statistics essay help

statistics essay help

The Importance of Statistics in Modern Society

1. Introduction to Statistics

Many jobs not labeled as statistics jobs involve statistical analysis. A solid undergraduate record in statistics makes graduate studies in statistics or closely related fields such as statistics, by improving the student’s chances of admission, and by improving the student’s chance of success in graduate study.

Careers in statistics often involve a mixture of technical and non-technical components. Many jobs involve aspects of consulting with academicians, scientists, or businesspersons, teaching or training, technical and administrative support.

The availability of a solid, multifaceted background in statistics has also made the statistics major a little more attractive to students who are seeking to supplement their primary major with advanced courses in statistics. A career in statistics is more than just analyzing numbers. It is the link between data interpretation and effective decision-making. Statisticians are found in the worlds of business and industry, academia, and government. The explosion of digital data has made people who stand at that link even more valuable.

The statistics major provides the student a solid background in the statistical aspects of these fields and prepares the student for immediate employment as a statistician or entry to graduate programs in statistics. For example, the increasing availability of very large data sets used for decision-making and information sharing has created exciting new career opportunities for statisticians. Positions that require substantial background in statistics but are not labeled as statisticians are now found in such areas as accounting, biology, computer science, economics, political science, and psychology. Such positions offer excellent salaries to new graduates.

Statistical methods now play important roles in virtually all aspects of science, as well as in areas such as accounting, businesses, economics, engineering, medicine, and public issues. Its range of application is increasing at a dramatic rate and relatively new fields such as Data Mining, Machine Learning, and Bioinformatics are attracting a great deal of attention, thanks to the increasing availability of very large data sets used for decision-making and information sharing.

Statistics is an area of applied mathematics that depends heavily upon computers for its tools and methodology. The creation of statistical inferences requires applying the many advances in computing that have occurred in the last quarter-century in the areas of data management, data visualization, and real-time reporting of statistical results. We rely heavily on data in the sciences, in accounting, and in governmental programs that inform and legislate. To properly manage our accounting and health systems, to hold triad accountants and other professionals accountable for their work, to report wane facts of our social systems, and to solve scientific problems, we must turn to statistical analysis.

2. Applications of Statistics in Various Fields

• Social Sciences: The applications of statistics in social science (sociology) include examples such as the behavior of human beings during elections, analyzing the standard of living of the people, and collecting and analyzing data about each individual living in a particular place to estimate the reality of the main population and the value of parameters. It also helps in the development of urbanization phenomena and determining the relationship between two quantities, such as education and the standard of living of people in a place. It is used to formulate plans for developments in the concerned areas.

• Physics: Statistical methods in physics help physicists verify scientific laws with a certain degree of reliability. These methods are useful in controlling errors in measurements. Hypothesis testing for specific conditions such as uncertainty and error provides the degree of confidence needed to make decisions.

• Economics: The applications of statistics in economics are supply, demand, price, and production determination. Statistical calculations like the mean, mode, and median are essential for the calculation of per capita income and living standards. Calculation of parameters like the price index, unemployment rates, etc.

• Natural Sciences: The application of statistics in natural sciences is known as biological statistics. For example, sampling to determine the size of animal and plant populations. The growth pattern of plants, animals, etc.

3. Common Statistical Methods and Techniques

Reliance on sample data to make inferences about parameters has created the theory of statistical estimation. In numerous statistical exercises, point estimators or interval estimators of a certain form are utilized. Essentially, statistical analysis unites three main solution strategies: hypothesis testing, estimation, and foretelling/prediction. The strength of assumptions made in statistical analysis can rule the adoption of any of these three strategies and is also connected with the convenience of the modeling pooling studies based on single sample data. Risks and whether the researcher has the capability of assuming any of them also depend on the assumptions and vary for each of these statistical strategies. Variations of the basic model give birth to more intricate point and region estimation and detection models. Empirical clustering methods are used in numerous fields as a way to illuminate the underlying structure of the information. The theory of comparison of three classifiers provides that terminology and logistical methods are required for comparative evaluation of multiple alternative treatments. In conclusion, statistical methods contribute to both strategy and tactical decision making in the planning phase of nearly every field problem, and almost all practical problems in all other fields can be coordinated around these activities.

Statistics is broadly used in modern society due to the treatment of large volumes of varying data. It covers both descriptive and inferential statistics, and numerous important methods employed and used in all other fields are discussed within the scope that follows. For descriptive purposes, statistical concepts most useful in describing data are, for example, the frequency distribution and its graphical representation, the histogram, or the stem-leaf plot. Because it is usually easier to depict the shape of the distribution and to interpret the value that corresponds proportionately to a given area under the graph of a density function, the quantile-quantile or the normal probability plot are widely applied. The standardized technique of data presentation includes box plots, which illustrate the median, quartiles, maximum and minimum values, and identify the range of the values. With a view to collective characteristic measurement, the bar chart and the pie chart stand out.

4. Challenges and Ethical Considerations in Statistics

Members of the International Statistics community are currently seeking and in the early stages of gaining recognition of and acceptance by all those who practice statistics, from the apprentices to the world awesomely wise who truly know, of the need for all practitioners in the field to be aware of and to act responsibly upon the guidelines that have been articulated. It is vital for the continued health and well-being of the statistical community that its practice and its practitioners command public trust and confidence. And the IASC is the primary organization, worldwide, responsible for ensuring that the benes of the world and those who come after maintain that public trust and confidence for all who choose to practice statistics now and well into the next century.

For those who practice statistics, particularly for those who provide professional statistical services in business, government, and academic settings, there are numerous ethical problems. Contractually imposed secrecy about statistical methods, misrepresentation of the results of methods, failure to convey the risks of acting upon statistical results, and breach of researchers’ obligation to report all substantive results obtained from the data are some common ethical problems. Additional challenges confront statisticians whose prime focus is the design and implementation of statistical or methodological research, or the teaching of statistics. Indeed, the ethical problems of the field could become an important concern of the statistical research community.

5. Conclusion and Future Trends in Statistical Research

The role of a statistician is seen as the reduction of the Shannon entropy associated with the distribution of the random variable representing the state of knowledge. The maximum expected utility principle is seen as the most satisfactory method of resolving the selection among such information. Thus, in order that statistics may fulfill in the best possible way its role in the promulgation of progress and best ensure the well-being of the community, the most promising lines for future research are seen first in the development of the subjective Bayes’ interpretation of probability and second in the construction of the incremental knowledge models that are required to make Bayes’ theorem operational, always, where possible, considering the impact of the possibility of monitoring on decision-making.

It is noted that statistics implicitly plays a role in most plans for development and growth. Probabilistic predictions are being used more and more as the complexity and difficulties of modern life defy the capacity of many to make the necessary decisions. It is pointed out that probabilistic forecasts generally have an element of circularity. The type of question asked must have a determinate answer; a probabilistic forecast does not usually supply such an answer. These thoughts lead to the view that the most appropriate role for statistics is described probably by Bayes’ theorem. It is then the purpose of a statistician to provide the information which then will permit decisions to be made.