Statistics are very helpful for evaluating information about the environment because they provide a quantitative way to measure and compare environmental conditions. Statistics can be used to analyze trends in environmental data over time, identify correlations between environmental variables, and assess the impacts of environmental policies. Statistics can also be used to compare environmental conditions in different regions or countries. In addition, statistics can be used to create predictive models that can help inform environmental decision-making.

## Environmental statistics

Application of statistical methods to environmental science

Environmental statistics is the application of Statistical methods for environmental science. Covers procedures for dealing with issues relating to natural environment in its undisturbed state, humanity’s interaction with the environment and urban environments. The field of environmental statistics has seen rapid growth in recent decades as a response to growing concern for the environment in the public, organizational and government sectors.

The United NationsThe Framework for the Development of Environmental Statistics (FDES) defines the scope of environmental statistics as follows: The scope of environmental statistics encompasses the biophysical aspects of the environment and those aspects of the socio-economic system that directly influence and interact with the environment. The scope of environmental, social and economic statistics overlap. It is not easy – nor necessary – to draw a clear line dividing these areas. Social and economic statistics that describe processes or activities that have a direct impact or direct interaction with the environment are widely used in environmental statistics. They are within the scope of the FDES.

## Uses

Statistical analysis is essential to the field of environmental sciences, allowing researchers to gain an understanding of environmental issues through researching and developing possible solutions to the problems they study. Applications of statistical methods to the environmental sciences are numerous and varied. Environmental statistics are used in many fields including; health and safety organizations, regulatory bodies, research institutes, water and river authorities, meteorological organizations, fisheries, protection agencies and in matters of risk, pollution, regulation and control.

Environmental statistics are especially pertinent and widely used in the academic, government, regulatory, technology, and consulting industries.

Specific applications of statistical analysis in the field of environmental science include earthquake risk analysis, environmental policy making, ecological sampling planning, environmental forensics.

Within the scope of environmental statistics, there are two main categories of their uses.

The types of studies covered by environmental statistics include:

• Baseline studies to document the current state of an environment to provide information in case of unknown changes in the future;
• Studies aimed at describing the likely impact of planned changes or accidental occurrences;
• Regular monitoring to try to detect changes in the environment.

## Sources

Data sources for environmental statistics are varied and include surveys relating to human populations and the environment, records from agencies that manage environmental resources, maps and images, equipment used to examine the environment, and research studies around the world. . A primary component of the data is direct observation, although most environmental statistics use a variety of sources.

## Methods

Statistical analysis methods in environmental science are as numerous as their applications. While there is a foundation for methods used in other areas, many of these methods must be adapted to meet the needs or limitations of data in environmental science. Linear regression models, generalized linear modelsand non-linear models are some methods of statistical analysis widely used in the environmental sciences to study the relationships between variables.

## References

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