Quantitative Methods

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Quantitative Methods

Quantitative research is the way to explaining phenomena by a systemic empirical investigation of observable phenomena via collecting numerical data that are analyzed using mathematical, statistical or computational techniques based methods.

Quantitative research involves the collection and analysis of data that is quantifiable.
Quantifiable means here the data must be able to be counted or mathematically calculated.

In a quantitative research, the question of measurement is central because it provides the connection between empirical observation and the conceptual dimension of the research.

Quantitative data is any data that is in numerical form such as statistics, percentages, etc. collected through polls, questionnaires, and surveys, or by manipulating pre-existing statistical data using computational techniques.

The collected data from individuals are known as variables.
Variables are any characteristic of the unit we are interested in and want to collect (e.g. size of a company, turnover, age of an employee, etc.). The label ‘variable’ refers to the fact that these data will differ between units.

In a quantitative research, subjects are usually measured once or more (before and after treatment, etc.).

Three main type of quantitative researches exist:
1. Descriptive (what is the current situation?),
2. Experimental (What is the cause?)
3. Ex post facto/causal comparative (what was the possible cause?).

The aim of a quantitative research is generally to determine the relationship between one thing, the independent variable, and another, independent variable, within a population.

Quantitative research provides a means for researchers to be able to generate statistics with the data that is collected through a sample of the empirical word.

The purpose of a quantitative research is get information that can be inferred (or generalized) from this sample to large populations of units (generalizability).

In term of methods, “quantitative methods”, is a broad umbrella term for a large number of topics, methods and approaches including classical statistical tests (t-test, ANOVA, etc.), regression, structural equation modeling, hierarchical Linear Modeling (multi-level analysis), etc.

Quantitative software (SAS, Stata, SPSS, R, etc.) are usually used to perform statistical tests and analysis.

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