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Quantitative data analysis Toolbox

2.4.2 Taking stock of your available resources

No matter how well you frame your analysis questions, your work will of course be limited by the resources that you have available. Consider how your resources will shape what you can accomplish. You should consider things like:

  • Available datasets: What datasets do you have access to that would be relevant for your problem at hand? Is this data sensitive in any way?
  • Skillset within your team (or yourself): Do you or your team have past experience with this kind of work? Do you know how to use the tools that you have available for the analysis?
  • Time: How much time do you have available to dedicate?
  • Knowledge of subject matter: In addition to considering your relevant practical skills, how familiar are you with the theoretical foundations for this work? Do you understand the phenomena that you are investigating and the factors that are relevant to consider?
  • Tools available for the analysis: Do you have access to tools that will help you investigate your data? Are these tools something that you’re familiar with?

For example, your analysis plan and goals will be significantly different if you have a team of skilled data scientists working for four months, than if you have one week to do an analysis that you don’t have experience with previously.

Taking stock of available resources will also help you determine the feasibility of your analysis. In some cases, you might decide that you don’t have enough of the resources that you need to proceed. This could, for example, force the team to make pragmatic decisions, such as reducing the survey length of time so the team will be able to complete data collection within budget.

This is much better to identify at the beginning of your analysis process than once you’re halfway through!

For example, one objective of the data collection in the case study was to determine access to improved WASH services among the target population (as seen in research question 3: What proportion of the population has access to improved WASH services and does it vary by region?).

As such, the survey includes a question specifically asking respondents to state their primary source of drinking water. Different types of water source are categorized as ‘improved’ or ‘unimproved’.

However, this question is less accurate than water testing to determine the quality and safety of the household drinking water source. For example, ‘hand pipes/boreholes’ are considered an improved water source, but may have been constructed at a low quality or contaminated post-construction. If the team had the available resources (budget, time availability and technical knowledge), then more accurate water quality data could be collected as part of the field work.