Hypothesis
- A hypothesis proposes an explanation and predicts observable outcomes.
- It must be testable and used to design studies that measure relevant variables.
- Testing a hypothesis gathers evidence that can support or refute a proposed explanation.
Definition
Section titled “Definition”A hypothesis is a proposed explanation for a phenomenon or a set of observations. It is a testable statement that is used to help explain a phenomenon or to make predictions about future events. Hypotheses are essential in the scientific process because they help scientists to test their theories and to gather evidence to support or refute their ideas.
Explanation
Section titled “Explanation”A hypothesis begins from observations and proposes a relationship or explanation that can be evaluated empirically. Researchers design studies that measure the relevant variables and compare outcomes; if the observed results align with the hypothesis, the study provides evidence in its favor. Hypotheses therefore guide the collection of data and the testing of theories, enabling scientists to build or revise understanding based on evidence.
Examples
Section titled “Examples”Sugar consumption and risk of type 2 diabetes
Section titled “Sugar consumption and risk of type 2 diabetes”This hypothesis proposes a relationship between the amount of sugar a person consumes and their risk of developing type 2 diabetes. It is based on the observation that people who consume large amounts of sugar are more likely to be overweight and to have high blood sugar levels, both known risk factors for type 2 diabetes. To test the hypothesis, researchers could measure the amount of sugar participants consume and compare it to their risk of developing type 2 diabetes. If the hypothesis is correct, the study would show that people who consume more sugar are more likely to develop type 2 diabetes.
Social media use and anxiety/depression
Section titled “Social media use and anxiety/depression”This hypothesis proposes a relationship between the amount of time a person spends on social media and their levels of anxiety and depression. It is based on the observation that people who spend a lot of time on social media may be more likely to experience social isolation and to compare themselves to others, both of which can contribute to anxiety and depression. To test the hypothesis, researchers could measure the amount of time participants spend on social media and compare it to their levels of anxiety and depression. If the hypothesis is correct, the study would show that people who spend more time on social media are more likely to experience anxiety and depression.