Econometrics Questions
Explore questions in the Econometrics category that you can ask Spark.E!
Prediction the value of one variable from another.
You are in the head of line and there are three clerks each dealing with customer. What is the probability that of the three customers currently being served and yourself, you are the last one to finish buying a ticket?
The training error decreases for smoothing splines as the tuning parameter lambda increases
Shrinkage and Dimension Reduction are both methods with dealing with the problem of large bias that occurs in high dimensions
The mean function for white noise is zero
Which of the following pairs of distribution and link function is most appropriate to model if a person is hospitalized or notA. Normal Dist, Identity LinkB. Normal Dist, Logit LinkC. Binom Dist, Linear LinkD. Binom Dist, Logit Link
For a data set containing one million observations, two models are tested. The models are nested, and the model with the fewest variables, model 1, has the smaller BIC, the larger AIC, the smaller R^2 and the larger adjusted R^2.On the basis of adjusted R^2, select model 1.
AR(3) Process: Partial autocorrelation for lag 5 is always greater than zero
For every time series, the acf at lag 0 is exactly 1
AR(3) Process: Partial autocorrelation for lag three is always equal to zero
Modeling Obstacles not treated by GLM: Modeling a non-linear relationship between the response mean and the predictors
An acf that decays exponentially in height is characteristic of an autoregressive series
For a large enough degree d, polynomial regression can produce an extremely flexible curve
The weights for the Partial Least Squares score arise from the slopes of the single variable regressions of y onto each explanatory variable
An acf with spike at lag k may indicate a repeating pattern of length k
Modeling Obstacles not treated by GLM: Modeling a discrete response distribution in terms of a explanatory variable with a continuous distribution
Estimating a value outside the range of measured data.
To test a GLM with polynomial explanatory terms, only accept the model if both Type 1 and Type III Tests agree
Regression works poorly in high dimensions because not all of the predictors are actually associated with the response
Generalized Additive Models are sometimes referred to as parametric because no response distribution is assumed