Experiments are the method by which scientists test natural phenomena in the hopes of gaining new knowledge.You will be able to apply the principles of experimental design to your own experiments if you learn the fundamental principles.All good experiments operate according to the logical, deductive principles of the scientific method, regardless of their scope.
Step 1: Pick a topic that interests you.
Experiments that cause scientific paradigm shifts are very rare.The majority of experiments answer questions.Scientific knowledge is built from data from many experiments.Pick a question with a small scope.There are gaps in the current scientific literature.If you want to do an experiment on agricultural fertilization, don't try to answer the question, "Which kind of fertilization is best for plants?"One experiment won't be able to draw universal conclusions about the different types offertilizer and plants in the world.A better question to ask is "What concentration of nitrogen infertilizer produces the largest corn crops?"Scientific knowledge is vast.Before you even start to plan your experiment, research your topic thoroughly.Did past experiments answer the question you want to study?Is there a way to change your topic to address questions left unanswered by previous research?
Step 2: It's time to isolated your variable.
A scientist performs an experiment for a range of values for the variable he's testing for.When doing an experiment, it's important to adjust the specific variable you're testing for.Our scientist would grow multiple corn crops in soil with different nitrogen concentrations in our experiment.Each corn crop would be given the same amount of fertilization.He wouldn't use a higher concentration of magnesium for one of his corn crops if he knew the chemical composition of thefertilizer would not differ.The exact same number and species of corn crops would be grown in the same type of soil each time he replicated his experiment.
Step 3: Make a hypothesis.
A hypothesis is a prediction of the experiment's outcome.Good hypotheses are informed by the background research you performed and the preliminary data you have generated in the lab when choosing your experiment's topic.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.Remember that despite your best research work, your hypothesis may very well not be supported by your results - in this case, you have proven that your prediction was not correct in order to expand your knowledge.A hypothesis is usually a quantitative sentence.The ways that the experimental parameters will be measured are taken into account in a hypothesis.The hypothesis is that corn crops supplemented with 1 pound of nitrogen per bushel will result in a greater yield mass than equivalents grown with differing nitrogen supplements.
Step 4: You should plan your data collection.
You should know when and what kind of data you will collect.This data can be measured at regular intervals or at a set time.In our experiment, we'll measure the weight of our corn crops after a set growing period.We'll compare the nitrogen content of each crop to this one.For experiments that measure the change in a variable over time, it's necessary to collect data at regular intervals.It's important to stick to your plan as close as possible.If you see changes in your results, you can rule out different time constraints as the cause.You can simply insert your data values into the table as you record them if you make a data table prior to that.You should know the difference between dependent and independent variables.A dependent variable is the one that is affected by the independent variable.The dependent and independent variables are "nitrogen content" and "yield" in our example.As the variables change, the table will have columns for them.
Step 5: You should conduct your experiment slowly.
If you want to test for your variable, run your experiment.It almost always requires you to run the experiment multiple times.In our example, we will grow multiple identical corn crops and supplement them with different amounts of nitrogen.The bigger the range of data you can gather, the better.It is possible to record as much data as possible.One of your experimental replications should not include the variable you are testing for.In our example, we will include a corn crop with no nitrogen in it.This will be the baseline against which we'll measure the growth of our other corn crops.All safety measures associated with hazardous materials or processes should be observed in your experiment.
Step 6: Don't forget to collect your data.
If possible, record your data directly into your table, so that you don't have to re-enter and consolidate it later.Know what to look for in your data.If you can, it's a good idea to represent your data visually.Plot data points on a graph and express trends with a line or curve.This will allow you to see patterns in the data.The dependent variable is represented on the vertical y axis in most basic experiments.
Step 7: Come to a conclusion by analyzing your data.
Was your hypothesis correct?There are observable trends in the data.Did you find any new data?Do you have any questions that could be used in a future experiment?As you assess your results, try to answer these questions.If you don't get a definitive "yes" or "no" from your data, consider running additional trials, collecting more data or writing your results up with future directions in mind.Write a paper about your results.The results of most new research must be written and published according to a specific format, dictated by the style guide for a relevant, peer-reviewed academic journal.
Step 8: Define your variables by picking a topic.
For the purpose of this example, we'll use a small-scale experiment.We will test the effects of different aerosol fuels on the firing range of a potato gun.The range of the projectile is dependent on the type of aerosol fuel we use, while the independent variable is the variable we change.Is there a way to make sure each potato projectile has the same weight?Is it possible to give the same amount of aerosol fuel for each firing?The range of the gun can be affected by these.Fuel each shot with the same amount of spray as you weigh each projectile.
Step 9: Make a hypothesis.
Let's say that hair spray has a higher amount of butane than the other sprays.We can think of a reason why the hair spray will send a potato projectile farther.When firing a potato projectile weighing between 250-300 grams, the higher butane content of the aerosol propellant in the hairspray will produce a longer range.
Step 10: Before you collect your data, organize it.
In our experiment, we'll test each aerosol fuel 10 times.Aerosol fuel with no butane will be tested as our experimental control.To prepare, we'll assemble our potato cannon, test it, buy aerosol sprays, and carve and weigh potato projectiles.Before creating our data table, let's create it.The furthest left column will be labeled "Trial #"Each firing attempt will be marked by the numbers 1-10 in the cells in this column.The names of the aerosol sprays will be labeled in the following four columns.The range of each firing attempt will be contained in the ten cells beneath each column.Below the four columns, write the average value of the ranges.
Step 11: The experiment should be done.
The same amount of aerosol spray will be used to fire ten projectiles.We will use a long tape measure to measure the range our projectile traveled after each firing.The data should be in the table.We need to observe certain safety concerns in our experiment.We should wear heavy gloves and close the potato gun's firing cap securely when using aerosol fuels.To avoid accidental injuries from projectiles, we should stand to the side of the gun, not in front of it or behind it.
Step 12: Analyze the data.
We found that the hair spray shot the potatoes the farthest, but the cooking spray was more consistent.We can see the data visually.A scatter plot or box plot is a good way to show the variation in each fuel's firing range.
Step 13: Make your conclusions.
Provide any supporting statistics for your experimental results.We can say with confidence that our hypothesis was correct based on our data.We discovered that the cooking spray produced the most consistent results, something we didn't anticipate.Let's say that the paint from the spray paint built up inside the potato cannon makes it difficult to fire multiple times.We can recommend areas for further research if we have more fuel.We can give the results of our experiment to the world in the form of a scientific paper, but it would be better if we presented the information in a tri-fold science fair display.