Statistics is the field of applied mathematics that involves the collection, analysis, explanation, and presentation of data. Statistics is applied in many fields that include natural sciences, humanities, business, social sciences, and government. Modern statistics involves the quantification of the social, scientific, and biological phenomenon, design and analysis of surveys and experiments especially in biological sciences, market research, economics, and management.
In society, the principles of statistics are used in helping people have a better understanding of the world they are living in. By being able to evaluate data properly, people are able to reason and react intelligently to the information presented to them. In principle, statistics help society to take control of the world and the environment surrounding it.
The general perception among the majority of people is that statistics can be manipulated to suit the need of the author. This makes it hard for people to trust statistics. According to a noted Harvard researcher, Dr. Robert Blendon, over 70% of the population don’t trust statistics. In marketing for example, whenever marketers are selling a product, they only present statistics that show that their products are the best. Any statistics showing that people don’t like the product are never presented to the public.
Another reason why people don’t trust statistics is the fact that they can be misleading. If a person carrying out a survey is not careful when defining and applying a specific rating scheme, for example, health care, the consumer is likely to form an inappropriate negative perception about the product. The fact that measures are drawn from samples of population leads to sampling error. This error makes statistics to be misleading hence people tend to have low trust in statistics.
Lack of understanding of statistical concepts by the majority of people plays a significant role that leads to mistrust of statistics by people. Most statistics are presented in complicated graphs that lack accuracy and tend to lose comprehension. Many people are not able to interpret charts and graphs as they lack basic knowledge of statistics. When people are not able to grasp the information communicated by statistics easily, they tend to lose trust in the data.
Descriptive statistics are used in describing basic features of the data in a specific study in a simple way. These statistics provide simple summaries that can be understood easily about samples and measures. This coupled with simple graphic analysis, helps to form the basis of practically every quantitative analysis of the data. Data presented in descriptive statistics are easily managed. A research study involving large measures and data is simplified by the use of descriptive statistics in a reasonable way. A lot of data is summarized in a simpler way in each descriptive statistic. However, descriptive statistics leads to distortion of the original data as one attempts to describe a large set of observations with one simple indicator. At the same time, a lot of data and important details are lost.
Inferential statistics are used to draw a conclusion that extends beyond the data presented. As opposed to descriptive statistics which is relatively simple, inferential statistics is more complex. Inferential statistics makes use of hypothesis testing, prediction, point estimation, and interval estimation method. Depending on the intention of the author of the statistics, inferential statistics can be very misleading especially when poor tests are done coupled with usual statistical abuses.
Statistics is an independent field of mathematics that involves the collection, analysis, explanation, and presentation of data. Through the use of statistics, people have a better understanding of their lives and the world they are living in. However, many people do not trust statistics as they feel that the data presented in them can be easily manipulated to suit the need of the author. People tend to shy away from statistics as they are in most cases presented in complicated graphs and charts which lack accuracy.