statistics essay sample

statistics essay sample

The Importance of Statistics in Modern Society: An Analytical Essay

1. Introduction to the Role of Statistics in Various Fields

Statistics does not necessarily mean, therefore, pedestrian analysis, nothing more than the mechanical manipulation and transformation of numbers. To rely on this would be to misinterpret what statistics—especially statistics in the service of psychology—ought to be. The tools we have been considering so far, the methodology of psychometrics and multivariate analysis, are useful things only if they are called into play only after the psychological problem is well understood—after the researcher knows, or has solid grounds for believing, that the relevant phenomena differ either prospectively or in terms of constructs salient to theoretical orientation. It is certainly possible, of course, to go far in descriptive analysis; and indeed, classical psychological activity employed ad hoc quantitative tools in order to cast light on human conduct and thought processes, before the intrusion of either eugenics or existentialism forced psychology to turn its eyes away from a direct confrontation with processes and to a concern with persons and society. At the same time, it seems only coincidence that a direct analysis of experimental research is beginning to catch up with our understanding of individual, dyadic, and group behavior.

While some students take statistics because they wanted to, most have come to it under some duress. They have heard that it is much in demand in the job market and have been told something by way of caution by someone in the psychology department. They are often uneasy with mathematics and often consider probability less as a numerical concept than a matter of opinion. The image of statistics is none too attractive or inspiring. But those who have made the best of this none-too-happy beginning in a subject which is too often called psychological statistics or sociology statistics in college courses are capable in high school of more excitement about algebra, say by way of problems which arise in chemistry. Perhaps it is all the more needed essays such as this statistical subjects fall on fertile soil except in mathematics departments. And we have all too few other forums. A convenient and undistinguished mind with a slide rule carries less authority in scholarly debates as to the direction of expansion.

2. Key Statistical Concepts and Methods

All data are developed under structures that cause information records prove that surprising events are, in fact not just infrequent on the temporal domain, the exception in the universe. The spaces allocated to such events exist, just as minute gravitons that flit across our cosmos. With this observation, it may seem that behavioral consequences from potentially benchmark altering information contained in financial markets are, after all, in evidence. Several authors analyzing financial market performance noticed that the efficiency one perceives as possible, only if possessing powerful information sources, matches the markets produced observables. A list of potential events buyers of information possess that may cause a correspondence is given. The key point both made is apparently that the more comprehensive structures for the end users, the more likely non-trivial information provide-sources generate very surprising hypothesis tests. So, a more careful examination of inefficient ripple effects exhibited in financial markets might stem from this realization, along a combined passage that the more confining structures, the less-obstructed of terms to other possible arguments, register.

To discuss in detail, the key statistical concepts and their methods in one empirical article can be overwhelming. To use mathematical probability, statistical methods are used for the analysis of data. Therefore, data are categorized as interest, and its formation demands careful specialized examination to properly confirm whether they provide information for, as one example, originating input messages. All statistical methods use randomness, recovering information from data edged in uncertainty; as a consequence, techniques could give emphasis to events that seldom happen. The decisionistic nature of a method is circumvented when acquiring input data by deciding upon the answer, and tracking it down conditional on a respondent who can carelessly answer questions in a trial, inaccurate way. Such a potentially answer can magnetize imprecision to the data, leading to serious difficulty in data editing techniques, as well as to, as an outcome, misleading lead-based observations.

3. Applications of Statistics in Real-World Scenarios

It is a miracle drug that can relieve diseases of the statistical patient in the health area. Statistics can deliver mothers and moms who are waiting for a healthy baby in health by providing consistent delivery. It is appropriate to use statistical methods to drive topics valuable to communities such as allowing plants to grow, designing waste disposal, study atomic radiation issues, and propose advances in weighting, capturing, and measuring chemicals which can damage the soil. Many students are educated in the use of climate history to measure periods in the subject of environment. It takes time, but when they finish educating, almost all residents of the U.S. do not experience at least 4 statistics. Such matters are part of the daily activities of most individuals. We need to realize these statistics when we are prepared to make purchasing choices and vote, and when we spend hours in business. Civil and economic empowerment for a country depends on the efficient skills of functions and opinions of knowledgeable voters.

The new advances in technology are expected to alter the development prospects of the human race. Besides developing statistics for a particular parameter or trying to identify the genuine pattern hidden in the very fabric of the definite phenomenon, it is a tool for analyzing results of experiments of any kind, no matter how the data is collected. Every household, business, and college students evaluate at least some of their activities using statistical methods. Statistical techniques can be employed in areas including crime and public safety, education and social sciences, energy and environment, financial matters, government, infrastructure, overall health matters, and labor, employment, as well as income or wages, national security and veterans plan, etc. Agriculture needs statistics to operate profitably. It requires statistics for the safety of food supply, regulating environmental processes, operations, predicting the weather, etc. Social scientists can adopt statistical techniques and better understand civil rights, practices, homicides, and racially biased behavior, as in issues of broad public concern, such as joblessness, gross regional product, and many people experiencing poverty.

4. Challenges and Ethical Considerations in Statistical Analysis

The well-known George E.P. Box (1919-2013) once persuasively pointed out that all models are wrong, but some models are useful! Indeed, the vast development of statistical theories and methodologies would not have made it possible to produce much useful statistical usage if one always hankered after the perfect fit of the formulated statistical model to the real model. In the meantime, however, we have to recognize that the mis-specification of the model can induce an influential drawback on the conclusions drawn from the analyses of data. In order to significantly derive the authentic nature of sources and to make precise statistical inferences or decisions about different aspects of the data generating process, more challenges and frustrations have to be faced with. It is the responsibility of the data analyst to be critically aware of the situation in which such drawbacks might exist. Sensitivity analysis and diagnostic checking are some of the potential approaches to help alleviate the issues associated with model misspecification.

An outstanding challenge in statistical analysis is the construction of the genuine statistical model, which differs from the data generating process. The statistical model aims to provide a precisely fitted analytic formula for the real model. An inadequate statistical model may lead to biased and inefficient estimations of the parameters, incorrect statistical inferences, or inconclusive conclusions. It should be noted that the complexity of various phenomena in social and natural sciences, engineering technologies, and the relationships among variables are always much more complicated than those abstracted by a statistical model. Telescoping the various characteristics of a complex process into a suitably structured statistical model that captures the essence of the research inquiry is one of the key missions in statistics. To accomplish this task, it usually involves not only the knowledge, experiences, and intuitions in the subject matter but also the expertise in statistical theories and methodologies.

5. Conclusion: The Future of Statistics and Its Impact on Society

Apart from the research in the area of technological advancements and new data sources, the increased importance of statistics for the scientific and technological development is addressed. Since scientists are getting to the point of collecting big amounts of new essential data and are realizing its importance to help humans in the near future, statisticians have been more involved in more general scientific projects, in which statistics is not the main goal, but serves instead as a tool to give scientific support on a particular subject.

Within the statistical community, the biggest debate is about the kind of statistician we want to be. Are we data scientists, working in the technological era of big data? Are we data gatherers and analysts, easy targets to the robotic era? We are all these and more. In the age of big data, the target of statistics methods research has become diversity. Scientists are gathering more and more new kinds of data and it is important that statistics adapts to these new situations.

The analysis of data that drive the modern world lies at the heart of modern society. These data affect many decisions in daily life and change the directions of scientific research. But data also have their limitations. Most limitations are due to the simple fact that data do not and cannot measure the infinite variables related to a real-world problem.

Statistics measurement is very important in this world. Statistics researchers are not only responsible for determining the size of a problem, but also to show why some groups are more affected than others, and why a problem occurs. This is all crucial for the development of policies to deal with these problems. Policy-making is a very applied area in statistics, which leads to our next point.