Yahoo Web Search

Search results

  1. 4 days ago · The proposed method generalizes the desirable uniform convergence property of ordinary least squares to the M-estimation. Meanwhile, it is a general approach that allows any $$\sqrt{n}$$ -consistent coefficient parameter estimators to be applied in the procedure to make global inferences for the link function.

  2. 5 days ago · Instead of fitting separate models for each predictor, we can include multiple predictors in the same model. When more than one predictor is used, the procedure is called multiple linear regression. Recall the unknown, or true, linear regression model with one predictor: This equation describes how the mean of Y changes for given values of X.

  3. 4 days ago · The Chi-square test of independence checks whether two variables are likely to be related or not. We have counts for two categorical or nominal variables. We also have an idea that the two variables are not related. The test gives us a way to decide if our idea is plausible or not. The sections below discuss what we need for the test, how to do ...

  4. 4 days ago · These are referred to as high leverage observations. The fact that an observation is an outlier or has high leverage is not necessarily a problem in regression. But some outliers or high leverage observations exert influence on the fitted regression model, biasing our model estimates. Take, for example, a simple scenario with one severe outlier.

  5. 1 day ago · Many statistical methods depend on the data being normally distributed. In this case, you will read that the method “assumes data is normally distributed” or “assumes normality.” One of your first actions for a set of data values should be to look at the shape of the data. The normal distribution has a symmetrical shape.

  6. 5 days ago · Many statistical methods depend on the data being normally distributed. In this case, you will read that the method “assumes data is normally distributed” or “assumes normality.” One of your first actions for a set of data values should be to look at the shape of the data. The normal distribution has a symmetrical shape.