The hypothesis and the research question represent to statisticians two alternative hypotheses. An alternative hypothesis is the prediction that there is a relationship or there is a difference that has not occurred by chance or random error. Although we differentiate between hypotheses and research questions in the creation of theoretical predictions based on previous research, there are no mathematical differences in how they are perceived. (Therefore, both of these predictions can be represented as alternative hypotheses.
The null hypothesis expresses expectations for what should occur within the population, so the null hypothesis allows researchers to determine the probability of the results we find in our samples are consistent with the overall population.
Sampling error-when researchers rely on samples, a certain amount of error occurs.
Significance testing is determining whether you can accept the null hypothesis(there is no difference between x and y) or you have to reject the null hypothesis(there is a difference between x and y).
Probability level(probability value or p value). If a study’s finding are accurate 95% of the time, then there is a 5% chance that the results obtained in a study happen because of error.