When are hypotheses supported in science?
University Didactics & Teaching Development
4. Discussion: Interpret the test results
Experimental science is about testing hypotheses. Therefore, the sentence on the subject (whether or not your results support the hypothesis) is very important for your record. It doesn't mean you have failed if your data doesn't confirm the hypothesis. This case can even be more interesting: You could find a new perspective on how to evaluate and interpret the data. Failure to support a hypothesis is very common in the natural sciences and often marks the starting point for new experiments.
- Go back to your hypothesis in the introduction. Then take another look at your results and data. Assess whether your hypothesis is confirmed or not. At this point, as a scientist, you need to be as unbiased as possible.
- Write a statement about your thoughts. There are three options:
- the data support the hypothesis,
- the data do not support the hypothesis or
- in general, the data support the hypothesis, but there are certain exceptions (explain them).
Example: "The hypothesis that the viscosity of solution X increases with the addition of solutions Y and Z was supported by the test result."
It is important to back up your statement about the hypothesis with laboratory data.
- Go back to your results and identify the exact dates that led to your decision on the hypothesis.
- Write a paragraph (or two, if necessary) in which you present the relevant data and explain how they relate to the hypothesis.
- Refer to data from figures or tables directly in the text: Table 1, Figure 1 etc.
In the second step, you highlighted data that helped you make a decision about the hypothesis. Now you are using your understanding of the scientific concept to explain your decision. No matter how the test results relate to the hypothesis, you have to find a logical and scientific basis for it.
- Return to the scientific justification of your hypothesis at the end of the introduction. Use this reasoning and your understanding of the scientific concept behind the experiment as the starting point of your explanation. Your explanation will likely correspond to one of four scenarios, choose the one that best fits your protocol:
- If the results fully support the hypothesis, and if the reasoning in the introduction is correct, then take your arguments further and show how the science behind the experiment explains the results.
- If the results fully support the hypothesis but the reasoning in the introduction was not entirely correct, explain why the initial reasoning was wrong and provide better evidence.
- If the results generally support the hypothesis, but with some restrictions, describe them (if you haven't already done so) and use your argumentation as a basis for discussing the restrictions.
- If the results do not support the hypothesis, explain why not. Take into account (1) problems with your understanding of the scientific concept behind the experiment, (2) problems with your reasoning and / or (3) problems with the conduct of the experiment itself (if there were problems with the reliability of the laboratory data or if changes were made in the implementation discuss them in detail and show exactly how the implementation could have influenced the results and how these uncertainties could be circumvented).
After you have dealt with the critical point, the hypothesis, the rest of the discussion can deal with other things. You can address these in individual paragraphs.
- Return to the notes you made while experimenting. Search for possible sources of error when preparing the experiment, when calibrating the measuring instruments and during the measurement as well as with the materials used.
- In scientific articles, scientists compare their results with those of other experiments. You can do something similar if you compare your results with those of other students. Comment on any similarities and differences you find and suggest possible explanations for the differences. Ask your assistant beforehand whether this is allowed.
- Professors who write experimental scripts are usually interested in how the experiments can be improved. You can demonstrate your ability to be productive in criticizing the attempt by making suggestions for improvement.
For advanced internships:
- It might be useful to sort the different measurement uncertainties. The sources of these uncertainties can be random (those that cannot be predicted) or systematic (those that are personal, methodological, or device-related uncertainties).
- Who is the weirdest Marvel character
- Contains D K Goel NCERT solutions
- Who is eligible to appear in USMLE
- Why should I stay sober
- What are the reasons for using Snapchat
- How HR experts solve their problems
- Why are swords considered powerful?
- What is social security in the UK
- Why is diversity an attraction in Nepal
- Is religion an obstacle to women's rights?
- How is ragging done in NIT Jamshedpur
- Is co-education better than girls' honor
- Was sacked Mourinho at Real Madrid
- What are the most common flying insects
- Why does the mind develop habits
- British companies submit quarterly reports
- Are animals aware of global warming?
- Do you have BitLife
- How good is Yamaha MT15
- Why did Iceland want independence from Denmark?
- Electricity goes through the laser light
- How does a man divide his thoughts
- What are creative problem solvers
- What are the advantages of digital marketing
- Are actively managed funds better than ETFs
- What happens when you breathe dust
- Have asteroid temperature
- What is 2 2 68
- What are up-tempo dance music
- Why are male corpses used for preparations?
- How do you develop trust in people
- Have employees free speech
- What are the most overlooked strengths of the INFPs