Analysis is the process of finding out what your information means and what conclusions it will support. For survey information, item mean scores generally suffice. For behavioural indicators, such as absences and tardiness, frequency counts or percentages will do the job. These analyses are descriptive and comparable. You can use them to measure your progress from year to year.
Analysing quantitative and qualitative data is often the topic of advanced research and evaluation methods courses. However, there are certain basics which can help to make sense of reams of data.
When analysing data (whether from questionnaires, interviews, focus groups, or whatever), always start from review of your research goals, i.e., the reason you undertook the research in the first place. This will help you organize your data and focus your analysis. For example, if you wanted to improve a program by identifying its strengths and weaknesses, you can organize data into program strengths, weaknesses and suggestions to improve the program. If you wanted to fully understand how your program works, you could organize data in the chronological order in which customers or clients go through your program. If you are conducting a performance improvement study, you can categorize data according to each measure associated with each overall performance result, e.g., employee learning, productivity and results.
Basic analysis of "quantitative" information (for information other than commentary, e.g., ratings, rankings, yes's, no's, etc.):
Basic analysis of "qualitative" information (respondents' verbal answers in interviews, focus groups, or written commentary on questionnaires):
Attempt to put the information in perspective, e.g., compare results to what you expected, promised results; management or program staff; any common standards for your products or services; original goals (especially if you're conducting a program evaluation); indications or measures of accomplishing outcomes or results (especially if you're conducting an outcomes or performance evaluation); description of the program's experiences, strengths, weaknesses, etc. (especially if you're conducting a process evaluation).
Click here to view a video that explains analyzing and interpreting data.
Click here to view a video that explains writing the results section for research papers.
Contents of a Research Report - An Example
Ensure your research plan is documented so that you can regularly and efficiently carry out your research activities. In your plan, record enough information so that someone outside of the organization can understand what you're researching and how. For example, consider the following format:
1. Organization Description/History
2. Product/Service/Program Description (that is being researched)
Problem Statement (in the case of non-profits, description of the community need that is being met by the product/service/program)
Overall Goal(s) of Product/Service/Program
Outcomes (or client/customer impacts) and Performance Measures (that can be measured as indicators toward the outcomes)
Activities/Technologies of the Product/Service/Program (general description of how the product/service/program is developed and delivered)
Staffing (description of the number of personnel and roles in the organization that are relevant to developing and delivering the product/service/program)
Overall Evaluation Goals (e.g., what questions are being answered by the research)
Methodology
Types of data/information that were collected
How data/information were collected (what instruments were used, etc.)
How data/information were analysed
Limitations of the evaluation (e.g., cautions about findings/conclusions and how to use the findings/conclusions, etc.)
Interpretations and Conclusions (from analysis of the data/ information)
Recommendations (regarding the decisions that must be made about the product/service/program)
Content of the appendices depends on the goals of the research report, e.g.:
Click here to view a video that explains how to write the conclusion and recommendations.
Although you may have learned in other writing classes that summaries are appropriate conclusions for papers, summaries are typically offered as front matter (prefatory material) in research documents. Therefore, a summary is a weak, redundant ending for a research document. You may, of course, offer a few summary statements to orientate your reader, but effective conclusions do far more than recap information you have already offered in the prefatory material, the introduction, and the discussion of your document.
These endings are all based on the idea that you should draw conclusions, not just conclude. In short, they depend on your explaining “What does this mean for us?” One of the most useful conclusions for many workplace documents is a section offering recommendations or solutions. Such a conclusion is most typically used for problem/solution reports, but it can also be used for cause/effect, comparison/ contrast, and other organizational schemes. In this section, you may recommend which of several solutions is most likely to solve the problem, is most feasible, or is least disruptive.
Although instincts are important in the workplace, a reader will rarely be satisfied that they are the best grounds on which to base important decisions. Thus, you must explain the criteria on which your recommendations are based. Furthermore, your criteria must match the reader’s expectations and needs. Imagine how embarrassing it would be to offer recommendations based on a sense of urgency and moving from immediate-to-remote implementation stages when your readers think your recommendations are based on costs. In other words, you might lose all your credibility if you have proposed an expensive plan because it offers the most immediate relief for the problem, but your readers expect you to offer the most cost-efficient plan.
Your recommendations may correspond to the following criteria: