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A cost centre is a department within a business to which costs can be allocated. The term includes departments which do not produce directly but they incur costs to the business, [1] when the manager and employees of the cost centre are not accountable for the profitability and investment decisions of the business but they are responsible for some of its costs.
Classification of Individual Consumption According to Purpose (COICOP) is a Reference Classification published by the United Nations Statistics Division that divides the purpose of individual consumption expenditures incurred by three institutional sectors, namely households, non-profit institutions serving households, and general government.
An economic taxonomy is a system of classification of economic activity, including products, companies and industries. Some economists believe that the study of economic policy demands the use of a taxonomic/classificatory approach. [1]
An important part of standard cost accounting is a variance analysis, which breaks down the variation between actual cost and standard costs into various components (volume variation, material cost variation, labor cost variation, etc.) so managers can understand why costs were different from what was planned and take appropriate action to ...
In statistics, where classification is often done with logistic regression or a similar procedure, the properties of observations are termed explanatory variables (or independent variables, regressors, etc.), and the categories to be predicted are known as outcomes, which are considered to be possible values of the dependent variable.
A cost object is a term used primarily in cost accounting to describe something to which costs are assigned. [1] Common examples of cost objects are product lines, geographic territories, customers, departments or anything else for which management would like to quantify cost.
In materials management, ABC analysis is an inventory categorisation technique which divides inventory into three categories: 'A' items, with very tight control and accurate records, 'B' items, less tightly controlled and with moderate records, and 'C' items, with the simplest controls possible and minimal records.
The first step in doing a data classification is to cluster the data set used for category training, to create the wanted number of categories. An algorithm, called the classifier, is then used on the categories, creating a descriptive model for each. These models can then be used to categorize new items in the created classification system. [2]