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Research is loosely translated as a search for knowledge. The term research is defined explicitly as a scientific and systematic approach to seeking pertinent information regarding a particular topic. Therefore, research is an art of scientific investigation whose aim is to get more information. There are various kinds of research, namely, essential, applied, descriptive, and analytical research (Amrhein, Trafimow, & Greenland, 2019). The focus of this review explores descriptive and analytical research. The goal is to explore their meaning in scientific study and highlight some of the major differences between both. Descriptive and analytical inquiries are different but serve an essential role in statistics and data analysis. The differences between both are determined by what they seek to achieve or explore. For example, descriptive research endeavors to describe and encourage us to learn by engaging the question of what? The analytical research aim is to analyze the data by answering the question of why? (Omair, 2015). The primary role is to determine how the issue came to be. Descriptive research relies on classification, description, creating a comparison, and measuring the data collected.
Descriptive vs. Analytical Research
Analytical research focuses on understanding the cause-effect relationships between two or more variables. For example, statistics showing the fluctuation of trade deficits between the United States and the rest of the world during 2015-2018 comprises descriptive research. One may talk about the mean or average trade deficit for a given time period. In analytical research, the researcher tries to explain the reasons why and how the trade deficit has moved in a specific direction within the given time (McLeod, Payne & Evert, 2016). Special statistics and statistical controls are needed to accomplish meaningful analytical research endeavors. Another analytical research example includes exploring why the value of the Japanese Yen has reduced against major world currencies such as euro, U.S. dollar, and British pound. This is because analytical research can better explain how and why the currency has weakened against the major currencies in the world.
Importance of Analytical Research
In research, analytical research is fundamental because it encompasses critical thinking skills and critical assessment of the information obtained in research. Students, psychologists, doctors, and marketers, among others, prefer to use analytical research to discover the missing link in study information (Valcárcel, 2017). Analytical is vital because it introduces new ideas about what is happening in your data and helps prove or disprove hypotheses. The type of data collected is essential in establishing a the relevance of a particular idea or validating a hypothesis. The information gathered helps in identifying a claim and ascertaining whether it is true or false (Omair, 2015). Therefore, analytical research is necessary because it brings together small details, often unobservable, to create more provable assumptions about a phenomenon being investigated. In an organization, analytical research helps the management in decision-making about various product promotions and the effectiveness of campaigns. In medicine, it is essential in determining whether a given treatment is effective or not. Thus, analytical research can help save lives, save money, and lead to more effective ways to met one’s objectives.
Inferential and Descriptive Statistics
The field of statistics is divided into two major categories, namely inferential and descriptive statistics. Each of the segments is vital because they offer different methods aimed at accomplishing specific research objectives. Both descriptive and inferential statistics are fundamentally different. The descriptive approach seeks to describe the happening in a particular set of data or a population. Conversely, inferential statistics give many more tools to researchers to explore findings within a given sample group and attempt to generalize them to a larger population under study. Inferential statistics results from complex mathematical calculations that make it possible for researchers to infer trends regarding the population under review using a smaller representative sample taken from that population (Amrhein et al., 2019). Inferential statistics is crucial as it enables scientists to examine the association between several variables in a given sample and make valid inferences about the larger population. Inferential statistics in analytical research always requires a research design that provides for the control of the influence of extraneous variables on the research results, greatly reducing the error in making predictions and conclusions from the research data. Descriptive statistics is concerned with collecting numbers and using them to show different features of a population using that data.
Descriptive statistics is vital in understanding issues such as the center and spread of the data collected. However, descriptive statistics does not lead to any concrete generalizations. This is because its principal measurements, namely the mode, mean, and standard deviation, have specific numbers making it hard to apply generalization. Inferential statistics uses some of the same measurements as used in descriptive statistics but also many others with unique characteristics (Valcárcel, 2017; Amrhein, Trafimow & Greenland, 2019). Examples include the standard deviation and mean but these statistics and others have a different focus. While generalizations about a specific population occur, they are not stated as exact but expressed as estimates of parameters with varying degrees of probability.
In conclusion, the term research is loosely translated as the systematic investigation of a phenomenon in search of knowledge. Two of the more important types of research include descriptive and analytical examinations. Both are very different in terms of aim and approaches used to arrive at generalization. Descriptive methods show what the data looks like while analytical research seeks to examine the causal effect between two or more variables. Analytical research is very important in many fields of study such as psychology, marketing, medicine, and other areas and commonly employed because it provides more definitive information in answering research questions.
Amrhein, V., Trafimow, D., & Greenland, S. (2019). Inferential statistics as descriptive statistics: There is no replication crisis if we don’t expect replication. The American Statistician, 73(sup1), 262-270.
McLeod, M. S., Payne, G. T., & Evert, R. E. (2016). Organizational ethics research: A systematic review of methods and analytical techniques. Journal of Business Ethics, 134(3), 429-443.
Omair, A. (2015). Selecting the appropriate study design for your research: Descriptive study designs. Journal of Health Specialties, 3(3), 153.
Valcárcel, M. (2017). Usefulness of analytical research: rethinking analytical R&D&T strategies. Analytical chemistry, 89(21), 11167-11172.