Experimentation is the method by which scientists test natural phenomena in the hope of gaining new knowledge. Good experiments follow a logical path to isolate and experiment with specific and well-defined variables. By learning the basics of the experimental process, you will learn to apply these principles to your experiments. Regardless of their purpose, all good experiments operate according to the logical and deductive principles of the scientific method, from the school's "potato" clock designs to the cutting-edge research of the Higgs boson.
Steps
Part 1 of 2: Design an Experiment That Sounds Scientific
Step 1. Choose a specific topic
Experiments whose results disrupt entire scientific paradigms are very, very rare. The vast majority of experiments answer small and specific questions. Scientific knowledge is based on the accumulation of data obtained from countless experiments. Choose an unanswered topic or question that is small and verifiable in scope.
- For example, if you want to conduct an experiment on agricultural fertilizer, don't try to answer the question "What kind of fertilizer is best for plant growth?". There are very many types of fertilizer, as well as plants in the world: a single experiment will not be able to draw universal conclusions. A much better question for devising an experiment might be "What nitrogen concentration in the fertilizer produces the largest crop of corn?"
- Modern scientific knowledge is very, very vast. If you intend to do some serious scientific research, do some research before you start planning your experiment. Have past experiments already answered the question you intend to study your experiment? If so, is there a way to adjust the game so that it tries to explore questions left unsolved by existing research?
Step 2. Isolate your variables
A good scientific experiment studies specific and measurable parameters, called "variables". In general terms, a scientist conducts an experiment within a certain range of values for the variable under consideration. A key concern when conducting an experiment is to change "only" the specific variables you want to test (and no other variables).
Following our example of the fertilizer experiment, the scientist has to grow several cobs on the ground, with the help of fertilizers of different nitrogen concentrations. He must supply the exact same amount of fertilizer to each ear. He must therefore ensure that the chemical composition of the fertilizers differs only in the concentration of nitrogen - for example, he will not use a fertilizer with a higher concentration of magnesium for one of the cobs. Furthermore, in each replica of his experiment, he will grow the same quantity and quality of cobs, in the same type of soil
Step 3. Formulate a hypothesis
A hypothesis is basically a prediction of the outcome of the experiment. It shouldn't be a blind bet: valid assumptions are based on the research you've conducted regarding the topic of your experiment. Formulate your hypotheses based on the results of similar experiments, conducted by experts in your field, or, if you are addressing an issue that has not yet been thoroughly studied, start by combining all the literary research and all the recorded observations that can you find. Remember that despite your best research work, your assumptions may turn out to be wrong - in this case, you will have broadened your knowledge anyway, as you will have proven that your assumptions were incorrect.
Typically, a hypothesis is expressed by means of a declarative and quantitative sentence. A hypothesis may also consider how the experimental parameters will be measured. A good guess for our fertilizer example would be: "Cobs treated with one pound of nitrogen per acre will develop more mass yield than equivalent cobs treated with different nitrogen concentrations."
Step 4. Schedule data collection
First decide "when" you will collect the data, and "what type" of data you will collect. Measure this data at a predetermined time or, in other cases, at regular time intervals. In our fertilizer experiment, for example, we will measure the weight of our cobs (in kilograms) after a predetermined growing period. We will compare this weight with the nitrogen contained in the fertilizer with which we have treated the different cobs. For other experiments (such as those that measure changes in a given variable over time), it will be necessary to collect data at regular intervals.
- Creating a data table before the experiment is a great idea - you can simply enter the values into the table as you record them.
- Learn the difference between your dependent and independent variables. The independent variable is the one you change, while the dependent variable is the one that changes as the independent variable changes. In our example, the "amount of nitrogen" is the "independent" variable, while the "mass (in kg)" is the "dependent" variable. A simple data table should contain columns for both variables, as they will change over time.
Step 5. Conduct your experiment methodically
Testing variables often requires conducting the experiment several times for different values of the variables. In our fertilizer example, we will grow several identical cobs and treat them with fertilizers containing varying amounts of nitrogen. Generally, it is best to collect as broad a spectrum of data as possible. Collect as much data as you can.
- Good experimental design includes what is referred to as "control". One of the replicas of your experiment should not include the variable you are testing. In the fertilizer example, we will add a fertilizer treated cob that does not contain nitrogen. This will be our control: it will be the basis from which we will measure the growth of the other cobs.
- Observe all safety measures associated with the use of harmful materials during your experiments.
Step 6. Collect your data
If possible, collect all the data directly into your tables - it will save you the headache of re-entering and consolidating the data later. Learn how to recognize outliers in your data.
