Arceus74 said:Suppose the value of P=0.03.
Suppose we assume los is 5%.
Then we will accept null hypothesis.
So based on what factors do we assume los and what los do industries follow?
The level of significance (LOS) is a measure of the probability of making a Type I error, which is rejecting the null hypothesis when it is actually true. It is typically set at 0.05 or 5% in scientific research, meaning that there is a 5% chance of incorrectly rejecting the null hypothesis. It helps researchers determine the reliability and validity of their findings.
The level of significance is typically determined prior to conducting the study and is based on the research question, the amount of risk the researcher is willing to take, and the nature of the data being analyzed. It can also be adjusted based on the specific goals and requirements of the study.
The level of significance and p-value are closely related. The p-value is the probability of obtaining the observed results or more extreme results if the null hypothesis is true. If the p-value is less than or equal to the level of significance, then the results are considered statistically significant and the null hypothesis is rejected.
It is generally not recommended to change the level of significance after the study has been conducted. This can lead to biased results and false conclusions. However, it may be appropriate to adjust the level of significance in certain situations, such as when conducting multiple tests or when the results have important practical implications.
The level of significance can affect the sample size in a study. A lower level of significance (e.g. 0.01) requires a larger sample size to achieve the same power as a higher level of significance (e.g. 0.05). This is because a lower level of significance requires stronger evidence to reject the null hypothesis, and thus a larger sample size is needed to detect smaller effects.