Experimentation is the method by which scientists analyze natural phenomena in the hope of obtaining new knowledge. Good experiments follow a logical design to isolate and test precisely and specifically defined variables. By learning the fundamental principles of experimental design, you can then apply them to your own experiments. Regardless of their scope, all quality experiments operate according to the logical and deductive principles of the scientific method, from the potato-driven clock of the fifth grade science fair to cutting-edge research related to the Higgs boson.
Part 1 of 2: Design a Scientifically Valid Experiment
Step 1. Choose a specific topic
Experiments whose results cause radical shifts in the scientific paradigm are very, very rare. The vast majority of experiments answer small, specific questions. Scientific knowledge is built from the accumulation of data from countless experiments. Pick a topic or unanswered question that is small and verifiable in scope.
- For example, if you want to do an experiment with agricultural fertilizers, don't try to answer the question, "What type of fertilizer is best for growing plants?" There are many different types of fertilizers and plants in the world, so an experiment will not be able to draw universal conclusions about it. A much more appropriate question to design an experiment on this would be "What concentration of nitrogen in the fertilizer produces the largest corn crops?"
- Modern scientific knowledge is very, very broad. If you are doing serious scientific research, do your research on your topic in depth even before you start planning your experiment. Are there past experiments that have answered the question you want to study with your experiment? If so, is there a way to adjust the topic to address questions that have not yet been answered by existing research?
Step 2. Isolate your variables
Quality science experiments test specific and measurable parameters called variables. Generally speaking, a scientist performs an experiment for a range of values of the variable he is studying. An important issue when conducting an experiment is adjusting only the specific variables you are studying (and not the rest of the variables).
- For example, in our case of fertilizers, our scientist would grow several corn crops in a soil with fertilizers whose nitrogen concentration is different. He should give every corn crop exactly the same amount of fertilizer. Then you should make sure that the chemical composition of the fertilizers you used does not differ in anything except their nitrogen concentration. For example, you shouldn't use a fertilizer with a higher magnesium concentration than the rest. Also, you should grow exactly the same number and species of corn crops at the same time and in the same type of soil each time you repeat the experiment.
Step 3. Build a hypothesis
A hypothesis is basically a prediction of the outcome of the experiment. It should not be a blind guess, good hypotheses should be supported by research you did when choosing the topic of the experiment. Base your hypothesis on the results of similar experiments carried out by colleagues or, if you are facing a problem that has not been studied in depth, base it on the combination of literature research and the observation that you can make. Remember that even though your research work is the best, your hypothesis may still be incorrect. If this happens, you will not have wasted your time, as you will expand your knowledge by proving that your prediction was wrong.
Typically, a hypothesis is expressed as a quantitative declarative phrase. A hypothesis also takes into account the ways in which the experimental parameters will be measured. A good hypothesis for our fertilizer example is: "Corn crops supplemented with 450 grams (one pound) of nitrogen for every 25 kilograms (one bushel) will result in a higher yield mass than equivalent corn crops grown with supplements. of different nitrogen "
Step 4. Plan your data collection
Know in advance when you are going to collect the data and what kind of data you are going to collect. It measures this data at a set time or, in other cases, at regular intervals. In our fertilizer experiment, for example, the weight of corn crops (in kilograms) will be measured after establishing a growing period. This will be compared with the nitrogen content of the fertilizer with which each crop was treated. For other experiments (such as those that measure the change of a variable over time), it is necessary to collect data at regular intervals.
- Making a data table before you start is a great idea. With this table you will only have to place the values of your data as you document them.
- Learn to differentiate the dependent variables from the independent ones. An independent variable is one that, when changing, affects a dependent variable. In our example, "Nitrogen content" is an independent variable and "Yield (in kilograms)" is the dependent variable. A basic table will have columns for both variables as they change over time.
Step 5. Carry out your experiment methodically
Do your experiment and study your variables. This almost always requires running the experiment several times to obtain values for different variables. In our fertilizer example, several identical corn crops will be grown supplemented with fertilizers containing different amounts of nitrogen. Generally, the greater the range of data you can collect, the better. Document as much data as possible.
- A good experimental design incorporates what is known as control. One of your experimental replicas should not include the variable you are studying for the rest of the replicas. In our fertilizer example, a maize crop that does not receive nitrogen will be included. This will be the control replica and will serve as the basis for measuring the growth of the rest of the crops.
- Look at each and every safety measure associated with hazardous materials or processes in your experiment.
Step 6. Gather your data
If possible, document your data directly in your table. This will save you the headache of re-entering and consolidating your data later. Learn to evaluate the outliers in your data.
