C2 has an extensive data collection group dedicated to executing a variety of quantitative research study initiatives.
Quantitive research empirically investigates conclusions resulting from the numerical, mathematical or statistical examination of all kinds of data sets ranging from psychological and sociological to economical and market-driven. Objectives of quantitative research include the following:
The primary difference between quantitative and qualitative research concerns objectivity vs subjectivity, or the emergence of data from specialized qualitative/quantitative research design.
Examples of qualitative research designs involve evaluation, correlation, survey, descriptive and experimental research. All of these designs demand the inclusion of perimeters defining sample size, variables, data collection, data analysis.
Quantifying accumulation of data is accomplished through a wide variety of techniques allows the researcher to numerically assess differences between two or more subject groups exhibiting definitive variables. For example, a researcher may want to quantify the rate at which people in their 20s lose weight in contrast to people in their 50s. Multiple regressions for variables such as beginning weight, lifestyle, pre-existing medical conditions and genetics is necessary for delivering objective results exemplifying the advantages of quantitative research.
By incorporating inferential statistical analysis in quantitative research, errors can be eliminated that contribute to false hypotheses and information that could be potentially disadvantageous to companies seeking to increase their marketing and sales standards. Concepts that should be included in professional quantitative research designs include one or more of the following:
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