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