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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 independent variables (often called 'predictors', 'covariates', 'explanatory variables' or 'features').
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For example, if a product needed a sudden change in material or details changed, it can be done in between batches. As opposed to assembly production or mass production where such changes cannot be easily made. [3] The time between batches is called cycle time. [2] Each batch may be assigned a lot number.
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