feat(notes): Add definition representativeness, validity

03-documentation/terms_of_reference-key_terms.md

@@ -185,3 +185,75 @@ forms of inequality:
 - Likert scale (1-4/1-5 scale questionnaire)
 - Cronbach's alpha test score (reports coherence of set of items in a group)
 - Binary answer (yes/no)
+
+## Representativeness
+
+In academic studies, representativeness can be assessed at various levels,
+ depending on the scope and objectives of the research. Here are the different
+ levels of representativeness commonly considered in academic studies:
+
+1. National Representativeness: This level of representativeness indicates that the
+ sample used in the study is reflective of the entire population of a specific
+ country. The findings are intended to be generalizable to the entire nation.
+
+2. Subnational Representativeness: At this level, the study aims to be
+ representative of a specific subnational region within a country, such as a state,
+ province, or city. The findings are intended to be applicable to the population
+ within that specific geographic area.
+
+3. Regional Representativeness: Some studies may focus on representing a broader
+ region, such as a group of countries within a certain geographical area. The
+ findings are intended to be generalizable to the population within that regional
+ context.
+
+4. Organizational or Institutional Representativeness: In some cases, studies may
+ aim to be representative of specific organizations, institutions, or industries.
+ The findings are intended to be applicable to similar entities within the same
+ category.
+
+5. Demographic Representativeness: This level of representativeness focuses on
+ ensuring that the sample used in the study is representative of specific
+ demographic characteristics, such as age, gender, ethnicity, income level, or
+ education level.
+
+6. Sectoral Representativeness: Some studies may aim to be representative of
+ specific sectors or industries, such as healthcare, education, finance, or
+ technology. The findings are intended to be applicable to similar sectors or
+ industries.
+
+These different levels of representativeness help researchers and readers
+ understand the extent to which the findings of a study can be generalized to
+ different populations, regions, or contexts. It is important for researchers to
+ clearly define the level of representativeness they are aiming for and to use
+ appropriate methods to achieve it.
+
+## Validity
+
+Internal validity and external validity are both important concepts in research
+ design and are used to assess the quality and generalizability of study findings.
+ Here's a brief explanation of the differences between the two:
+
+Internal Validity:
+- Internal validity refers to the extent to which a study accurately measures the
+  relationship between the variables it is investigating, without the influence of
+  confounding factors.
+- It assesses whether the observed effects or outcomes in a study can be attributed
+  to the manipulation of the independent variable, rather than to other factors.
+- Factors that can impact internal validity include experimental design, control of
+  extraneous variables, and the accuracy of measurements and data collection methods.
+
+External Validity:
+- External validity refers to the extent to which the findings of a study can be
+  generalized to other populations, settings, or conditions beyond the specific
+  sample and context studied.
+- It assesses the degree to which the results of a study can be applied to
+  different individuals, groups, or situations.
+- Factors that can impact external validity include the representativeness of the
+  sample, the ecological validity of the study conditions, and the relevance of the
+  findings to real-world settings.
+
+In summary, internal validity focuses on the accuracy and reliability of the study's
+ findings within the specific context of the research, while external validity
+ focuses on the generalizability and applicability of the findings to broader
+ populations or settings. Both types of validity are important considerations in
+ research design and interpretation of study results.