PRF study guide
PRF · Work through your exam, one topic at a time.
The Professional Research Foundations (PRF) credential is designed for people who plan, conduct, oversee, or consume research and need to demonstrate a working command of the full research lifecycle rather than a single technique. Candidates typically include early-career investigators, research coordinators and project managers, data analysts moving into study design, graduate students preparing for independent work, and staff in ethics, quality, or evidence-synthesis roles. The PRF study guide has 8 sections and about 2,397 words.
01Research Design and Planning
The candidate must be able to move from a research question to a defensible design. Know the difference between a hypothesis-generating (exploratory) and hypothesis-testing (confirmatory) study, and why a confirmatory study needs a pre-specified primary outcome, a sample-size justification, and an analysis plan fixed before data collection.
317 words, about 2 min02Ethics, Integrity, and Regulatory Compliance
Candidates should be fluent in the governing principles: respect for persons, beneficence, and justice. Know how informed consent operationalizes respect for persons, how risk-benefit assessment operationalizes beneficence, and how fair subject selection operationalizes justice.
321 words, about 2 min03Literature Review and Evidence Appraisal
Know how to frame a searchable question using population, intervention or exposure, comparator, and outcome. Understand the value of pre-registering a review protocol, using multiple databases, and documenting search strings and inclusion decisions so the process is reproducible.
307 words, about 2 min04Measurement, Instrumentation, and Data Collection
Candidates must understand reliability and validity as separate properties. Reliability concerns consistency and includes inter-rater, test-retest, and internal consistency.
287 words, about 1 min05Quantitative Methods and Statistical Analysis
Candidates should understand the logic of hypothesis testing: null and alternative hypotheses, type I and type II error, power, and the p-value as the probability of data at least as extreme given the null. Know that a p-value is not the probability that the null is true, and that confidence intervals convey both magnitude and precision.
324 words, about 2 min06Qualitative and Mixed Methods
Candidates should understand the major qualitative approaches: phenomenology (lived experience), grounded theory (theory generation), ethnography (culture and context), and case study (bounded system). Know that sampling in qualitative work is purposive rather than probabilistic, and that saturation is a judgment about informational redundancy, not a fixed number.
283 words, about 1 min07Data Management, Quality, and Reproducibility
Candidates should understand the data lifecycle: planning, collection, entry, cleaning, storage, sharing, and archiving. Know the value of a data management plan that specifies formats, naming conventions, storage, access controls, and retention.
271 words, about 1 min08Reporting, Dissemination, and Translation of Findings
Candidates should know that reporting guidelines exist for major designs and that their purpose is transparent, complete reporting of what was done and found. Understand the general structure of a research report: rationale, methods, results, limitations, and interpretation.
287 words, about 1 min