Load factor may refer to: *

Load factor (aeronautics) In aeronautics, the load factor is the ratio of the lift of an aircraft to its weightHurt, page 37 and represents a global measure of the stress ("load") to which the structure of the aircraft is subjected: : n = \frac, where : n is the load fact ...

, the ratio of the lift of an aircraft to its weight * Load factor (computer science), the ratio of the number of records to the number of addresses within a data structure * Load factor (electrical), the average power divided by the peak power over a period of time *

Capacity factor The net capacity factor is the unitless ratio of actual electrical energy output over a given period of time to the theoretical maximum electrical energy output over that period. The theoretical maximum energy output of a given installation is def ...

, the ratio of actual energy output to the theoretical maximum possible in a

power station A power station, also referred to as a power plant and sometimes generating station or generating plant, is an industrial facility for the generation of electric power. Power stations are generally connected to an electrical grid. Many p ...

Passenger load factor Passenger load factor, or load factor, measures the capacity utilization of public transport services like airlines, passenger railways, and intercity bus services. It is generally used to assess how efficiently a transport provider fills seats a ...

, the ratio of revenue passenger miles to available seat miles of a particular transportation operation (e.g. a flight) * Factor loadings in statistics, the exposure to specific factors or components in

Factor Analysis Factor analysis is a statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved variables called factors. For example, it is possible that variations in six observed ...

Principal Component Analysis Principal component analysis (PCA) is a popular technique for analyzing large datasets containing a high number of dimensions/features per observation, increasing the interpretability of data while preserving the maximum amount of information, and ...

See also