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Environmental Statistics
Environment statistics is the application of statistical methods to environmental science. It covers procedures for dealing with questions concerning the natural environment in its undisturbed state, the interaction of humanity with the environment, and urban environments. The field of environmental statistics has seen rapid growth in the past few decades as a response to increasing concern over the environment in the public, organizational, and governmental sectors. The United Nations' Framework for the Development of Environment Statistics (FDES) defines the scope of environment statistics as follows: The scope of environment statistics covers biophysical aspects of the environment and those aspects of the socioeconomic system that directly influence and interact with the environment. The scope of environment, social and economic statistics overlap. It is not easy – or necessary – to draw a clear line dividing these areas. Social and economic statistics that describe proces ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Statistics
Statistics (from German language, German: ', "description of a State (polity), state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied. Populations can be diverse groups of people or objects such as "all people living in a country" or "every atom composing a crystal". Statistics deals with every aspect of data, including the planning of data collection in terms of the design of statistical survey, surveys and experimental design, experiments. When census data (comprising every member of the target population) cannot be collected, statisticians collect data by developing specific experiment designs and survey sample (statistics), samples. Representative sampling assures that inferences and conclusions can reasonably extend from the sample ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Environmental Resources
Environment most often refers to: __NOTOC__ * Natural environment, referring respectively to all living and non-living things occurring naturally and the physical and biological factors along with their chemical interactions that affect an organism or a group of organisms Other physical and cultural environments *Ecology, the branch of ethology that deals with the relations of organisms to one another and to their physical surroundings *Environment (systems), the surroundings of a physical system that may interact with the system by exchanging mass, energy, or other properties. *Built environment, constructed surroundings that provide the settings for human activity, ranging from the large-scale civic surroundings to the personal places *Social environment, the culture that an individual lives in, and the people and institutions with whom they interact *Market environment, business term Arts, entertainment and publishing * ''Environment'' (magazine), a peer-reviewed, popular e ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Statistics
Statistics (from German language, German: ', "description of a State (polity), state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied. Populations can be diverse groups of people or objects such as "all people living in a country" or "every atom composing a crystal". Statistics deals with every aspect of data, including the planning of data collection in terms of the design of statistical survey, surveys and experimental design, experiments. When census data (comprising every member of the target population) cannot be collected, statisticians collect data by developing specific experiment designs and survey sample (statistics), samples. Representative sampling assures that inferences and conclusions can reasonably extend from the sample ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Environmental Studies
Environmental studies (EVS or EVST) is a multidisciplinary academic field which systematically studies human behavior, human interaction with the Natural environment, environment. Environmental studies connects principles from the physical sciences, commerce/economics, the humanities, and social sciences to address complex contemporary environmental issues. It is a broad field of study that includes the natural environment, the built environment, and the relationship between them. The field encompasses study in basic principles of ecology and environmental science, as well as associated subjects such as environmental ethics, ethics, environmental geography, geography, anthropology, public policy (environmental policy), education, political science (environmental politics), urban planning, environmental law, law, environmental economics, economics, environmental philosophy, philosophy, environmental sociology, sociology and environmental justice, social justice, environmental pla ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Coordination Of Information On The Environment
Coordination of Information on the Environment (CORINE) is a European programme initiated in 1985 by the European Commission, aimed at gathering information relating to the environment on certain priority topics for the European Union (air, water, soil, land cover, coastal erosion, biotopes, etc.). Since 1994, the European Environment Agency The European Environment Agency (EEA) is the agency of the European Union (EU) which provides independent information on the environment. Definition The European Environment Agency (EEA) is the agency of the European Union (EU) which provides ... (EEA) integrated CORINE in its work programme. EEA is responsible for providing objective, timely and targeted information on Europe's environment. Bibliography *CORINE Biotope Manual, publ. 1992 EU, *CORINE: Examples of the Use of the Programme 1985–1990, publ. 1991 EU, *CORINE: Land Cover Technical Guide, publ. 1994 EU, Search for CORINE literature by the EEA External linksEuropean En ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Non-linear Model
