a) Descriptive data analysis: This refers to the process of organizing, summarizing, and interpreting data to describe the characteristics or patterns within a given sample or population.
b) Inferential data analysis: This involves making inferences or generalizations about a population based on the observed data from a sample. It uses various statistical techniques to determine the likelihood of an observed result occurring by chance.
c) Primary data: These are data that are collected directly from original sources for a specific research purpose. The researcher collects primary data through surveys, experiments, observations, interviews, or other means.
d) Secondary data: These are data that have already been collected by someone else for a different purpose and are made available to researchers. Examples of secondary data include government reports, academic literature, and data collected by other researchers.
e) Units of analysis: It refers to the entities or subjects that are being studied in a research project. The units of analysis can vary depending on the research question and can be individuals, groups, organizations, or even countries.
f) Research: It is the systematic investigation of a topic or problem to discover new knowledge, interpret existing knowledge, or develop or test theories.
h) Sampling frame: It is a list or a set of units from which a researcher selects a sample. It provides a complete representation of the target population and helps ensure that the sample is representative of the population.
i) Qualitative research methods: These are research methods that focus on understanding and interpreting social phenomena through non-numerical data. Qualitative methods include interviews, focus groups, observations, and content analysis.
j) Quantitative research methods: These are research methods that involve the collection and analysis of numerical data to test hypotheses, establish relationships, and make statistical inferences. Quantitative methods include surveys, experiments, and statistical analysis.
k) Inductive research: It is an approach to research that involves formulating theories or generalizations based on observations and patterns in the data. Inductive research starts with specific observations and then develops broader hypotheses or theories.
l) Deductive research: It is an approach to research that involves testing existing theories or hypotheses using new data. Deductive research starts with a hypothesis or theory and then collects data to confirm or refute it.
m) Replicability: It refers to the ability of other researchers to replicate or repeat a study using the same methods and procedures and obtain similar results. Replicability is an important aspect of the scientific method and helps establish the validity and reliability of research findings.
n) Precision: It refers to the level of detail, accuracy, or exactness in measurement or estimation. Precision is important in research because it determines the reliability and validity of the data and findings.
o) Falsifiability: It is the capacity of a hypothesis, statement, or theory to be proven false by empirical evidence or observation. Falsifiability is an essential characteristic of scientific research as it allows for the testing and potential rejection of hypotheses.
p) Parsimony: It is a principle in research that favors the simplest explanation or theory that adequately explains a phenomenon. Parsimony suggests that researchers should avoid unnecessary complexity in their explanations and theories.
q) Probability sampling: It is a sampling technique where each member of the population has a known, non-zero chance of being selected for the sample. Probability sampling methods include simple random sampling, stratified sampling, and cluster sampling.
r) Non-probability sampling: It is a sampling technique where the selection of sample members is based on the researcher's judgment or convenience and does not involve a random selection process. Non-probability sampling methods include purposive sampling, snowball sampling, and convenience sampling.
s) Panel mortality: It refers to the loss of individuals or units in a longitudinal study over time, resulting in a decrease in sample size and potential bias in the results. Panel mortality can occur due to participant dropout, non-response, or attrition.
g) Research design: It refers to the overall plan or structure that guides a research study. The research design includes the selection of research methods, data collection procedures, and data analysis techniques, and helps researchers address their research questions or hypotheses effectively.