Organizing, Analyzing, & Interpreting Data Chapter 10 Organizing, Analyzing, & Interpreting Data Janet Salmons, PhD

Objectives Identify key steps needed to create an analytic strategy. After reading and reflecting on Chapter 10, you will be able to: Identify key steps needed to create an analytic strategy. Differentiate between deductive, inductive, and abductive reasoning, and explain how they would be used in data analysis and interpretation. Describe stages of the data analysis process.

. Analysis is a recursive process. Reasoning Coding Reporting The analytic process appropriate to the study aligns with the research purpose, methodology, methods, and theoretical frameworks central to the design. A comprehensive exploration is outside the scope of this book, however you will find some central principles to help you begin to discern meaning from your data. Memos

Reading, Re-, Re-re-reading, and listening and viewing your data Careful, multiple readings and exposure to the data will be essential. Even if you are working from transcriptions, it may be worthwhile to listen to the original recordings, and/or view any visual data multiple times.

Sequence of analytic steps makes a difference Option A Option B Compare across interviews More interviews on questions that emerged All documents All interviews Compare across cases Interview and documents B A There is more than one way to analyze your data.

Coding Coding is an essential part of the many types of social research. Once data collection has been conducted, the researcher will need to begin to make sense of the data. Lockyer et al. (2004) describe it as follows: Coding requires the researcher to interact with and to think about the data. It is a systematic way in which to condense extensive data sets into smaller analyzable units through the creation of categories and concepts derived from the data. Coding is a process that allows you to discover links between different parts of the data that are regarded as having common properties. Coding facilitates the organization, retrieval, and interpretation of data and leads to conclusions on the basis of that interpretation.

Analytic Memos Researcher reflexivity is key to qualitative research analysis. Keeping track of ideas and insights is successful through writing memos. Codebooks help you to organize and categorize levels of codes and memos.

Theories and Reasoning Two ways to use theory in data analysis: Deduction: theory is the first source of knowledge; research proceeds from theory, through hypothesis, to empirical analysis. A strict form of deduction is not necessarily suitable for qualitative research. However, qualitative researchers may use a theoretical framework that offers the foundation for analysis and interpretation of data. Induction: theories are outcomes of empirical research; research proceeds from empirical research to theoretical results. New constructs, theories as well as typologies and models are generated from the results.

Inductive Reasoning Inductive reasoning allows us to make order from chaos, to see the whole from the fragments. et al., 2014). Researchers identify codes from the data. Themes and trends data are drawn from the data and interpreted by the researcher.

Deductive Reasoning Deduction involves reasoning from the general to the particular. Researchers can identify premises, categories, principles from the research problem statement, research questions, interview questions, theoretical framework or seminal literature that become codes used to screen and categorize the data.

Abductive Reasoning Abductive reasoning is a form of logical inference that goes from observation to an explanation that accounts for the observation, and seeks to explain relevant evidence (Locke, 2010; Schwandt, 2007). ‘Abduction’ refers to the process of moving from the everyday descriptions and meanings given by people, to categories and concepts that create the basis of an understanding or an explanation to the phenomenon described.

Multiple forms of reasoning may be needed to find meaning in data Reflexive researcher Deductive coding: looking for evidence of key concepts identified the research design. Inductive coding: looking for concepts, themes and patterns that emerge from the data. Abductive reasoning: moving from codes to clusters or categories, to explanations. Findings

Analyzing and interpreting Data & the Qualitative eResearch framework All elements of the research design come to fruition at the analysis and interpretation stage. At this stage, the researcher aims to generate results, findings or conclusions that achieve the purpose of the study. The researcher must be mindful of his or her position and guard against undue bias. This can be difficult in situations where the research questions are not answered – or where the answer is not what the researcher expected.

References Bernard, H.R. & Ryan, G. (2009) Analyzing qualitative data. Thousand Oaks, CA: Sage. Johnsson, L., Eriksson, S., Helgesson, G. & Hansson, M.G. (2014) Making researchers moral: Why trustworthiness requires more than ethics guidelines and review. Research Ethics, 10(1), 29–46. doi: 10.1177/1747016113504778 Locke, K. (2010) Abduction. In A.J. Mills, G. Durepos & E. Wiebe (eds.), Encyclopedia of case study research. Thousand Oaks, CA: Sage. Schwandt, T.A. (ed.) (2007) The SAGE dictionary of qualitative inquiry. Thousand Oaks, CA: Sage.