1. H

    Meaning of bootstrapping residuals

    What does it physically mean when I bootstrap residuals in a regression problem. Like when I bootstrap residuals and create synthetic data does it mean I am hypothetically doing some experiments(virtual experiments which are represented by synthetic data). Or does it mean I am just randomly...
  2. N

    ANOVA, residual normality assumptions

    Hi everybody, I would like to ask you something about the normality hypotesis on the residuals when performing an ANOVA. Do I have to check the entire residuals data set or, do I have to check normality of the residuals relative to each level of each IV (for example, 1 IV with 3 levels, 3...
  3. R

    What to do with very low Durbin-Watson?

    For 100 companies, I have collected (i) `tweets` and (ii) corporate website `pageviews` for `148` days. The tweetvolume and pageviews per day are two independent variables corpaired against the stock `trading volume` for each company, resulting in 100 x 148 = 14,800 observations. My data is...
  4. E

    Test whether assumptions for cluster estimator of VCE are fulfilled

    Dear all, I am running a regression on a dataset which I think shows correlation between observations of a cluster. Therefore I use the cluster-robust-VCE estimator by adding -cluster(group)- to the regression command. As this estimator requires the disturbances between groups to be...
  5. J

    confusion on terminology

    I could use some confirmation or correction on something basic that has been confusing me for a while. It has to do with "normal" and steps in modeling. Normality is for residuals (people already helped me with this in a previous thread) and this comes after fitting a model. In the beginning of...
  6. P

    evaluating loess fit

    Hello Everyone, I am trying to evaluate the fits of data using loess() in R. I cannot seem to find any established methods for determining the quality of a loess fit. I have been using the median absolute deviation of the residuals as an estimate of the "goodness of fit" and the amount of...
  7. K

    Residuals v.s errors

    What is the difference between a residual and an error? Is it wrong to say an error is the difference between the data points and a fitted line while a residual is the difference between data points and the sample mean.Please help!!
  8. K

    Assumptions that underlie a regresion model

    Are there any statistical tests that i can use to evaluate whether the assumptions for the regression model are being met? The assumptions i want to test are: 1. The model adequately describes the behaviour of the data. 2. The random error term is an independently and normally...
  9. L

    Prediction Errors

    Given a regression output of: Budget = 1.76 + 0.20 = Lawmakers S = 4.20 R-Sq = 10.7% (There is also a scatter plot that I obviously cannot post but I'm not sure if it's needed for this...) I'm being asked what the typical size of prediction errors is. I will admit that I'm finding...