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Application of Statistics in the Real World

This article under research studies the aging data in Japan across all generations and genders. It also looks at how the social-economic structure of Japan and how it has played a role in this factor. In order to carry out an efficient and accurate analysis of this topic, statistics were incorporated in the analysis that enabled it to arrive at its conclusions.

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Statistics is a mathematical method of gathering, analyzing and interpreting data. It involves the use of numerical data, statistical, theories, surveys and experiments. Probability and statistics assist modern societies to cope with unexpected issues, for example, this article about Japan’s aging trends. A person using statistics must know the theoretical part of the subject. This will involve formulas, graph drawing and interpretation of the article has information that has been statistically achieved and analyzed.

Variables are elements that are measured, manipulated or controlled when doing research. They are of many types depending on their role in our different studies. They can be correlational, which means they are achieved through relating facts and hence can not be conclusive for example saying that old people are many in Japan and they cannot work hence the change in Japan’s workforce. Research has to be done figures and calculated to confirm that otherwise, it seems right but it could be wrong.

Variables can also be experimental, that is, achieved the outcome through calculations. There are also variables that are independent like in this case the elderly population and dependent meaning that they depend on what happens to the independent e.g. the population of Japan will be affected by the increase or decrease of the old, its workforce, productivity, consumption and overall Japan’s economy.

In this article, most of the variables are experimentally calculated and figures are given. There will always be errors in the calculation but researchers should ensure they are minimal to prevent misleading results. The data collected has enabled us to know that Japan has the highest number of elderly people and how this affects the nation’s productivity and consumption.

There are two types of data qualitative and quantitative. Qualitative is in nominal terms or natural language e.g. small, medium and large, while quantitative data is in numbers representing, measurement percentages, measurements of temperature, etc. In the article more quantitative data has been used than qualitative e.g. 18% decrease in the workforce, a decrease of the population from 127.8 million to 95.2 million by the year 2050, 27.4 25%, etc.

Data collection is a process of preparing and obtaining data, it is a very vital stage of any research study. There are many ways of collection, such as the use of questionnaires, organizing, interviews, focus groups case studies, observation and, portfolios. In this article methods used were interviews, use of questionnaires, headcounts and case studies. The methods used here were headcount and interviews to get the number of the old people and information about them. There were also case studies used to enable them to predict what will happen to Japan and also interviews with people who know more about the economy.

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Sampling is selecting the targeted population for the study; it should be random and unbiased. Sampling is cheap, data collection is fast, accurate and there is the homogeneity of data. Methods to be used can be combined or single and also one has to choose a sample size. Sampling methods can enable us to get either probability samples which means each sample has a chance of being chosen, while in the other non-probability samples there is no assurance that each element will be chosen or has a non-zero chance.

Some of these are simple random sampling where all sets are given equal probability of selection, this minimizes biases and makes analyzes of the data easier. In this case, the population is stratified into strata and each stratum is then sampled scientifically and different elements of each of them are considered and variability is maximum although it is not important if the population has the same characteristics. Systematic sampling involves arranging the population in some order then choosing components, such as every 5th item at regular intervals. However, the method can be very tiring especially where the population is large. Other methods applicable are clustering, use of quota, panel, etc. The method used in this article is systematic since only one stratum of the population is involved. This can be inefficient because there are other strata that have people who can not produce too, for example, the sick and children there are also other factors like energy, political environment, etc.

Inferential methods are forms of propositions e.g. estimates, assumptions and confidence intervals. The result of using this method is that one can come up with simple reasonable solutions. According to the findings, Japan will have problems with its workforce between the years 2000-2050 hence a solution had to be sought. In this article, the researchers were able to propose solutions like a change of retirement age or allow immigrants, estimates of decrease of the workforce by 18% and decrease in consumer population by 8%, etc.

In conclusion, statistics has enabled the world to be ready for uncertainties and plan for the future. People using statistical methods should ensure their data is correct to prevent getting wrong results and hence making bad decisions. People should also not misuse statistical knowledge like in the past studies done on the same topic contradicted causing doubts on how correct is the information.

Works Cited

Htakea, Fumio & Atio, Makotos. Population Aging And Consumption in Japan. Review Of Income and Wealth. Vol. 44 (3). 1998. Print.

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