My weather predictions are extremely accurate!
I am a human barometer and I can predict a storm system
arriving in my area about four days prior to the event.
About the only times I am wrong is when the weather system
misses our area by a few miles!
To compare the evidence gathered with the predictions made, first, analyze the data to identify any patterns or trends that align with your initial predictions. Assess the accuracy of the predictions by looking for discrepancies or confirmations in the evidence. Finally, draw conclusions about the validity of your predictions, considering factors that may have influenced the results, and reflect on any adjustments needed for future predictions.
Comparing the predicted results with the actual results is known as the forecast error. The purpose of experimentation and statistics is to become better at prediction to reduce the forecast error.
-- Repeat the experiment. If you have the time and money, then five or ten repetitions is an even better idea. -- Compare your results with those of other experimenters. -- Compare your results with the predictions of theory.
The purpose of an experiment is to compare the results with a hypothesis or a control group. This allows researchers to determine whether the experimental treatment or variable has a significant effect on the outcome. By analyzing differences in results, scientists can draw conclusions about causality and the validity of their initial predictions. Ultimately, this process helps advance knowledge in a particular field.
...to make predictions. Scientists will then compare their predictions to what happens in the real world. If their predictions equaled what happened in reality, the model is good. If the predictions were different, the scientists know they have to refine the model to better predict what will happen.
You compare them by their empirical results.
To calculate accuracy in a statistical model, you compare the number of correct predictions made by the model to the total number of predictions. This is typically done by dividing the number of correct predictions by the total number of predictions and multiplying by 100 to get a percentage. The higher the accuracy percentage, the better the model is at making correct predictions.
generally speaking, scientists share and compare results in metric units.
Standardization
Control
Results compare with the plan and are used for evaluation purposes. This is what will tell if there are new actions needed depending on the goals achieved.
They use predication and hypothesis to compare with the end results, like comparing past knowledge to new. Observation and experimenting is to test out the hypothesis, to discover new theories or even prove old ones right or wrong.