 | Look up quantitative in Wiktionary, the free dictionary. |
Quantitative may refer to:
QA or qa may refer to:
Computational archaeology describes computer-based analytical methods for the study of long-term human behaviour and behavioural evolution. As with other sub-disciplines that have prefixed 'computational' to their name, the term is reserved for methods that could not realistically be performed without the aid of a computer.
Qualitative research relies on data obtained by the researcher from first-hand observation, interviews, questionnaires, focus groups, participant-observation, recordings made in natural settings, documents, and artifacts. The data are generally nonnumerical. Qualitative methods include ethnography, grounded theory, discourse analysis, and interpretative phenomenological analysis. Qualitative research methods have been used in sociology, anthropology, political science, psychology, social work, and educational research. Qualitative researchers study individuals' understanding of their social reality.
Quantitative research is a research strategy that focuses on quantifying the collection and analysis of data. It is formed from a deductive approach where emphasis is placed on the testing of theory, shaped by empiricist and positivist philosophies.
Content analysis is the study of documents and communication artifacts, which might be texts of various formats, pictures, audio or video. Social scientists use content analysis to examine patterns in communication in a replicable and systematic manner. One of the key advantages of using content analysis to analyse social phenomena is its non-invasive nature, in contrast to simulating social experiences or collecting survey answers.
Quantitative analysis may refer to:
Cohort or cohortes may refer to:
Quants may refer to:
Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively.
Data visualization is an interdisciplinary field that deals with the graphic representation of data. It is a particularly efficient way of communicating when the data is numerous as for example a Time Series. From an academic point of view, this representation can be considered as a mapping between the original data and graphic elements. The mapping determines how the attributes of these elements vary according to the data. In this light, a bar chart is a mapping of the length of a bar to a magnitude of a variable. Since the graphic design of the mapping can adversely affect the readability of a chart, mapping is a core competency of Data visualization. Data visualization has its roots in the field of Statistics and is therefore generally considered a branch of Descriptive Statistics. However, because both design skills and statistical and computing skills are required to visualize effectively, it is argued by some authors that it is both an Art and a Science.
Technical may refer to:
Biomechanical may refer to:
QRT may refer to:
IQC may refer to:
Titration is a common laboratory method of quantitative chemical analysis that is used to determine the unknown concentration of a known reactant.
Interpolation is a method of constructing new data points within the range of a discrete set of known data points in the mathematical field of numerical analysis.
Analysis is the process of observing and breaking down a complex topic or substance into smaller parts to gain a better understanding of it.
Qualitative descriptions or distinctions are based on some quality or characteristic rather than on some quantity or measured value.
Systems Analysis and Design, an interdisciplinary part of science, may refer to:
Analytica may refer to: