PADM810 Quantitative Methods Review
Michael Discussion Thread: Quantitative Methods Strengths and Weaknesses Michael PADM810 Discussion Thread: Quantitative Methods Strengths and Weaknesses Quantitative research methods allow a systemic approach to data, specifically focusing on the numerical implications at any given moment. There are two sides to research quantitative and qualitative. Qualitative research can focus on cultural nuances without the numerical significance, and Quantitative would focus on the numerical values of the cultural nuances, from diminishing resources, purchasing power, and any other statistical-based quantitative piece of information.
In this post, we have focused on Quantitative research methodology and how it applies to public administration. What are Quantitative Methods? The Oxford Dictionary defines it as “Relating to, measuring, or measured by the quantity of something rather than its quality” (Dictionary, 2008). Providing this general idea of what Quantitative research means, it is easily ascertained that the focus is on any given moment’s numerical or even intrinsic value.
The concept of Quantitative research is listed in the Oxford dictionary as “Emphasis on objective measurements and the statistical, mathematical or numerical analysis of data” (Dictionary, 2008), supporting the base definition of Quantitative. There can be more than four common types of Quantitative research methods; however, the typical four are Descriptive, Correlational, Causal-Comparative/Quasi-Experimental, and Experimental Research.
One author states, “Quantitative researchers often discuss ethics as if specific ethical problems can be reduced to abstract normative logics (e.g., virtue ethics, utilitarianism, deontology). Such approaches overlook how values are embedded in every aspect of quantitative methods, including observations, facts, and notions of objectivity” (Zyphur & Pierides 2020). Having the capability of including individual values is vital as they influence the core concepts. The four core types of quantitative methods are essential to understand as each has a time and place to utilize.
There are moments when more than one method is used, and portions of each technique are combined into a mesh of quantitative methodology to reach a specific point in research. These methods are easily understood, but there is a small amount of malleability for each one, as they can be tailored depending on the situation they are being utilized for.
The standard quantitative methods will be briefly described in the following paragraphs. Descriptive quantitative methods have been referred to as the characteristics of a population or possibly a phenomenon being studied. These are just the characteristics, not the fine points or in-depth details, but just the data characteristics in a general sense. Understanding data characteristics concerning a population or phenomenon allows for developing projective correlations.
Correlational quantitative methods look into the relationship between two or more variables without the researchers’ interference. Correlation for data analysis is vital in any level of research and even more so in quantitative analysis. This method is often integrated into multiple research points to understand any given circumstance better and generate data that may assist at any given moment. Causal-Comparative is one of the few methods that is technically a group of processes that accomplish a single task. The task is to examine the potential causes of observed differences in existing groups.
The three most common methods in Causal-Comparative are the Chi-square test, paired samples, independent t-tests, and analysis of variance (ANOVA, ANCOVA). The methods can also be integrated into other quantitative methods to reach the desired outcome. The quasi-Experimental quantitative method is unique as it researches the impact of an intervention. There is always a need to understand what will happen if researchers intervene in a population or phenomenon. This method is the primary method utilized to understand that impact better.
Experimental Research quantitative method is seemingly the oldest concept in quantitative methods, as it establishes cause-effect between variables and has been a common scientific concept since the start of society. This method is one of the basic constructs that inadvertently helped solidify society as it is known today and continues to assist in breakthroughs in every level of science globally. One author states, “Research in the social sciences is built on either quantitative or qualitative analysis, depending on the research context” (Lo et al.…2020), and with society being fluid, It is also essential to review the strengths of quantitative research methodologies.
The strengths of these general methods will be briefly reviewed in a public administration environment in the next section. What are the strengths of using Quantitative Methods in Public Administration? The four standard quantitative research methods are Descriptive, correlation, Causal-Comparative/Quasi-Experimental, and experimental. These methods can be standalone processes or combined within other constructs to reach specified goals.
Each technique has highlights and lowlights on its merit, but they will be reviewed based on a public administration environment in this section. Descriptive is a method that can raise a political leader from nothing to something, as understanding the characteristics of a population is to understand the direction the region is heading in. The characteristic of a population can determine needs, purchasing trends, sociodemographic acceptance, business acceptance, and many other constructs that extend from understanding the essential characteristics of a demographic. This is one of the most considerable strengths of quantitative methods, and if integrated with different research methodologies, it can produce data to understand large-scale constructs.
The correlational method is one concept used in more than just public administration but even in essential conflict resolution. The relationship between two variables and those variables can be any number of things. One example is two warring factions in a middle eastern country or even two opposing counsels in court. No matter the variable, the data can be reviewed to understand the variations between the two better. Understanding what is going on between two variables is huge in public administration and is used in military processes regularly.
Causal-Comparative is a unique method because it has several internal components comprising multiple working parts. The most common methods within this quantitative method are the Causal-Comparative Chi-square test, paired samples, independent t-tests, and analysis of variance (ANOVA, ANCOVA). The premise of this concept is the data of observed differences in existing demographics and or phenomena. Observed being the keyword in this construct as interference is not a thing for this method, and only what can be displayed for the world to see is on the research docket.
While this concept is similar to the phrase “What you see is what you get,” researchers and academics use this premise to understand the visible variations, then use that data to work towards a common goal, which is a strength for any industry. Quasi-Experimental seems like it is something from Star Trek; the show’s prime directive prohibits Star Fleet members from interacting with the natural order of any given civilization, all the while this method looks at the potential outcome of such interferences. Understanding the effect of these interferences is essential; for example, the fiscal bailout was reviewed with this quantitating analysis so many years ago to know if the results would be amenable.
This is an asset on a broad scale and can be an asset on small constructs like villages or towns, but it is often overlooked at that level as a tool to use. Experimental Research is as old as the Bible as it is cause and effect. The cause of a situation, emotion, action, whatever the target may be, and the effect of the said target on any given point in this reality. This is the baseline for many of the actions of the current political leadership. The leaders look for understanding behind the action, look for likely results from a planned action then weigh the pros and cons.
This is a definite strength in public administration quantitative analytics. Quantitative research in the rawest form has been around since before public administration as we know it existed, and these concepts are not going away soon—policy practices for regional administration and healthy food products for schools in different circumstances. Definitively, public administration has been affiliated with the government; maybe that will change as larger companies are making impacts just as significant, maybe not. Quantitative research and public administration are not explicitly limited to the United States.
In one instance in Italy, quantitative research had to be implemented in conjunction with public administration officials in response to the current pandemic. One author points out, “On the supply side, the production structure exhibits a strong participation of Italian businesses in global value chains, thus making the country highly exposed to the disruption of global supply chains induced by the shock” (Pietro… et al., 2020). While quantitative research methods have the basic four concepts, researchers continually expand upon quantitative methods as a whole.
One concept is Quantitative Easing which is an abstract monetary policy focused on obscure investments, there is, of course, more detail and complexity to it, but the point is that it is a quantitative method that impacts research that is relatively new in comparison to the other quantitative methods be it research or monetary practices, one author indicates “Overall, we find that these QE policies have significant effects on financial variables such as the exchange rate, and these effects are larger concerning those in output and prices” (Carrera & Ramírez-rondán, 2019-2020).
This would be a strength, as the quantitative research and fiscal methods are fluid, thus being adjusted to benefit any data-driven situation. Shedding a little light on the fact that these concepts are global is essential, as it also shows the weakness of the concepts on a worldwide scale. The following section focuses on the hindrances or disadvantages of quantitative research methodology within the public administration environment and the details that cause the weaknesses. What are the weaknesses of using Quantitative Methods in Public Administration?
Descriptive quantitative research methods may have the capability of making or breaking political leaders but, in a general sense, cannot stand alone concerning research. There must always be supporting data and the results of descriptive quantitative methods. This is a significant weakness as it can take additional person-hours and funds and could lead to extension requests on deadlines to finish research due to lacking complete data for specified goals.
Correlational is a well-known concept that is the variations between two constructs, be it people, actions phenomenon, or other variables that may be of interest. There can be additional points in correlational research methods. Still, as the number grows, the exponential correlational data points between each variable make it more challenging to work with the more included variables. This is the main weakness of this method; however, keeping it simple is crucial, and additional methods can benefit.
