Hypothesis Examples: Different Types in Science and Research

Simply put, a hypothesis is an idea that can be tested based on the evidence available. A concept or statement must be tested to be proven credible. This serves as a starting point for further investigation to prove the hypothesis by applying the scientific method. However, there are multiple variables that can affect the results, and therefore the idea must be tested multiple times.

Before diving into hypothesis examples, take a moment to understand independent and dependent variables.

• an independent variable stands on its own and is not changed by other variables

• the dependent variable depends on other factors

The independent variable can cause a change in the dependent variable, but the dependent variable cannot cause a change in the independent variable. For example:

How does the amount of makeup one applies affect how clear their skin is?

Here, the independent variable is the makeup, and the dependent variable is the skin. The variables are important because they help determine the cause and effect. In this example, the hypothesis could be:

The amount of makeup one wears correlates to how clear their skin is.

Therefore, this hypothesis must be tested before it can be proven correct.

The most common forms of hypotheses are:

• Simple Hypothesis

• Complex Hypothesis

• Null Hypothesis

• Alternative Hypothesis

• Logical Hypothesis

• Empirical Hypothesis

• Statistical Hypothesis

See how these types of hypotheses are created through examples.

A simple hypothesis predicts the relationship between two variables: the independent variable and the dependent variable. This relationship is demonstrated through these examples.

• Drinking sugary drinks daily leads to being overweight.

• Smoking cigarettes daily leads to lung cancer.

• Getting at least 8 hours of sleep can make people more alert.

A complex hypothesis describes a relationship between variables. However, it’s a relationship between two or more independent variables and two or more dependent variables. You can follow these examples to get a better understanding of a complex hypothesis.

• Adults who 1) drink sugary beverages on a daily basis and 2) have a family history of health issues are more likely to 1) become overweight and 2) develop diabetes or other health issues.

• Individuals that 1) smoke cigarettes and 2) live in large cities are more likely than others to have 1) respiratory problems and 2) an increased risk of cancer.

• Individuals who 1) get an average of eight or more hours of sleep and 2) have a balanced diet and schedule are more likely to 1) be alert during the day and 2) have more energy.

A null hypothesis, denoted by H₀, proposes that two factors or groups are unrelated and that there is no difference between certain characteristics of a population or process. You must test the likelihood of the null hypothesis, in tandem with an alternative hypothesis, in order to disprove or discredit it. Some examples of a null hypothesis include:

• There is no significant change in a person’s health during the times when they drink green tea only or root beer only.

• There is no significant change in an individual’s work habits whether they get eight hours or nine hours of sleep.

• There is no significant change in the growth of a plant if one uses distilled water only or vitamin-rich water only to water it.

An alternative hypothesis, denoted by H₁ or H_A , is a claim that is contradictory to the null hypothesis. Researchers will pair the alternative hypothesis with the null hypothesis in order to prove that there is no relation. If the null hypothesis is disproven, then the alternative hypothesis will be accepted. If the null hypothesis is not rejected, then the alternative hypothesis will not be accepted. Some examples of alternative hypotheses are:

• A person’s health improves during the times when they drink green tea only, as opposed to root beer only.

• Work habits improve during the times when one gets 8 hours of sleep only, as opposed to 9 hours of sleep only.

• The growth of the plant improved during the times when it received vitamin-rich water only, as opposed to distilled water only.

A logical hypothesis is a proposed explanation using limited evidence. Generally, you want to turn a logical hypothesis into an empirical hypothesis, putting your theories or postulations to the test. In reference to these examples, there is currently no evidence to support these hypotheses. However, you can form a hypothesis based on the data available to draw a logical conclusion.

• Cacti experience more successful growth rates than tulips on Mars.

• Beings from Mars would not be able to breathe the air in Earth's atmosphere.

• Creatures found at the bottom of the ocean use anaerobic respiration rather than aerobic respiration.

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. Rather, it is going through 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.

• Women taking vitamin E grow hair faster than those taking vitamin K.

• Thirsty rats find their way through a maze quicker if there is water at the end of the maze.

In these examples, trial and error is leading to a series of findings. The results of these experiments can all be observed and proven over time.

A statistical hypothesis is an examination of a portion of a population or statistical model. In this type of analysis, you use statistical information from an area. For example, if you wanted to conduct a study on the life expectancy of people from Savannah, 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 Savannah's population.

• 50% of Savannah's population lives beyond the age of 70.

• 80% of the U.S. population gets a divorce because of irreconcilable differences.

• 45% of the poor in the U.S. are illiterate.

For a hypothesis to be sound, hold tight to these tips.

Define the independent and dependent variables very specifically, and don't take on more than you can handle. Keep yourself laser-focused on one specific cause-and-effect theory.

Keep your language clean and simple. State your hypothesis as concisely and to the point as possible. A hypothesis is usually written in a form where it proposes that, if something is done, then something else will occur. Usually, you’ll want to form your hypothesis as a statement, not a question. For example:

If I raise the temperature of a cup of water, then the amount of sugar that can be dissolved in it will be increased.

Any hypothesis will need proof. Your audience will have to see evidence and reason to believe your statement. For example, I may want to drink root beer all day, not green tea. If you're going to make me change my ways, I need some sound reasoning and experimental proof — perhaps case studies of others who lost weight, cleared up their skin and had a marked improvement in their immunity by drinking green tea.

Hypotheses and research are the backbone of science. A hypothesis that is well-stated, founded in truth, and that can withstand extensive and repeated research and experimentation can lead to new discoveries and breakthroughs.