If data conflicts with a scientific theory, then the theory must change or be abandoned. Scientific discipline requires the scientist putting forward a theory to attempt to disprove it before publishing his or her findings. Once published, the proposed theory is subjected to peer review, in which other scientists, competent in the relevant discipline, attempt to disprove the hypothesis. Only after thorough checking is a proposed theory accepted by the scientific community. Even then, it is constantly subjected to stress testing and analysis, as new data come to light.
For example, Newtonian physics were eventually found to be invalid in special circumstances identified by Albert Einstein, and the relevant theories were amended accordingly.
When data confirms a theory, it provides evidence that the predictions or explanations made by the theory are consistent with real-world observations. This strengthens the validity and reliability of the theory, increasing confidence in its explanatory power. Confirmation of a theory does not necessarily mean it is absolutely true, but it suggests that the theory is a useful framework for understanding and predicting the phenomenon in question.
A scientific law is the description of a recurring event that occurs in nature. A scientific theory is an explanation of the law. The law does not change, but the theory may change when new data indicate that it needs to.
If a theory does not agree with experimental results, you can either revise the theory to account for the discrepancies or discard the theory and develop a new one that aligns with the experimental evidence.
A scientist can prove a theory by conducting experiments, collecting data, and analyzing results to see if they consistently support the predictions made by the theory. The more evidence that aligns with the theory's predictions, the stronger the support for the theory. Additionally, peer review and replication of results by other scientists help confirm the validity of a theory.
When scientists disagree about which theory is correct, they may engage in debates, present evidence to support their positions, and conduct further research to gather more data. Ultimately, the scientific community typically relies on evidence-based reasoning and peer-reviewed evaluation to determine the most well-supported theory. Over time, consensus is often reached through continued experimentation and analysis.
When data confirms a theory, it provides evidence that the predictions or explanations made by the theory are consistent with real-world observations. This strengthens the validity and reliability of the theory, increasing confidence in its explanatory power. Confirmation of a theory does not necessarily mean it is absolutely true, but it suggests that the theory is a useful framework for understanding and predicting the phenomenon in question.
No. A theory is formed when lots of data point to a probability. Further data may modify the theory.
There is currently no observational data that fundamentally conflicts with the Big Bang model. There are however some people that have trouble accepting the model: they are very much against it.
Calculated data is data attained from a theory and or formula. Raw data is data accumulated from an observation or experiment. If the calculated data from a theory is successful in predicting the raw data of an observation/experiment, then the theory is strengthened.
stalemate
it is a Theory! :)
A theory is a well-supported explanation for phenomena based on observation, experimentation, and analysis. Data refers to the facts, figures, or information collected from experiments, surveys, or observations, which are used to support or refute a theory. In summary, a theory is an overarching explanation, while data are the specific observations that inform and test that theory.
No
It ultimately depends on what your theory is. Sometimes the fact that your data doesn't support your hypothesis means that the theory from which the hypothesis was derived was altogether wrong and is therefore discarded. Other times it might just mean a simple modification of the original theory, to accommodate the new-found evidence.The most important thing to remember is that your data will not always support your hypothesis, and in the event that such happens, you end learning a whole lot more.A.B.C.D.its A
A theory.
There is only one way not to collect data. The only way that is not a good way to collect data is theory development.
Theory-driven research is guided by existing theories and hypotheses, while data-driven research relies on analyzing data to generate insights and patterns without predefined theories. In theory-driven research, the focus is on testing and confirming existing theories, whereas data-driven research focuses on exploring and discovering patterns in the data to derive new insights.