If you can, it is always advisable to represent your data visually. Arrange the data points on a graph and express the trends with the best-fitting line or curve. This will help you (and anyone else viewing the graph) to visualize patterns within the data. For most basic experiments, the independent variable is plotted on the horizontal x axis and the dependent variable on the vertical y axis
Step 7. Analyze your data and come to a conclusion
Was your hypothesis correct? Were there any observable trends in the data? Did you find any unexpected data? Do you have any unanswered questions that could serve as the basis for a future experiment? Try to answer these questions as you evaluate your results. If your data does not give your hypothesis a definitive "yes" or "no", consider conducting additional experimental trials and gathering more data.
To share your results, write a comprehensive scientific article. Knowing how to write a scientific essay is a very useful skill. The results of the vast majority of recent research must be written and published according to certain specifications
Part 2 of 2: Run an Example Experiment
Step 1. Choose a theme and define your variables
For the purposes of this example, a simple, small-scale experiment will be chosen. In this experiment, the effects of different aerosol fuels on the firing range of a potato launcher will be analyzed.
- In this case, the type of aerosol fuel used is the independent variable (the variable that is modified), while the range of the projectiles is the dependent variable.
- Things to consider for this experiment: Is there a way to make sure that each potato shell has the same weight? Is there a way to deliver the same amount of aerosol fuel for each shot? These aspects can affect the caster's firing range. Weigh each projectile before conducting the experiment and load each shot with the same amount of aerosol.
Step 2. Create the hypothesis
If you're going to try hair spray, cooking spray, and spray paint, let's say hair spray has a propellant with a higher amount of butane than other sprays. Because butane is flammable, it is possible to hypothesize that the hair spray will produce a greater propulsive force upon ignition, sending the potato projectile farther. The hypothesis should be written as: "The high butane content of the propellant spray in the hair spray will, on average, produce a longer range when a potato projectile weighing 250-300 grams is fired."
Step 3. Organize your data collection in advance
In this experiment, each aerosol fuel will be tested 10 times and the results will be averaged. An aerosol fuel that does not contain butane will also be tested and used as an experimental control. To prepare, the potato launcher will be assembled, tested to make sure it works, the spray will be purchased, and the potatoes will be cut and measured.
- A table will also be created. This will have five vertical columns:
- The leftmost column will be labeled "Test #". The cells in this column will simply contain the numbers 1 through 10, representing each shot attempt.
- The next four columns will have the name of the aerosol that will be used for the experiment. The ten cells below the header of each column will contain the range (in meters) of each shot attempt.
- Under the four columns for each fuel, leave a space to write the average value of the ranges.
Step 4. Carry out the experiment
Each aerosol will be used to fire ten projectiles, using the same amount of aerosol for each shot. After each shot, a tape measure will be used to measure the range that the projectile traveled. This information will then be documented in the data table.
As in many experiments, this experiment has certain safety concerns to be aware of. The aerosol fuel used is flammable, so be sure to close the firing cap on the potato launcher securely and wear thick gloves while lighting the fuel. To avoid accidental injury from projectiles, you also need to make sure you are (and any bystanders) to the side of the launcher, not in front of or behind it
Step 5. Analyze the data
Let's say that it was found, on average, that the hair spray throws the potatoes farther than the others, but the kitchen spray was the most consistent. It is possible to represent this data visually. A good way to represent the average range for each spray is with a bar graph, while scatterplots are useful for showing the variation of the ranges for each shot.
Step 6. Draw your conclusions
Reflect on the results of your experiment. Based on the data, it is safe to say that the hypothesis was correct. It can also be said that something was discovered that was not predicted, that cooking spray produces the most consistent results. It is possible to make a report on any problems or mistakes made. Let's say paint from the spray paint built up inside the potato launcher's combustion chamber, hindering the ability to make successive shots. Finally, areas can be recommended for future research, for example, perhaps a larger amount of fuel will achieve better ranges.
The results can even be shared with the world through a scientific trial. Given the theme of this experiment, it may be more appropriate to present this information in a triptych for display at a science fair
- Have fun and stay safe.
- Science is about asking big questions. Don't be afraid to choose a topic that you haven't looked at before.
- Wear eye protection
- If something gets in your eyes, wash them thoroughly with water for at least 5 minutes.
- Do not leave food or drinks near your workplace.
- Wash your hands before and after the experiment.
- When using sharp knives, dangerous chemicals, or very hot flames, make sure you are under the supervision of an adult.
- Wear rubber gloves when handling chemicals.
- Put your hair up before you start