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Also agriscience or ag science, and often pluralized as in agricultural sciences. The application of scientific methods to agriculture , or the study of agriculture as a scientific discipline. It is a multidisciplinary field encompassing all elements of the natural, economic, and social sciences which are used in the practice and understanding ...
Good agricultural practice (GAP) is a certification system for agriculture, specifying procedures (and attendant documentation) that must be implemented to create food for consumers or further processing that is safe and wholesome, using sustainable methods. While there are numerous competing definitions of what methods constitute good ...
Outcomes can involve, for example, a guaranteed supply level, price stability, product quality, product selection, land use or employment. Governments can use tools like rural development practices , agricultural extension , economic protections , agricultural subsidies or price controls to change the dynamics of agricultural production, or ...
S.M.A.R.T. (or SMART) is an acronym used as a mnemonic device to establish criteria for effective goal-setting and objective development. This framework is commonly applied in various fields, including project management, employee performance management, and personal development.
The economic and environmental benefits of precision agriculture have also been confirmed in China, but China is lagging behind countries such as Europe and the United States because the Chinese agricultural system is characterized by small-scale family-run farms, which makes the adoption rate of precision agriculture lower than other countries.
Such measures can be used in statistical hypothesis testing, e.g. to test for normality of residuals, to test whether two samples are drawn from identical distributions (see Kolmogorov–Smirnov test), or whether outcome frequencies follow a specified distribution (see Pearson's chi-square test).
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Robust measures of scale can be used as estimators of properties of the population, either for parameter estimation or as estimators of their own expected value.. For example, robust estimators of scale are used to estimate the population standard deviation, generally by multiplying by a scale factor to make it an unbiased consistent estimator; see scale parameter: estimation.