DEFINITION of 'Random Factor Analysis'

Random factor analysis is a statistical analysis technique used to determine the origin of random data in a data collection. Random factor analysis is used to decipher whether the outlying data is caused by an underlying trend or just simply random occurring events and attempts to explain the apparently random data. It uses multiple variables to more accurately interpret the data.

BREAKING DOWN 'Random Factor Analysis'

Random factor analysis is commonly used to help companies better focus their plans on potential or actual problems. If the random data is caused by an underlying trend or random recurring event, that trend will need to be addressed and remedied accordingly. For example, consider a random event such as a volcano eruption. Sales of breathing masks may skyrocket, and if someone were to just look at the sales data over a multi-year period this would look like an outlier, but the analysis would attribute this data to this random event.

In Analysis of Variance, a popular statistical technique, and several other methodologies, there are two types of factors: fixed effects and random effects. Which type is appropriate depends on the context of the problem, the questions of interest and how the data is gathered.

With a fixed effect factor, data has been gathered from all the levels of the factor that is of interest.

For instance, the purpose of an experiment is to compare the effects of three specific dosages of a drug on the response. "Dosage" is the factor; the three specific dosages in the experiment are the levels; there is no intent to say anything about other dosages.

A random effect factor then includes a factor with many possible levels. Interest is at all possible levels, but only a random sample of levels is included in the data.

For example, a large manufacturer of widgets is interested in studying the effect of a machine operator on the quality of a final product. The researcher selects a random sample of operators from the large number of operators at the various facilities that manufacture the widgets. The factor is "operator." The analysis will not estimate the effect of each of the operators in the sample, but will instead estimate the variability attributable to the factor "operator."

  1. Random Walk Index

    Random Walk Index compares a security’s price movements to a ...
  2. Simple Random Sample

    A simple random sample is a subset of a statistical population ...
  3. Data Smoothing

    The use of an algorithm to remove noise from a data set, allowing ...
  4. Random Walk Theory

    The random walk theory is the idea that stocks take a random ...
  5. Quality Control Chart

    A quality control chart is a graphic that depicts whether sampled ...
  6. Weak Form Efficiency

    Weak form efficiency is one of the degrees of efficient market ...
Related Articles
  1. Trading

    Financial Markets: Random, Cyclical or Both?

    Are the markets random or cyclical? Depends on whom you ask. We look at both sides of the argument.
  2. Investing

    What Are The Odds Of Scoring A Winning Trade?

    Just because you're on a winning streak doesn't mean you're a skilled trader. Find out why.
  3. Investing

    Introduction To Stationary And Non-Stationary Processes

    What to know about stationary and non-stationary processes before you try to model or forecast.
  4. Investing

    Most Common Probability Distributions

    In this article, we'll go over a few of the most popular probability distributions and show you how to calculate them.
  5. Trading

    4 ways to predict market performance

    Learn about four different views of the market and future pricing, including supporting academic research.
  6. Trading

    Losing To Win

    Adopting realistic expectations is essential to staying in the trading game.
  7. Insights

    What Is Market Efficiency?

    The efficient market hypothesis (EMH) suggests that stock prices fully reflect all available information in the market. Is this possible?
  1. What's an example of stratified random sampling?

    Stratified random sampling divides a population into subgroups or strata, whereby the members in each of the stratum formed ... Read Answer >>
  2. What are the pros and cons of stratified random sampling?

    Stratified random sampling provides a more accurate sampling of a population, but can be disadvantageous when researchers ... Read Answer >>
  3. What are the advantages and disadvantages of using systematic sampling?

    Learn about the primary advantages and disadvantages of using a systematic sampling method when conducting research of a ... Read Answer >>
Trading Center