I would like to talk about point 6, which mentions that a P-value of >0.05 does not necessarily means that no effects are observed. I think this is a very common point or error that a lot of people profoundly believes. Many people treat the p-value as a magical threshold to the point that they think anything below it is a YES and anything above it must be a NO. It is important to note that there are many potential factors contributing to the p-value, so something above the threshold does not mean that the null hypothesis must be true. It just means that we cannot rule out the possibility of chance. There could still be an effect demonstrated in the data. It’s just that the probability that this may happen by chance is a bit too high for us to definitely conclude that an effect must have caused this.
Also, the p-value is set differently in different research objectives and different disciplines. For example, in astronomy, most research set the p-value threshold to 0.001 or 0.0001. In the astronomical scales of the universe, a lot of things could happen by chance. Therefore, the threshold for rejecting the null hypothesis is set very stringently to ensure that there is enough confidence to conclude an effect is more likely to cause the observation than it happening by chance.