54 Summary

This chapter discussed common concerns in data collection such as bad data and and militating strategies. We highlighted four of the most common types of errors (coverage, measurement, non-response and sampling) as well as some tips for minimizing them in data collection. We also indulged in an expanded discussion of sampling and considerations for developing effective sampling frames. As what might be considered an addendum to chapter 7 (Methodology), we emphasized that you ask yourself three questions as you dive into data collection: 1) What data is most pertinent to my research question? 2) How much of it can I and do I need to collect? And 3) How is my data still limited with regard to answering my question (either through bias or lack of representation)? The chapter also outlined specific considerations for primary and secondary data collection in both qualitative and quantiative studies. First, we reiterated some guidance for conducting interviews and surveys in primary research. Next, we discussed secondary data and provided a list potential sources. The chapter ended with tips to help you assess and evaluate data and procedure to ensure that you are collecting quality data, including considerations about missing data and data transformation.