Statistics - Explanation and definition of statistics

What is statistics

Statistic is defined as the science that deals with the collection, organization, processing, presentation and analysis of the information both quantitative and qualitative, in order to make predictions and draw conclusions that help us to take correct decision applied in a wide range of areas and sectors such as economic, social, demographic, health, scientific and industrial...

Often information alone is incomplete not giving us any useful value, when we are presented with a large number of raw data the human mind is incapable of assimilating so we need to summarize or reduce them to understand, you need to treat and manage information right way to organize and find the possible relationships to help us draw conclusions, statistics gives us a set of methodologies, techniques and tools that help us achieve this goal.

Statistics is the science that studies and analyzes qualitative and quantitative data, commonly are used to link the numbers with statistics, but also deals with qualitative or descriptive data as text or symbols. Furthermore this science is composed of two disciplines or branches known as descriptive statistics and inferential statistics.

Descriptive statistics provides methodologies and tools for the collection, organization and presentation of data that representing a system. Tools such as frequency tables, bar charts, histograms, pie charts or diagrams that help us to find and visualize the information, also the calculation of indicative parameters as mean, deviation or variance that gives us summary information of all analyzed data aredeveloped by descriptive statistics.

Inferential statistics provides methodologies and tools necessary to understand and predict the behavior of a system from a number of partial and representative data samples. Techniques and methodologies as models of simple and multiple linear regression, correlation coefficients, sampling techniques or hypothesis tests are specific from inferential statistics.

Descriptive statistics describes and summarizes the system while the inferential statistics model and predicts the behavior of the system relying on probability. Censuses in a particular city, the numbers of patients attending a hospital over a period of time or number of cars driving on a certain freeway are calculated and represented by the use of techniques and tools developed by the descriptive statistics, on the other side surveys on voting intentions, the relationship between nicotine and life expectancy or forecasts sale of a particular product are calculated by using inferential statistics.

Thanks to advances in information technology and computers today we have specific software that help us statistical calculations, this type of software allows us to handle a large volume of information and apply a wide range of statistical techniques to obtain information useful with high accuracy and in a short space of time, on the other hand this type of software facilitates the preparation of statistical tables and graphs that help us to visualize and comprehend information from elegant and professional manner.

History of statistics

From the origins of our species humans beings have needed to account for and organize the resources available in order to manage them, in prehistory our ancestors used written symbols and painted leather pieces, rocks, tables and walls of caves to accounting people, animals, agricultural products, metals or anything else that needed to account for and manage.

Ancient civilizations like the Egyptian, Babylonian, Chinese, Greek or the Roman Empire through the work of its officials and scribes kept records and census of the population that lived in their regions as well as tax records and wealth that they possessed.

The basis of the current statistics were developed in the seventeenth century by the merchant English John Graunt, he developed the first mortality tables assigning probabilities of survival by age and an analysis and conclusions of the origins and causes of death, making the first demographic study based on deaths.

During the same seventeenth century through studies of mathematicians and scientists of the stature of Christiaan Huygens, Jakob Bernoulli, Blaise Pascal and Pierre de Fermat developed breakthroughs in the field of mathematical probability, being one of the basic branches in which supports inferential statistics, later in the eighteenth century figures such as Abraham de Moivre, Thomas Bayer, Joseph Louis Lagrange and Pierre Simon Laplace laid the foundations of probability theory.

In the early nineteenth century William Playfair introduced bar charts, sector, linear and circular as a means of representation of economic and demographic data, on the other hand Carl Friedrich Gauss developed his famous campaign shaped curve and the method of least squares, Francis Galton invented the use of the regression line and develops the concept of correlation coefficients, at the end of the century Karl Pearson introduced the concept of standard deviation and the famous Chi-square starting bases inferential statistics.

In the twentieth century, Ronald Aylmer Fisher develops statistical inference techniques by introducing analysis of variance (ANOVA) and covariance (ANCOVA), the maximum likelihood method and introducing the concepts of consistency, efficiency, credibility, accuracy and validation. John Wilder Turkey develops box plots, while Bradley Efron develops the bootstrap methodology.

During this century the statistics find in computers the perfect way for implementing their methodologies and techniques for large data volumes, thanks to these techniques develops data mining methodologies and Big data that allow us to look for patterns and extract useful information from sets large of data apparently not related.

Applications of statistics

In today's world the decision process is becoming more complicated by the degree of complexity and difficulty to manage the large volume of information that we handle daily, on the other hand we all know that information is power and correct treatment and analysis of information gives us decisive advantages over our competitors, these are the main reasons why NGOs, military, scientific, prestigious industries as well as large corporations around the world use techniques and statistical methods help them reach their goals and improve it.

Currently statistical theories and methodologies developed over time are used in a wide range of sectors such as health, sociological, economic, scientific, educational, military... These sectors successfully applied statistical methods that helped to improve and solve problems those who face daily.

One of the most statistical applications used to governments and companies around the world is econometrics, econometrics is the economy science that relying on mathematical and statistical models analyzes and studies economic models in order to understand and predict their future behavior, as well then use this knowledge to predict the sales volume of a particular product, to quantify the effect of advertising on future benefits, know the future values of certain shares on the stock, predicting economic growth of a country or validate macroeconomic theories.

In the industry sector statistics is widely used as tools for quality control and process improvement as well as reducing consumption of raw materials, control charts where it monitors and analyzes the behavior of certain processes coming to predict when can occur failure, process capability index which indicates whether a process is stable and reliable, Pareto charts, histograms, scatter diagrams, six sigma methodology... These and other statistical tools are present in many different industries such as pharmaceutical, automotive or food.

In the health sector statistics is widely used to detect and understand the origins of an epidemic and predict their evolution, validate the use of new drugs for the treatment of diseases, study and analyze how genetic variations influence our quality of life or understand how chronic diseases.

The psychology and sociology use statistical techniques to predict the behavior of humans and populations, for example by statistical techniques analyze whether tougher penalties has implications for crime rate, the degree of effectiveness that have analyzed policy measures and announcements against alcohol and snuff or the degree of stress that people are exposed to certain trades, on the other hand statistics help to develop different kinds of test both intelligence and personality.

Scientific, military, governors, managers, doctors, athletes ... Millions of sectors and professionals around the world use the tools offered by statistics to improve their daily decisions improving and optimizing the results of their work.

Now that you know what the statistics, did you know that scientists had finally validated the discovery of the Higgs particle when experiments developed on the accelerator LHC had a statistical confidence level of 5 sigma?

If you like, share it