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Passive income is a type of unearned income that is acquired with little to no labor to earn or maintain. It is often combined with another source of income, such as regular employment or a side job. [1] . Passive income, as an acquired income, is taxable.
The most direct of the three is the production approach, which sums up the outputs of every class of enterprise to arrive at the total. The expenditure approach works on the principle that all of the products must be bought by somebody, therefore the value of the total product must be equal to people's total expenditures in buying things.
American retail corporation Walmart has been the world's largest company by revenue since 2014. [1] . The list is limited to the largest 50 companies, all of which have annual revenues exceeding US$130 billion. This list is incomplete, as not all companies disclose their information to the media or general public. [3] .
5S (Five S) is a workplace organization method that uses a list of five Japanese words: seiri (整理), seiton (整頓), seisō (清掃), seiketsu (清潔), and shitsuke (躾). These have been translated [by whom?] as 'sort', 'set in order', 'shine', 'standardize', and 'sustain'. [1] .
The Gini coefficient was developed by the Italian statistician Corrado Gini and published in his 1912 paper Variabilità e mutabilità (English: variability and mutability).[17] [18] Building on the work of American economist Max Lorenz, Gini proposed that the difference between the hypothetical straight line depicting perfect equality, and the actual line depicting people's incomes, be used ...
Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems.It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. [1]
In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships between a dependent variable (often called the outcome or response variable, or a label in machine learning parlance) and one or more error-free independent variables (often called regressors, predictors, covariates, explanatory ...
