Redundancy and repetition of control factors win, or winnow out, results.
to make the experiment more reliable
performing the experiment multiple times
performing the experiment multiply times.
A reliable experiment is one that can be proven or has been worked out several times giving valid or dependable results.
So the experiment's results are more reliable
to make the experiment more reliable
performing the experiment multiple times
to make your results more reliable
To make an experiment more reliable, it is important to have a large sample size, control for confounding variables, and ensure replicability by conducting the experiment multiple times. These factors reduce the impact of chance and increase the validity of the study findings.
performing the experiment multiply times.
To make an experiment more accurate you would have to repeat the experiment 3-5 more times to make it reliable and also you would do what Liverpool college do and compare the answers with other people in the class, community or teacher.
Stirring an experiment helps to ensure that all components are evenly mixed and distributed, reducing the likelihood of inconsistent results due to unequal distribution or settling of particles. This can lead to more accurate and reliable data by maintaining consistency throughout the experiment.
A reliable experiment is one that can be proven or has been worked out several times giving valid or dependable results.
So the experiment's results are more reliable
Retesting an experiment can help verify the results and ensure they are consistent and reliable. It also allows for any errors or inconsistencies to be identified and corrected. By repeating the experiment, you can increase the validity and confidence in the findings.
How accurate data is in the sense that you've repeated an experiment a number of times. I.e., one would answer the question 'how reliable were your results?' with something like 'they were very reliable as the experiment was repeated 67 times'.
Yes, an experiment can be reliable but not valid. Reliability refers to the consistency of the results when the experiment is repeated under the same conditions, while validity assesses whether the experiment measures what it is intended to measure. For instance, a poorly designed experiment may produce consistent results (reliable) but may not accurately reflect the true relationship between the variables being studied (not valid). This highlights the importance of both concepts in research design.