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The difference between multicollinearity and auto correlation is that multicollinearity is a linear relationship between 2 or more explanatory variables in a multiple regression while while auto-correlation is a type of correlation between values of a process at different points in time, as a function of the two times or of the time difference.
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Can A correlation matrix can be used to assess multicollinearity between independent variables?
yes
What is multi collinearity?
Multicollinearity is the condition occurring when two or more of the independent variables in a regression equation are correlated.
Consequences of autocorrelation?
The answer will depend on the level of statistical knowledge that you have and, unfortunately, we do not know that. The regression model is based on the assumption that the residuals [or errors] are independent and this is not true if autocorrelation is present. A simple solution is to use moving averages (MA). Other models, such as the autoregressive model (AR) or autoregressive integrated moving average model (ARIMA) can be used. Statistical software packages will include tests for the existence of autocorrelation and also applying one or more of these models to the data.
What is difference between as on and as at?
difference between as on and as at
What is durbin-Watson?
Durbin-Watson is a statistic that is used in regression analysis. Its main goal is to notate autocorrelation presences in prediction errors.
