In order to code in qualitative research you are faced with the task of quantifying your subjective data, and this means converting research that consists of subjective observations into an objective data set. In other words, you are required to quantify your qualitative research first in order to code in the research. In short, you will use numbers to interpret research observations that are not numbers-based.

Step 1

You will need to organise your research results before coding it in.

Gather your pre-research outline as well as all of your field notes, interview question results and/or survey results. This article assumes that you have already conducted your research and are seeking to code it in for the purposes of presentation and/or publication. As converting qualitative research into quantitative results can be a capricious process, it is necessary that you assure your pre-research theory and methodology are close at hand for reference.

Step 2

Underlining key words is a good tool for tabulating textual analysis.

Quantify and tabulate your results. In order to code in qualitative research, you will have to analyze your subjective data from a mathematical viewpoint. If you are doing textual analysis, this might simply involve counting the number of times a certain word is listed--It is easier to do this in word processing applications, but you can do it by hand. Surveys are qualitative, but multiple choice questions can be coded in by percentage of response A, B, C, etc. Field notes can be coded in by finding common objective observations that you have made, e.g., "The shoppers I observed at Tesco appeared more in a hurry than those at Asda" can be coded in with 1 representing a slow pace of shopping, 2 representing a faster pace, and so on. Your numbered results will constitute the data that you will be coding in. Tabulation is simply compiling all the data together.

Step 3

You are transferring (coding in) your research notes into electronic format to be empirically analyzed.

Enter the results into a spreadsheet. You should have at least 15 results, or you should not be thinking about "coding" anything, with the exception of a case study, in which case the 15 results would come from within the research concerning your one specific case, with each of the fifteen variables a sub-point of your subject of study. Results should be entered with the subjects' names associated with the data on one axis (spreadsheet row headers) and the numerical results pertaining to the subjects on the other axis (spreadsheet column headers).

Step 4

Each color in your final graph or chart might represent different variables for one recipient or subject.

Control for as many objective factors as possible, e.g., age, race, sex, etc., and then code in your qualitative data in the succeeding columns. Coding in your qualitative data requires you to list quantitative data that might be boring but nevertheless might also answer your research question better than your hypothesis regarding your qualitative data. So while your rows might contain only one type of data, e.g., someone's name, the column headers might contain several variables that do not constitute your qualitative data, but which represent the "control group." Coding in qualitative data without quantitative data is not a good research practice, as it leaves no controls and can invalidate your research findings.

Step 5

Coding qualitative data as percentages of something is a good way to numerically represent your subjective research.

Label the category, in the header of a column, with a word that captures the essence of what you are measuring. This is where you will need your pre-research theory and methodology notes. For empirical data, such as "age," you would of course just put in the age, but for something like "gender," which is not the same as "sex," you cannot just use the word gender, so your data set in this case should be named something that relates to the way in which you measured the more subjective variable gender. For example, "percent male" would be much more telling than simply "male" or "female" in terms of statistical comparison. This rule does not apply if you are coding in answers from a questionnaire that only allows the participant to select from two answers, in which case the coding can be simplified by assigning two different numbers, e.g., 1 and 2.

Step 6

If you have done a good job coding in your data, your charts and graphs should provide stunning results.

Organize your results relative to your hypothesized independent variable. This will affect the layout of your charts and graphs, but also gives you immediate insight into whether your independent variable(s) has any kind of correlation with your dependent variable(s). You do this by selecting a column that has the headers of all of the names corresponding to your coded-in qualitative data, going to "format" and selecting how the data should be organized. Once you have done this, you are ready to create graphs and charts and insert your coded-in qualitative data into your presentation or paper.