Once your proposal has been fully approved and data has been collected after a successful permission from the Institutional Review Board (IRB), we’re ready to tackle the Quantitative Data Analysis Chapter. For quantitative data, the analysis often relies on the use of statistical software, and requires both a descriptive (or exploratory) analysis and an inferential analysis to produce statistically valid inferences. A descriptive analysis utilizes tools such as tables and plots to explore the data as well and specific research questions in more depth, prior to conducting inferential analyses, which confirm the significance as well as magnitude of the statistical association between the main variables in your research.

Along with our findings, we also need to present evidence that our research and analysis is academically valid. For qualitative studies, this entails a discussion regarding various facets of trustworthiness in data such as credibility, transferability, dependability, and confirmability. For quantitative studies, this amounts to checking that all of the assumptions of a statistical model (e.g. a regression or correlation) are satisfied, and discussing any potential bias that may have resulted from our methodology.

The final discussion and conclusion needs to focus on correctly interpreting the data analysis results, in addition to providing directions for future study – including any limitations of the study, in addition to any recommendations for future studies as well as implications for social change and theory.

We can assist you with every part of this, and our statistical consulting team is available for consultation every day at your convenience. For free, customized feedback on how we can guide you through this stage of your dissertation, you can email or call us anytime.