Causal-Comparative is the unique method that contains more than one method within the Causal-Comparative research method. This can cause conflicts between each method and others and create complications for those attempting to integrate this method with other processes, as it already contains multiple processes.
Quasi-Experimental is a necessary process, but it can be concluded as a justification for high-level interference. Government interference in an economic downturn, military interference in Ukraine, and many other examples. Understanding the outcome of the interferences frequently leads officials to think the positive outweighs the negative. This comes from the perspective of some United States citizens government interference is not welcome in most situations unless help is needed, and that may be the current situation, but it is not in every situation. Experimental Research is cause and effect. If only looking at data, the cause and the effect may not line up.
The cause can have implications that are not data-driven, like free will; the ultimate quantitative problem is the chaos that is the human decision-making process will always put a stopper in logical data-driven processes. Some believe the quantitative method is the best research methodology for all applicable purposes. This is not the case, there is only one perfect concept, and it is not the concept developed by man; the Bible states, “Surely there is not a righteous man on earth who does good and never since” (Ecclesiastes 7:20, Bible, 2008).
Perfection is something society strives for, well as least usually strives for, as it is designed for us to be perfect; the Bible states, “You, therefore, must be perfect, as your heavenly Father is perfect” (Matthew 5:48, ESV, Bibles 2008). This creates a vacuum in developmental processes as the creators strive for perfection, but as a race, it will never be reached until it is time to return to heaven. The following section will explain how professors can analyze data and help public administration make appropriate decisions. How can academicians use data analysis to inform public decisions and educate public leaders on the application of Quantitative Methods?
Public Administration is considered both a governmental construct and an academic field. Public administration is an institution known for its theoretical approaches to resolving political and sociodemographic issues, backed by academia, “As an academic field, public administration is obligated to advance theoretical and pragmatic understanding of governmental institutions and processes” (Wright… et al., 2004).
Public administration has always been a focal point in some form or fashion, and research methods used in public administration are scrutinized even more than usual. The overwhelming scope of public administration can be seen in academia, the private sector, and government sectors throughout the globe. One author breaks down public administration “First, public administration is characterized by plurality, both of theories and topic as well as philosophical positions and research methods” (Groeneveld… et al., 2015).
There are multiple points in academia where data can be seen as originating from academia; for instance, students in Ph.D. programs for Public Administration have to take classes that focus on quantitative research method comprehension, which instills some basic understanding of the need for the processes and implications for future use. This not only shows those interested in political careers the necessity for this type of research method but instills the concepts in the school to continue research on any number of ongoing issues to assist the national leaders in coming to a resolution.
Academia instills the processes in political leaders as students, builds the research constructs, continues the research as a practical way to instruct students while solving problems, and then provides the resolutions to the designated point of contact for the problem in question. While this seems simple, the issue is that many political leaders do not hold academia high in regard and disregard warnings or even direct communications concerning any issues that may be ongoing. Conclusion Quantitative research methods are tools for all generations of leaders, whether in public administration or otherwise.
There is no single way to do anything in this world, including research. One great example of variations in this type of research is “Quantitative researchers have applied these high standards for transparency in a survey and other quantitative data that are collected and coded by researchers, as well as in analytic data techniques” (Batt & Kahn 2021) and the fact that analysts or researchers believe transparency provides comprehension, which is not the case.
This type of research will dictate the methodologies, and whoever may be the researcher will adjust the approach as needed, depending upon the situation. This post asked for strengths, weaknesses, and potentiality for assistance from the academic world. These are all considerations for a perfect world, and as a society or even a race goes, we are far from perfect. One author points out that “In any discipline, arguments for methodological choices depend partly on the research problem at hand and partly on the philosophical or paradigmatic preferences of the researcher” (Groeneveld et al.… 2015).
Quantitative methods are tools; every tool has specific idealistic use, and a good mechanic knows it takes more than a single tool to do the job right. Lastly, with varying economic standing and shifting regional taxations, there is no single way to use quantitative research methodology across the entire country; even the requirements for the exact employment type change depending upon the region, so it will always require more than the basic quantitative concepts to produce a good result.