It's always a good idea to visually represent your data if possible. Plot data peaks on a graph, and express trends with a suitable line or curves. This will help yourself (and everyone who looks at the chart) to visualize the trends in the data. For most basic experiments, the independent variable is plotted on the horizontal X axis, while the dependent variable is plotted on the vertical Y axis
Step 7. Analyze your data and come to a conclusion
Was your hypothesis correct? Are there any observable traces in your data? Did you stumble upon unexpected data? Do you have any other unanswered questions that could form the basis of a future experiment? Try answering these questions as you consider the results. If your data does not give you a definitive "yes" or "no", consider conducting new experimental tests, and gathering additional data.
To share your results, write a comprehensive scientific publication. Knowing how to write a scientific publication is an important skill, as the results of many new research must be written and published in a specific format
Part 2 of 2: Conducting an Example Experiment
Step 1. We select a subject and define our variables
For the purposes of this example, we will consider a simple small-scale experiment. We will test the effects of different spray fuels on the firing range of a "potato shooter".
- In this case, the type of fuel spray represents the "independent variable", while the projectile range is the "dependent variable".
- Things to consider for this experiment: Is there a way to make sure each "bullet potato" has the same weight? Is there a way to administer the same amount of spray fuel with each launch? Both factors can potentially affect the range of the weapon. We weigh each potato before the experiment, and feed each shot with the same amount of spray fuel.
Step 2. Let's formulate a hypothesis
If we want to test a hair spray, a cooking spray and a paint spray, we can say that the hair spray has an aerosol propellant with a greater amount of butane than the others. Since we know that butane is flammable, we can speculate that the hair spray will produce a greater propulsive force when triggered, launching the potato-bullet farther. We can write our hypothesis this way: "The higher concentration of butane contained in the aerosol propellant of the hair spray will produce, on average, a longer range when firing a potato-bullet weighing between 250-300 grams."
Step 3. First of all, we organize the collection of materials
In our experiment, we will test each aerosol fuel 10 times, and average the results. We will also test an aerosol fuel that does not contain butane as a control for our experiment. To prepare, we will assemble our "potato shooter", make sure it works, buy our spray cans and shape our potato bullets.
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We also create our data table in advance. We prepare five vertical columns:
- The left column will be labeled "Test #". Each space in the column will simply contain the numbers 1-10, which will indicate each shot attempt.
- The next four columns will be labeled with the names of the different sprays we will use in our experiment. The ten spaces under each column will indicate the range reached (in meters) by each shot.
- Under each of the four fuel columns, we will leave a space to indicate the average of the flow rates.
Conduct a Science Experiment Step 11 Step 4. We conduct the experiment
We will use each spray can to fire ten bullets, using the same amount of spray for each bullet. After each shot, we will use a long tape to measure the distance traveled by the bullet. At this point we record the data in the table.
Like many experiments, ours also has security measures to be taken. The combustible sprays we will be using are flammable, so we will need to make sure to close the safety of the potato shooter properly and to wear heavy gloves when we turn on the fuel. To avoid accidental injuries from bullets, we'll also need to make sure we don't interfere with the weapon's trajectory. So let's avoid being in front of (or behind) it
Conduct a Science Experiment Step 12 Step 5. Let's analyze the data
Let's say we found that, on average, the hair spray fired the potatoes farther, but the cooking spray was more consistent. We can visually represent this data. A good way to represent the average flow rates of each spray is through the use of a column chart, while a scatter chart is a good way to represent the variation of each flow.
Conduct a Science Experiment Step 13 Step 6. We draw conclusions
Let's reflect on the results of our experiment. Based on the data, we can confidently say that our hypothesis was correct. We can also say that we have discovered something that we had not hypothesized, and that is that the cooking spray produced the most consistent results. We can report any problems or errors encountered (for example the paint from the drawing spray may have accumulated inside the potato shooter, jamming it several times). Finally, we can recommend directions for future research: for example, greater distances could be covered by using larger quantities of fuel.
We can even share our results with the world using the tool of scientific publication; given the subject of our experiment, it might be more appropriate to present this information in the form of a triple scientific exhibition
Advice
- Have fun and experiment safely.
- Science is about asking big questions. Don't be afraid to choose an area you haven't explored yet.
Warnings
- Wear eye protection
- If something gets in your eyes, rinse them under running water for at least 5 minutes.
- Do not consume food or drinks near the work station.
- Wear rubber gloves while handling chemicals.
- Pull your hair back.
- Wash your hands before and after an experiment.
- When using sharp knives, dangerous chemicals, or open flames, make sure you are under adult supervision.
