What to Consider When Thinking about Data and Analysis

Define your research questions. Every data collection and analysis effort has to begin with asking the right research questions. Questions should be measurable, clear and stated as simply as possible.

Decide what to measure. Consider what kind of data you need to answer your key questions. Does answering your research questions require quantitative or qualitative data or both? In general, when you measure something and give it a number value, you are creating or working with quantitative data. When you classify or judge something, you are creating or working with qualitative data.

• Quantitative data deals with things you can measure objectively. This data type is measured using numbers and values and may include things like the area of a land parcel, how many people live in a household, ages and dates of birth to name a few.
• Qualitative data deals with characteristics and descriptors that can’t be easily measured, but can be observed subjectively. Qualitative data includes things like measuring perceptions about tenure security or measuring attitudes toward government land policies.

Decide how to measure it. Thinking about how you measure your data is just as important as deciding what you want to measure.

• How frequently do you need to collect and analyze your data, monthly, quarterly, annually?
• What is the type of data? Are you working with quantitative or qualitative measures?
• What is its unit of measure? Will this data be measuring people’s perceptions with a text or narrative response or will it be measured using numeric values like hectares or acres?

Document your steps. Consider the software you use for analysis, and whether those applications automatically generate information about your data files (metadata) and process steps (such as log files). Keeping track of your data processing and analysis steps can save you time when you want to recreate your work, or share your methodology with others.

Boost your skills. If you’re considering using a new application you are not familiar with, or you just want to learn more about software that you use regularly, look for training opportunities. There are a wide variety of online courses you can take to increase your skill level.

Keep your data safe. Document and describe your data as you capture it, organize your files, and make smart choices about where you store your data. Since some software programs produce files that are proprietary and can only be opened in their applications, consider saving data in formats that can be opened by different software programs.