Search results
Having independent and identically distributed (IID) data is a common assumption for statistical procedures and hypothesis tests. But what does that mouthful of words actually mean? That’s the topic of this post! And, I’ll provide helpful tips for determining whether your data are IID.
An IID random variable or sequence is an important component of a statistical or machine models, also playing a role in time series analysis. In this post, in an intuitive way, I explain the concept of IID in three different contexts,: sampling, modelling, and predictability. IID in Sampling.
I am trying to understand the difference between iid and non-iid data. Let's consider a given time series, and say it's reasonable to assume that at each time point the random variable $X_t$ depends on $X_{t-1}$. Now say someone gives me the dataset $ D = \{ ( t_i, x_i ) \} $ for $i=1 \dots n$.
Got IID Data? Assessing the IID Assumption. We'll consider two scenarios: I. Simple random sampling of a population. II. Sequential Sampling of a process. I. Simple random sampling.
“This is a well-written, well-organized guide to the practice of database administration. Unlike other books on general database theory or relational database theory, this book focuses more directly on the theory and reality of database administration as practiced by database profes sionals today, and
Database systems: Volume 1 D. Lewis CO2209 2016 Undergraduate study in Computing and related programmes This is an extract from a subject guide for an undergraduate course offered as part of the
The definition extends naturally to more than two random variables. We say that random variables are i.i.d. if they are independent (see further Independence (probability theory) § More than two random variables) and identically distributed, i.e. if and only if. EQUATION.
