Null/alternative hypothesis: The best thing to do is look at lots of examples and see how these hypotheses are defined. There are numerous examples given throughout. In inferential statistics, the term null hypothesis usually refers to a general statement or default position that there is no relationship between two measured. The given hypothesis is tested with the help of the sample data. A simple random sample has the full freedom of giving any value to its statistic. This is a good follow-up to the post—thanks Nick. It goes a little further in the discussion, more than semantics, by including the topic of practical. Name: Eston • Tuesday, September 16, 2014. Thanks for the comment, Ian. I believe I did explain what the null hypothesis is; however, you seem to be asking why it's. what does it mean to reject the null, by Professor Laura Swart. Why do we reject the null hypothesis when we have 99.7% of area under the curve supporting null hypothesis? • Hypothesis Tests. Statisticians follow a formal process to determine whether to reject a null hypothesis, based on sample data. I would suggest that it is much better to say that we fail to reject the null hypothesis , as there are at least two reasons we might not achieve a significant. The null hypothesis is a hypothesis which the researcher tries to disprove, reject or nullify.