PR1 | Research Design and Analysis

Research Design

instruments to be used in collecting and analyzing data that helps you answer your research questions more effectively

Case Studies

a detailed study of a specific subject

Ethnographic research

in-depth observational studies of people in their natural environment, aiming to understand the cultures, challenges, motivations, and settings of those involved.

Grounded Theory

collecting rich data on a topic of interest and developing theories inductively

Phenomenology

investigating a phenomenon or event by describing and interpreting the shared experiences of participants

Narrative Research

examining how stories are told to understand how participants perceive and make sense of their experiences

Descriptive

provides information on the current state of affairs by observing participants in a natural situation

Experimental

provides causal relationship information between variables within a controlled situation

Quasi-experimental

attempts to build a cause and effect relationship between an independent variable and a dependent variable

Correlational

allows researcher to establish a relation between two closely related topics/variables

Exploratory

explores a new subject area by taking a holistic viewpoint and gathering foundational insights

Cross-sectional

provides a snapshot of a moment in time to reflect the state

Longitudinal

provides several snapshots of the same sample over a period of time to understand causal relationship

Mixed methods

provides a bespoke application of design subsets to create more precise and nuanced results

Observational

involves observing participants’ ongoing behavior in a natural situation

Non-probability Sampling Methods

samples are chosen without regard to probability of occurrence, caution should be exercised in interpreting the results

Convenience Sampling

elements are chosen primarily by convenience

Judgement/Purposive Sampling

elements are chosen based on the researcher’s or an expert’s judgement

Quota Sampling

the sample must be spread or roughly proportional over the population; samples are picked until the quotas are filled

Probability Sampling

samples are chosen based on known probabilities, samples may be generalized to entire populatio n

Simple Random Sampling

every unit has an equal chance of being selected

Systematic Sampling

every nth unit in a population frame is picked

Stratified Sampling

the population is subdivided into homogeneous groups according to some common characteristic

Cluster Sampling

the population are divided into several clusters so each is representative of the population