In statistical hypothesis testing, the alternative hypothesis is a position that states something is happening, a new theory is preferred instead of an old one (null hypothesis). It is usually consistent with the research hypothesis because it is constructed from literature review, previous studies, etc. However, the research hypothesis is sometimes consistent with the null hypothesis.
In order to understand what an alternative hypothesis is, you first need to understand what the null hypothesis means. The word hypothesis means a working statement. In statistics, we’re interested in proving whether a working statement (the null hypothesis) is true or false. Usually, these working statements are things that are expected to be true. So, the Alternative Hypothesis would be the contrary or opposite of the null.
In statistics, alternative hypothesis is often denoted as Ha or H1. Hypotheses are formulated to compare in a statistical hypothesis test.
An example is where water quality in a stream has been observed over many years, and a test is made of the null hypothesis that “there is no change in quality between the first and second halves of the data”, against the alternative hypothesis that “the quality is poorer in the second half of the record”.
Wikipedia. Alternative Hypothesis. https://en.wikipedia.org/wiki/Alternative_hypothesis