Quantitative Research


Quantitative research is about collecting and analyzing data to explain phenomena. It gives a measure of how many people think, feel or behave in certain way. Quantitative research is based more directly on its original plans and its results are more readily analyzed and interpreted. Information from a sample is used to make generalizations or predictions about a population.

Quantitative research designs are either descriptive or experimental. Descriptive designs are where you measure an association between two variables (independent and dependent variables). Sample sizes are typically large. It often provides a macro view. For e.g. You might survey thousands of local students. Subjects are usually only measured once. In an experimental design, subjects are usually measured both before and after a treatment and you are looking for causality. Sample sizes tend to be small. For e.g. You might be analyzing a treatment for a small number of cancer patients. It is well suited for the testing of theories, hypothesis and cause and effects relationship.

It is normally based on the reported behaviors of a much larger and representative sample. Typical methods for data collection are surveys or questionnaires with closed-ended questions, using data from another source (for example, a government database) or an experiment with a control group and an experimental group.

Surveys are easy in theory but can be difficult to put into practice, mainly because of a typically low response rate. A questionnaire is given to each member of the sample and used to infer characteristics of the whole population. Surveys usually involve a representative sample of the population, using a technique like random sampling.

For Quantitative analysis, you might choose to report your results using confidence intervals and test statistics from t tests or f tests with significance levels (alpha levels) and p values. This also include descriptive statistics like mean, median and standard deviation and inferential statistics like ANOVA or multiple regression correlations.

Services Includes: Telephonic Survey (CATI), Online Survey, Products test, Gang Surveys, Shopper Research, Mystery Shopping, Shelf Test, In-Home User Test, Concept Test, Promotion Test, Pricing Test, Sniff Test, Employee or Customer Satisfaction Survey, Pre Post Launch Survey, Usage and Attitude Survey, Intercept studies (in malls, in airports etc.), Exit Surveys, Central Location Test (CAPI, PAPI, CAWI), Car Clinic