Each alpha level is dependent on the circumstance that surrounds a particular study. The significance level(alpha) is the probability of committing a type 1 error

Each alpha level is dependent on the circumstance that surrounds a particular study. The significance level(alpha) is the probability of committing a type 1 error. A type 1 error is committed when the researcher falsely rejects the null hypothesis. A significance level of 0.05 is the standard situation, most especially in the field science.

There are some experiments where you would most likely want to lower the type 1 error rate such as experiment that affects human health, like drug research or studies of psychological treatment. For some experiments, if the consequence of applying null hypothesis is extremely serious, for instance, if null hypothesis applies, there may be death, or serious injury, then you want to try your best to avoid the type I error. That means you must avoid the situation that null hypothesis is true but you reject it. As the significance level is the probability, you will make the type 1 error. So, for such experiments with serious results, we want to make the level smaller than standard situation. So, for such experiments, if you can’t tolerate a 5% chance of being wrong, use a lower significance level, 0.01 for example. 0.01 is common if there’s a possibility of death or serious disease or injury.

If the consequences of being wrong are especially minor such as political research or animal migration studies. you might use a higher significance level, such as 0.1, but this is rare in practice. That is, it may be common that we make the significance level much smaller than 0.05, but we rarely make the level larger than 0.05.

[promo1]