diff --git a/03-documentation/terms_of_reference-key_terms.md b/03-documentation/terms_of_reference-key_terms.md index 7d7e5ac..2cdd956 100644 --- a/03-documentation/terms_of_reference-key_terms.md +++ b/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.