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Statistics, in the modern sense of the word, began evolving in the 18th century in response to the novel needs of industrializing sovereign states. In early times, the meaning was restricted to information about states, particularly demographics such as population. This was later extended to include all collections of information of all types ...
Statistics (from German: Statistik, orig. "description of a state, a country") [1][2] is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. [3][4][5] In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a ...
Statistics educators have cognitive and noncognitive goals for students. For example, former American Statistical Association (ASA) President Katherine Wallman defined statistical literacy as including the cognitive abilities of understanding and critically evaluating statistical results as well as appreciating the contributions statistical thinking can make.
Statistical literacy is the ability to understand and reason with statistics and data. The abilities to understand and reason with data, or arguments that use data, are necessary for citizens to understand material presented in publications such as newspapers, television, and the Internet. However, scientists also need to develop statistical ...
Environmental statistics is the application of statistical methods to environmental science. Weather, climate, air and water quality are included, as are studies of plant and animal populations. Epidemiology is the study of factors affecting the health and illness of populations, and serves as the foundation and logic of interventions made in ...
Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. [1] Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science ...
Data science is "a concept to unify statistics, data analysis, informatics, and their related methods " to "understand and analyze actual phenomena " with data. [5] It uses techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, information science, and domain knowledge. [6]
The foundations of statistics are the mathematical and philosophical bases for statistical methods. These bases are theoretical frameworks that ground and justify methods of statistical inference, estimation, hypothesis testing, uncertainty quantification, and the interpretation of statistical conclusions. Further, a foundation can be used to ...