kvantitativt

Kvantitativt refers to a research approach or data type that emphasizes measurement of quantities and the use of numerical data and statistical analysis. In Swedish scholarly usage, kvantitativt stands in contrast to kvalitativt, which focuses on meanings, context and non-numeric evidence. Kvantitativt aims to describe, compare and generalize phenomena through numeric information and objective procedures.

Core characteristics include predefined variables, standardized measurement tools, rigorous sampling, and an emphasis on objectivity and reproducibility. The goal is often to produce findings that can be generalized beyond the studied sample and tested through statistical methods.

Data collection methods commonly associated with kvantitativt research include surveys, structured experiments, administrative records, and secondary data sets. Data types typically involve numeric data on scales such as nominal, ordinal, interval, and ratio. While nominal and some coded ordinal data can be analyzed numerically, kvantitativt analysis is most appropriate for interval and ratio data where mathematical operations are meaningful.

Analytical techniques encompass descriptive statistics (for example, mean, median, standard deviation) and inferential statistics (such as t-tests, chi-square tests, ANOVA, regression, and correlation). Proper kvantitativt work also involves careful sampling design, power analysis, and reporting with confidence intervals and p-values to convey uncertainty.

Strengths of kvantitativt include the potential for generalizable conclusions, precision, and the ability to test hypotheses with large samples. Limitations involve possible loss of contextual nuance, challenges in capturing complex phenomena with predefined instruments, and the risk of measurement bias. Kvantitativt research is often used alone or in combination with kvalitativt methods in mixed-methods designs to balance breadth and depth.