium for one of his corn crops. He would give each corn crop the exact same amount of fertilizer. For instance, in our fertilizer experiment example, our scientist would grow multiple corn crops in soil supplemented with fertilizers whose nitrogen concentration differs.One vital concern when performing an experiment is to adjust only the specific variable(s) you are testing for (and no other variables.) X Trustworthy Source Science Buddies Expert-sourced database of science projects, explanations, and educational material Go to source In general terms, a scientist performs an experiment for a range of values for the variable he's testing for. Good scientific experiments test specific, measurable parameters called variables. Have past experiments answered the question you want your experiment to study? If so, is there a way to adjust your topic so that it addresses questions left unanswered by existing research? If you intend to do serious scientific research, research your topic extensively before you even begin to plan your experiment. Modern scientific knowledge is very, very vast.A much better question to design an experiment around would be "What concentration of nitrogen in fertilizer produces the largest corn crops?"
For instance, if you want to do an experiment on agricultural fertilizer, don't seek to answer the question, "Which kind of fertilizer is best for growing plants?" There are many different types of fertilizer and many different kinds of plants in the world - one experiment won't be able to draw universal conclusions about either.X Trustworthy Source Science Buddies Expert-sourced database of science projects, explanations, and educational material Go to source To get ideas, look for gaps in the current scientific literature. Pick a topic or an unanswered question with a small, testable scope. Scientific knowledge is built upon the accumulation of data from countless experiments. The vast majority of experiments answer small, specific questions. Experiments whose results cause sweeping scientific paradigm shifts are very, very rare.
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