Please read the following: Case 2: Barbara Geddes (1990) points out the pitfalls of selecting cases, units, or observations purely on the basis of the dependent variable.

Barbara Geddes speaks on how comparative politics goes against the rules of statistics. Statistics teaches us that we must utilize an independent and dependent variable to determine the relationship between the two. This study is trying to speak about having a relationship by using only dependent variables. Analysts trying to explain why some developing countries have grown so much more rapidly than others regularly select a few successful new industrializing countries (NICs) for study, most often Taiwan, South Korea, Singapore, Brazil, and Mexico. (Geddes 1990) Each country has its own issues and problems, which may determine its level of growth. If an analyst focuses on the dependent variables, they would have different outcomes, and it would be biased to their country. What are the general issues that each country is facing, which will give the independent variable, that could conclude the relationship between all of the countries? Variables either are the primary quantities of interest or act as practical substitutes for the same. (Kaliyadan & Kulkami 2019) We can use inferential statistics to examine differences among groups and the relationships among variables. (Guetterman 2019) Outcome rate is the importance of the study, which is essential for the program evaluator. Summative evaluations also require precise definitions of targeted goals and outcomes; grantees must be clear on how to interpret their outcomes and what data to provide to demonstrate success. (NIH 2023) The debate will have to determine the outcome of the country's growth and what dependent variables contributed to it.

Inferential statistics utilize the ANOVA, which could utilize the dependent variables to determine an outcome. For example, an ANOVA could examine whether a primary outcome measuredependent variableis significantly different for groups assigned to one of three different interventions. (Guetterman 2019) Relationships that seem to exist between causes and effects in a small sample selected on the dependent variable may disappear or be reversed in a sample uncorrelated with position on the dependent variable. (Geddes 1990) The study would be difficult to prove with just the dependent variable alone. It is cases where they could possibly show a relationship in a large sample. A small sample will not show or hide the relationship. There are multiple countries with different reasons why they are growing differently. The independent variable will need to show the relationship due to bias, and the dependent variable due to each country's own growth practices.

Then, provide explain in what ways you agree or disagree with the permissibility of the identified scenarios. Justify your reaction.

References

Geddes, B. (1990). How the cases you choose affect the answers you get: Selection bias in comparative politics. Political Analysis Download Political Analysis, 2(1), 131-150. Retrieved fromhttp://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.372.5896&rep=rep1&type=pdfLinks to an external site.

Guetterman, T. C. (2019). Basics of statistics for primary care research.Family medicine and community health,7(2), e000067. https://doi.org/10.1136/fmch-2018-000067Links to an external site.

Kaliyadan, F., & Kulkarni, V. (2019). Types of Variables, Descriptive Statistics, and Sample Size.Indian dermatology online journal,10(1), 82-86. https://doi.org/10.4103/idoj.IDOJ_468_18Links to an external site.

National Library of Medicine (2023) Review of Four CARA Programs and Preparing for Future Evaluations. Retrieved from: https://www.ncbi.nlm.nih.gov/books/NBK594901/