- All
- Engineering
- Statistics
Powered by AI and the LinkedIn community
1
Define your research question
Be the first to add your personal experience
2
Choose your experimental design
Be the first to add your personal experience
3
Control for sources of error
Be the first to add your personal experience
4
Replicate your experiment
Be the first to add your personal experience
5
Evaluate your results
Be the first to add your personal experience
6
Communicate your results
Be the first to add your personal experience
7
Here’s what else to consider
Be the first to add your personal experience
When you conduct an experiment, you want to be confident that your results are valid and reliable. Validity means that your experiment measures what it claims to measure, and reliability means that your experiment produces consistent and accurate results. How do you ensure the validity and reliability of your experimental results? Here are some principles of experimental design that can help you achieve these goals.
Find expert answers in this collaborative article
Experts who add quality contributions will have a chance to be featured. Learn more
Earn a Community Top Voice badge
Add to collaborative articles to get recognized for your expertise on your profile. Learn more
1 Define your research question
Before you design your experiment, you need to have a clear and specific research question that guides your hypothesis, variables, and methods. Your research question should be relevant, feasible, and testable. It should also address a gap or problem in your field of study. A well-defined research question will help you avoid confounding factors, irrelevant outcomes, and vague interpretations.
Help others by sharing more (125 characters min.)
2 Choose your experimental design
Depending on your research question, you may choose different types of experimental design, such as randomized controlled trials, factorial designs, or quasi-experiments. Each design has its own advantages and disadvantages, and you should consider factors such as sample size, randomization, control groups, and ethical issues. You should also decide how you will collect, record, and analyze your data, and what statistical tests you will use to test your hypothesis.
Help others by sharing more (125 characters min.)
3 Control for sources of error
No experiment is perfect, and there are always sources of error that can affect your validity and reliability. Some common sources of error are measurement error, sampling error, human error, and bias. You should try to minimize these sources of error by using reliable and valid instruments, selecting representative and random samples, following standardized procedures, and avoiding subjective judgments. You should also identify and report any potential confounding variables, outliers, or limitations that may affect your results.
Help others by sharing more (125 characters min.)
4 Replicate your experiment
One way to check the reliability of your results is to replicate your experiment, either by yourself or by other researchers. Replication means repeating the same experiment under the same conditions and with the same methods, to see if you get the same results. Replication can help you verify your findings, correct any errors, and increase the generalizability of your results. You should also document and share your data and methods, so that others can replicate your experiment.
Help others by sharing more (125 characters min.)
5 Evaluate your results
After you conduct your experiment, you need to evaluate your results and see if they support your hypothesis and answer your research question. You should also compare your results with previous studies and theories, and discuss the implications and applications of your findings. You should be honest and critical about your results, and acknowledge any strengths and weaknesses of your experiment. You should also suggest any future directions or improvements for your research.
Help others by sharing more (125 characters min.)
6 Communicate your results
The final step of your experiment is to communicate your results to your audience, whether it is your peers, your instructor, or the public. You should present your results in a clear, concise, and accurate way, using appropriate formats, such as tables, graphs, or figures. You should also explain the meaning and significance of your results, and how they relate to your research question and hypothesis. You should also cite your sources, follow ethical standards, and use appropriate language and tone.
Help others by sharing more (125 characters min.)
7 Here’s what else to consider
This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?
Help others by sharing more (125 characters min.)
Statistics
Statistics
+ Follow
Rate this article
We created this article with the help of AI. What do you think of it?
It’s great It’s not so great
Thanks for your feedback
Your feedback is private. Like or react to bring the conversation to your network.
Tell us more
Tell us why you didn’t like this article.
If you think something in this article goes against our Professional Community Policies, please let us know.
We appreciate you letting us know. Though we’re unable to respond directly, your feedback helps us improve this experience for everyone.
If you think this goes against our Professional Community Policies, please let us know.
More articles on Statistics
No more previous content
- You're faced with conflicting data interpretations. How do you navigate statistical trend analysis? 1 contribution
- You're analyzing time-sensitive statistical data. How do you ensure accuracy without sacrificing efficiency? 2 contributions
- You're facing tight deadlines for statistical projects. How can you negotiate for more time effectively? 1 contribution
- Here's how you can excel in your career by pursuing a graduate degree in statistics.
- You're analyzing data sets from various sources. How do you ensure accurate statistical reporting? 1 contribution
- You're aiming for a salary increase in Statistics. How can you negotiate effectively to achieve it?
- Your statistical tools are pointing in a new direction. How will you align your business plan accordingly? 6 contributions
- You're faced with a rushed quality control request. How can you ensure statistical modeling accuracy?
- Your project timeline is at risk due to data discrepancies. How will you navigate this unexpected challenge?
No more next content
Explore Other Skills
- Programming
- Web Development
- Machine Learning
- Software Development
- Computer Science
- Data Engineering
- Data Analytics
- Data Science
- Artificial Intelligence (AI)
- Cloud Computing
More relevant reading
- Laboratory Management What steps can you take to ensure your experimental design is innovative and scientifically rigorous?
- Research Management What is the best way to determine the length of an experimental research project?
- Research How can you design an experimental research study that avoids common mistakes?