A simple hypothesis is a prediction of the relationship between two variables: the independent variable and the dependent variable.
Drinking sugary drinks daily leads to obesity.
A complex hypothesis examines the relationship between two or more independent variables and two or more dependent variables.
Overweight adults who 1) value longevity and 2) seek happiness are more likely than other adults to 1) lose their excess weight and 2) feel a more regular sense of joy.
A null hypothesis (H0) exists when a researcher believes there is no relationship between the two variables, or there is a lack of information to state a scientific hypothesis. This is something to attempt to disprove or discredit.
There is no significant change in my health during the times when I drink green tea only or root beer only.
This is where the alternative hypothesis (H1) enters the scene. In an attempt to disprove a null hypothesis, researchers will seek to discover an alternative hypothesis.
My health improves during the times when I drink green tea only, as opposed to root beer only.
A logical hypothesis is a proposed explanation possessing limited evidence. Generally, you want to turn a logical hypothesis into an empirical hypothesis, putting your theories or postulations to the test.
Cacti experience more successful growth rates than tulips on Mars. (Until we're able to test plant growth in Mars' ground for an extended period of time, the evidence for this claim will be limited and the hypothesis will only remain logical.)
An empirical hypothesis, or working hypothesis, comes to life when a theory is being put to the test, using observation and experiment. It's no longer just an idea or notion. It's actually going through some trial and error, and perhaps changing around those independent variables.
Roses watered with liquid Vitamin B grow faster than roses watered with liquid Vitamin E. (Here, trial and error is leading to a series of findings.)
A statistical hypothesis is an examination of a portion of a population.
If you wanted to conduct a study on the life expectancy of Savannians, you would want to examine every single resident of Savannah. This is not practical. Therefore, you would conduct your research using a statistical hypothesis, or a sample of the Savannian population.