What is autocorrelation?

Autocorrelation usually occurs in a set of data in which the patterns are repeated. The values ​​of similar variables, such as revenue or economic data, are often correlated. Scientists may also come across an autocorelence. It often appears in studies of economics, scientific experiments involving signal processing, as well as in optics and recording music. This phenomenon, usually described in conjunction with the time series, includes several patterns that scientists use to analyze or group data.

There is usually synchronization between the two variables for autocorrelation. An example is whether one person's income will change and at the same time this cash flow can change how another person or group spend during this period. Data can also be autocorrected if the strike of the company or trade union reduces work production at the same time and the trend continues to another measured time frame. Partial autocorrelation is sometimes possible; if data correlate over time, there may be a delay,If the data is correlated. Serial autocorrelation is usually when there is a delay between different data in the time series.

patterns that often occur with autocorrelation may be represented by the patterns of curves on the graph. These curves can be used to reflect the trend; This sometimes includes up and down patterns that may occur in cycles. Calculation errors may also cause correlation of data correlation, such as the newcomer uses incorrect values ​​or variables. The use of extrapolation and interpolation of data sometimes correlates, and does not do the variables separate in relation to time.

Autocorrelation may have a positive value, especially if the trend in the pattern moves up. Trends down often reflect the negative value. Such patterns are often analyzed in economics, but they can also prove signal pulses, electromagnetic fields and also in various statistics applications. This phenomenon withE often uses in such diverse applications as atomic measurement as well as studying the distribution of galaxies in space.

Autocorrelation detection is usually performed using the Durbin Watson test. The statistics are mathematically measured and whether the value above or below the value of another variable usually determines the result. Scientists can then determine cleanliness, and if this characteristic is found, the data file is often returned to its original form to remove the phenomenon if possible.