A statistical norm refers to the average or most frequent behavior observed within a population. Unlike social norms, which dictate what 'ought' to be done, a statistical norm is purely descriptive, representing what actually exists or occurs in reality. It is a quantitative measure of central tendency based on empirical data rather than a prescriptive rule of conduct or moral expectation.

Secondary data analysis involves the use of existing datasets, such as census records, government statistics, or previous research findings, to answer new sociological questions. This method is highly efficient as it saves time and resources compared to conducting original primary research, while allowing for large-scale longitudinal or comparative studies.

Measures of central tendency are statistical indices that represent the center or typical value of a dataset. The mean is the arithmetic average, the median is the middle value in an ordered list, and the mode is the most frequently occurring value. Together, these metrics provide a summary of the distribution's central point, which is essential for quantitative sociological research.

A hypothesis is a tentative, testable statement or prediction about the relationship between two or more variables. It is derived from theory and serves as the basis for empirical research, allowing sociologists to verify or refute theoretical claims through systematic observation and data analysis.

A hypothesis is a testable statement about the relationship between two or more concepts. To test these concepts empirically, sociologists convert them into variables—measurable attributes that can vary across cases. This process of operationalization allows researchers to collect data and perform statistical analysis to verify or refute their initial hypothesis.

In research methodology, a variable is any characteristic, number, or quantity that can be measured or counted. Variables can change over time or across different observations. They are essential for empirical research because they allow sociologists to test hypotheses, identify correlations, and determine causal relationships between different social phenomena by observing how changes in one variable affect another.

Quantitative sociology relies on systematic empirical investigation using statistical, mathematical, or computational techniques. This approach encompasses various methods, including the administration of surveys, rigorous data analysis, and the interpretation of numerical data to identify patterns, correlations, and trends within social populations.

Control variables are used in research to isolate the relationship between an independent variable and a dependent variable. By holding other potential influencing factors constant, researchers can determine if the observed relationship is genuine or spurious.

Quantitative sociology relies heavily on statistical methods to analyze numerical data collected from surveys, experiments, or existing datasets. These methods allow researchers to identify patterns, correlations, and trends across large populations, providing a mathematical basis for sociological generalizations and testing theories.

The term 'dark figure' refers to the significant volume of criminal activity that remains hidden from official records. In the context of domestic violence, many incidents are never reported to authorities due to fear, social stigma, or psychological trauma, making it difficult for researchers to capture the true statistical extent of the problem.