TYPES OF QUANTITATIVE RESEARCH
C2 has an extensive data collection group dedicated to executing a variety of quantitative research study initiatives.
What is Quantitative Research?
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:
- Develop useful mathematical and statistical theories/models that lead to cogent hypotheses.
- Address objectives relevant to a company’s goals in regards to critiquing data collection processes that may or may benefit the company’s viability.
- Reduce the risk of subjective errors that may occur in disorganized qualitative research processes
- Recover and avoid loss of time and overhead costs by obtaining precise information based on empirical models of investigation regarding a specific population of interest
- Statistically examine cause and effect correlations/relationships
- Quantitative Research vs Qualitative Research
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.
Quantitative Research Methods
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.
Basic Concepts of Inferential Statistics Used in 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:
- Probability level and significance testing
- Type I and Type II error indications
- Development of one and two-tailed tests
- T-tests for independent and non-independent samplings
- Implementation of ANOVA and posttests such as analysis of covariance
Quantitative survey techniques include:
- Telephone surveys
- In-store/on-site intercepts
- Mall surveys
- Online surveys
Quantitative study techniques include:
- Attitude, awareness and usage (AAU tracking)
- Cluster analysis
- Conjoint analysis
- Cross tabs
- Multi-dimensional scaling
- Multiple regression
- Perceptual mapping segmentation