Role of Statistics in Quantitive Analysis

Quantitative analysis is a type of analysis that uses statistics to evaluate numerical data.

Definition

Quantitative analysis is a term that refers to a method of analysis that posits a statement, or hypothesis, and then attempts to disprove that statement by examining the data. Statistics is a tool used to analyze the data.

Statistical significance

Perhaps one of major benefits of quantitative research is that it provides a technique for determining whether results are statistically significant, meaning the likelihood that the results of the study would be same if the research were repeated.

Practical significance

Quantitative analysis also has practical significance. Quantitative measures typically look at "size," be it the incidence of occurrence in a population or the magnitude of that occurrence.

Clinical significance

Quantitative research, in its use of statistics, can have clinical significance. Clinical significance refers to whether a change makes an actual difference. A good example of this is in medical studies when some participants are given the actual medicine, with balance receiving the placebo.

Qualitative Analysis

Combining qualitative and quantitative statistical analysis produces several benefits. These benefits include triangulation (a check-and-balance of sorts), complementary results (an enhancement of findings), and development (using the finding from one type of analysis to form the basis of a finding in the other type).

References

• Videolectures.net: Anthony J. Onwuegbuzie and Nancy L. Leech, "Enhancing the Interpretation of 'Significant' Findings"; The Qualitative Report Volume 9 Number 4 December 2004 770-792, p. 770, 772, 773