# Linked Questions

8answers
11k views

### What is meant by a “random variable”?

What do they mean when they say "random variable"?
5answers
16k views

### On the importance of the i.i.d. assumption in statistical learning

In statistical learning, implicitly or explicitly, one always assumes that the training set $\mathcal{D} = \{ \bf {X}, \bf{y} \}$ is composed of $N$ input/response tuples $({\bf{X}}_i,y_i)$ that are ...
5answers
73k views

### Regression when the OLS residuals are not normally distributed

There are several threads on this site discussing how to determine if the OLS residuals are asymptotically normally distributed. Another way to evaluate the normality of the residuals with R code is ...
5answers
26k views

### What exactly is a Bayesian model?

Can I call a model wherein Bayes' Theorem is used a "Bayesian model"? I am afraid such a definition might be too broad. So what exactly is a Bayesian model?
4answers
4k views

### Can anyone clarify the concept of a “sum of random variables”

In my probability class the terms "sums of random variables" is constantly used. However, I'm stuck on what exactly that means? Are we talking about the sum of a bunch of realizations from a random ...
3answers
643 views

### What exactly is a distribution?

I know very little of Probability and Statistics, and am wishing to learn. I see the word "distribution" used all over the place in different contexts. For example, a discrete random variable has a "...
3answers
1k views

### Definition and delimitation of regression model

An embarrassingly simple question -- but it seems it has not been asked on Cross Validated before: What is the definition of a regression model? Also a support question, What is not a regression ...
3answers
3k views

### What's the difference between “classifier” and “model” in classification?

I wonder what the difference between the terms "classifier" and "model" is with relation to classification methodologies for machine learning. Thanks in advance for your answers!
2answers
7k views

### How does OLS regression relate to generalised linear modelling

Can anyone please shed some light on the relationship between OLS and generalised linear model? Has it to do with the distribution of the error terms, general linear model requires normality in the ...
2answers
173 views

### How to determine a 'strong' driver?

I have a set of drivers that are binary and a concept to measure that contains natural numbers between 1-10. I'm currently using Kruskal's key driver analysis to determine the relative contribution ...
1answer
73 views

### Confusion about estimation and prediction

I have a very basic question, consider the following: While learning to predict y from x, we are learning the joint ...
1answer
2k views

### What is meant by using a probability distribution to model the output data for a regression problem?

Often a theoretical text will say something like, 'a probability distribution may be used to model the data' or, 'assume a probability distribution such as normal or Lognormal for the outputs'. ...