Measurements demand the use of operational definitions of relevant quantities (operationalization). That is, a scientific quantity is described or defined by how it is measured, as opposed to some more vague, inexact or idealized definition. The operational definition of a thing often relies on comparisons with standards: the operational definition of mass ultimately relies on the use of an artifact, such as a certain kilogram of platinum kept in a laboratory in France.

The scientific definition of a term sometimes differs substantially from its natural language usage. For example, sex and gender are often used interchangeably in common discourse, but have distinct meanings in sociology. Scientific quantities are often characterized by their units of measure which can later be described in terms of conventional physical units when communicating the work.

Measurements in scientific work are also usually accompanied by estimates of their uncertainty. The uncertainty is often estimated by making repeated measurements of the desired quantity. Uncertainties may also be calculated by consideration of the uncertainties of the individual underlying quantities that are used. Counts of things, such as the number of people in a nation at a particular time, may also have an uncertainty due to limitations of the method used. Counts may only represent a sample of desired quantities, with an uncertainty that depends upon the sampling method used and the number of samples taken.

(b) Hypothesis Development

A hypothesis includes a suggested explanation of the subject. It will generally provide a causal explanation or propose some correlation between two variables. If the hypothesis is a causal explanation, it will involve at least one dependent variable and one independent variable.

Variables are measurable phenomena whose values can change (e.g., class status can range from lower- to upper-class). A dependent variable is a variable whose values are presumed to change as a result of the independent variable. In other words, the value of a dependent variable depends on the value of the independent variable. Of course, this assumes that there is an actual relationship between the two variables. If there is no relationship, then the value of the dependent variable does not depend on the value of the independent variable. An independent variable is a variable whose value is manipulated by the experimenter (or, in the case of nonexperimental analysis, changes in the society and is measured). Perhaps an example will help clarify. In a study of the influence of gender on promotion, the independent variable would be gender/sex. Promotion would be the dependent variable. Change in promotion is hypothesized to be dependent on gender.

Scientists use whatever they can in accordance with their own creativity, ideas from other fields, induction, systematic guessing, etc. to imagine possible explanations for a phenomenon under study. There are no definitive guidelines for the production of new hypotheses. The history of science is filled with stories of scientists claiming a flash of inspiration, or a hunch, which then motivated them to look for evidence to support or refute their idea.