business statistics

posted by .

When autocorrelation of the residuals is present, what effect can this have on interval estimation and significance tests regarding the regression model involved?

  • business statistics -

    Most significance tests and interval estimation methods assume randomly sampled observations.

    The presence of autocorrelation in the data means that the observations are not random, but correlated to previous values, typical of time-series related data.

    This phenomenon results in null hypotheses indicating the absence of relationships are frequently rejected, for the wrong reason. The presence of an apparent correlation also narrows the estimation intervals and confidence intervals, resulting in a false sense of accuracy of the model.

    The statistical test for autocorrelation, the Durbin-Watson test is designed to indicate the presence or absence of autocorrelation. The statistic ranges from 0 (positive autocorrelation) to 4 (negative), 2 meaning absence of autocorrelation.

  • business statistics -

    Hi, MathMate, thank you for your help.
    God bless you

Respond to this Question

First Name
School Subject
Your Answer

Similar Questions

  1. statistics

    Which of the following is not a consideration in determining the goodness of fit of a model?
  2. Economics

    In a regression analysis, suppose there is, in fact, no seasonal pattern to sales, and the trend line is estimated using dummy variables to account for seasonality. What effect would this have on the estimation?
  3. Statistics !

    Hi I have calculated some statistics using a spreadsheet program and I have to compare three slopes of regression and their significance level in an energy species hypothesis.. -2.11 level of significance is 5% -4.73 level of significance …
  4. statistics

    A regression model has 2 independent variables and 16 observations, and the calculated Durbin-Watson d statistic is 2.78. What, if any, conclusion will be reached in testing for autocorrelation of the residuals with a: a. two-tail …
  5. Stats

    Instructions for Data Sets: In each data set, the dependent variable (response) is the first variable. Choose the independent variables (predictors) as you judge appropriate. Use a spreadsheet or a statistical package (e.g., MegaStat …
  6. multiple regression

    5. HR Assistant Survey A sample of HR assistants in Plano Texas was created. It was suggested that the data should be analyzed with a regression model to determine if salary was related to years of experience, aptitude test scores, …
  7. statistics

    Linear Regression In the babies.dta full dataset, generate a covariate called painind defined as 1 if the infant experienced severe pain upon receiving the shot (pain0 = 7) and as 0 otherwise. In Stata, you can use the commands: generate …
  8. Business Stats

    Regression Analysis: Avg. Tot. Score versus %Takers, T/S Ratio Model Summary S R-sq R-sq(adj) R-sq(pred) 34.2385 79.91% 79.06% 76.83% Coefficients Term Coef SE Coef T-Value P-Value VIF Constant 1118.5 39.5 28.34 0.000 %Takers -2.547 …
  9. Calculus

    I am working on a regression model , if my residuals don't exceed 0.6 does that mean this model is OK for my data?
  10. Calculus

    I am working on a regression model , if my residuals don't exceed 0.6 does that mean this model is OK for my data?

More Similar Questions