Forming a hypothesis is a crucial aspect of any scientific research. Hypotheses are testable statements that describe the correlation between two or more variables. On the other hand, a variable is a rational collection of observable and measurable characteristics, which can vary from one individual to the other in a population. This article evaluates the progression of having a vague sense of statements such as; "When it gets hot outside, the level of crime increases," and what the terms in the statement mean to measure it in a scientific study specifically. In the scientific study, there are two important properties of variables which include mutually exclusive and exhaustive variables.
According to Dietrich (2017), an exhaustive variable has a thorough list of characteristics that constitute the entire variables. In the statement, "When it gets hot outside, the level of crime increases," to measure the levels of crime increase; all the variables that make the rate of crime should be highlighted. The variables that determine the levels of crime increase would include; the age of the population, poverty levels, social levels of morality, availability of jobs, as well as police policy. In the statement under question, "when it gets cold outside," is not a variable of the levels of crime increase in a population. Additionally, the listing of the comprehensive variables offers a complete account of the levels of crime increase categories. On the other hand, a mutually exclusive variable score can only be in one response category (Gillespie et al ., 2015). In the example statement, the response would not be mutually exclusive because they do not coincide, and the occurrence of "the level of crime increases" supersedes "when it gets hot outside."
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The testing of two or more variables requires the definition of the variables as either dependent or independent, which determines the directional relationships between the variables. Additionally, an accurate and consistent measurement for the concept under question helps in the determination of the relationship between given relationships.
References
Dietrich, C. F. (2017). Uncertainty, calibration, and probability: the statistics of scientific and industrial measurement . Routledge.
Gillespie, B. J., Fredrick, D., Harari, L., and Grov, C. (2015). Homophily, close friendship, and life satisfaction among gay, lesbian, heterosexual, and bisexual men and women. PLoS One , 10(6), e0128900.
