Difference between correlation and autocorrelation

1. What is difference between correlation and autocorrelation?
2. What is the difference between autocorrelation and Multicollinearity?
3. What is the purpose of autocorrelation?
4. What is the difference between correlation and regression?

What is difference between correlation and autocorrelation?

It's conceptually similar to the correlation between two different time series, but autocorrelation uses the same time series twice: once in its original form and once lagged one or more time periods. For example, if it's rainy today, the data suggests that it's more likely to rain tomorrow than if it's clear today.

What is the difference between autocorrelation and Multicollinearity?

Autocorrelation is used for signals or time series. Autocorrelation is the correlation of the signal with a delayed copy of itself. Multicollinearity, which should be checked during MLR, is a phenomenon in which at least two independent variables are linearly correlated (one can be predicted from the other).

What is the purpose of autocorrelation?

The autocorrelation function is a statistical representation used to analyze the degree of similarity between a time series and a lagged version of itself. This function allows the analyst to compare the current value of a data set to its past value.

What is the difference between correlation and regression?

Correlation is a single statistic, or data point, whereas regression is the entire equation with all of the data points that are represented with a line. Correlation shows the relationship between the two variables, while regression allows us to see how one affects the other.