In mathematics, nonlinear modelling is empirical or semi-empirical modelling which takes at least some nonlinearities into account. Nonlinear modelling in practice therefore means modelling of phenomena in which independent variables affecting the system can show complex and synergetic nonlinear effects. Contrary to traditional modelling methods, such as linear regression and basic statistical methods, nonlinear modelling can be utilized efficiently in a vast number of situations where traditional modelling is impractical or impossible. The newer nonlinear modelling approaches include non-parametric methods, such as feedforward neural networks, kernel regression In statistics, kernel regression is a non-parametric technique to estimate the conditional expectation of a random variable. The objective is to find a non-linear relation between a pair of random variables ''X'' and ''Y''. In any nonparametric r ..., multivariate splines, etc., which do not require a ''priori'' knowled ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Generalized Linear Model
In statistics, a generalized linear model (GLM) is a flexible generalization of ordinary linear regression. The GLM generalizes linear regression by allowing the linear model to be related to the response variable via a ''link function'' and by allowing the magnitude of the variance of each measurement to be a function of its predicted value. Generalized linear models were formulated by John Nelder and Robert Wedderburn as a way of unifying various other statistical models, including linear regression, logistic regression and Poisson regression. They proposed an iteratively reweighted least squares method for maximum likelihood estimation (MLE) of the model parameters. MLE remains popular and is the default method on many statistical computing packages. Other approaches, including Bayesian regression and least squares fitting to variance stabilized responses, have been developed. Intuition Ordinary linear regression predicts the expected value of a given unknown quanti ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Linear Regression Model
In statistics, linear regression is a model that estimates the relationship between a scalar response (dependent variable) and one or more explanatory variables (regressor or independent variable). A model with exactly one explanatory variable is a ''simple linear regression''; a model with two or more explanatory variables is a multiple linear regression. This term is distinct from multivariate linear regression, which predicts multiple correlated dependent variables rather than a single dependent variable. In linear regression, the relationships are modeled using linear predictor functions whose unknown model parameters are estimated from the data. Most commonly, the conditional mean of the response given the values of the explanatory variables (or predictors) is assumed to be an affine function of those values; less commonly, the conditional median or some other quantile is used. Like all forms of regression analysis, linear regression focuses on the conditional probabi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Human Population
In world demographics, the world population is the total number of humans currently alive. It was estimated by the United Nations to have exceeded eight billion in mid-November 2022. It took around 300,000 years of human prehistory and history for the human population to reach a billion and only 218 more years to reach 8 billion. The human population has experienced continuous growth following the Great Famine of 1315–1317 and the end of the Black Death in 1350, when it was nearly 370,000,000. The highest global population growth rates, with increases of over 1.8% per year, occurred between 1955 and 1975, peaking at 2.1% between 1965 and 1970. The growth rate declined to 1.1% between 2015 and 2020 and is projected to decline further in the 21st century. The global population is still increasing, but there is significant uncertainty about its long-term trajectory due to changing fertility and mortality rates. The UN Department of Economics and Social Affairs projects ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Inferential Statistics
Statistical inference is the process of using data analysis to infer properties of an underlying probability distribution.Upton, G., Cook, I. (2008) ''Oxford Dictionary of Statistics'', OUP. . Inferential statistical analysis infers properties of a population, for example by testing hypotheses and deriving estimates. It is assumed that the observed data set is sampled from a larger population. Inferential statistics can be contrasted with descriptive statistics. Descriptive statistics is solely concerned with properties of the observed data, and it does not rest on the assumption that the data come from a larger population. In machine learning, the term ''inference'' is sometimes used instead to mean "make a prediction, by evaluating an already trained model"; in this context inferring properties of the model is referred to as ''training'' or ''learning'' (rather than ''inference''), and using a model for prediction is referred to as ''inference'' (instead of ''prediction''); see ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Descriptive Statistics
A descriptive statistic (in the count noun sense) is a summary statistic that quantitatively describes or summarizes features from a collection of information, while descriptive statistics (in the mass noun sense) is the process of using and analysing those statistics. Descriptive statistics is distinguished from inferential statistics (or inductive statistics) by its aim to summarize a sample, rather than use the data to learn about the population that the sample of data is thought to represent. This generally means that descriptive statistics, unlike inferential statistics, is not developed on the basis of probability theory, and are frequently nonparametric statistics. Even when a data analysis draws its main conclusions using inferential statistics, descriptive statistics are generally also presented. For example, in papers reporting on human subjects, typically a table is included giving the overall sample size, sample sizes in important subgroups (e.g., for each treatmen ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
