Variable-interval schedule (VI) is a reinforcement schedule in which reinforcement is provided for the first response that occurs after a variable amount of time from the last reinforcer or the start of the trial interval.
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Two way ANOVA
It can be though more often it is a variable on the interval scale (when looking for trends over time).
When, over a given range, the probability that a variable in question lies within a particulat interval is equal to the size of that interval as a proportion of the range.
This statement means that you need to justify the choice of your selection. For example, if you choose a specific type of variable i.e., nominal, interval, etc. You need to show proof as to how you can statistically justify why you choose this particular variable. How can you justify the outcome of this type of variable chosen.
In the simplest setting, a continuous random variable is one that can assume any value on some interval of the real numbers. For example, a uniform random variable is often defined on the unit interval [0,1], which means that this random variable could assume any value between 0 and 1, including 0 and 1. Some possibilities would be 1/3, 0.3214, pi/4, e/5, and so on ... in other words, any of the numbers in that interval. As another example, a normal random variable can assume any value between -infinity and +infinity (another interval). Most of these values would be extremely unlikely to occur but they would be possible. The random variable could assume values of 3, -10000, pi, 1000*pi, e*e, ... any possible value in the real numbers. It is also possible to define continue random variables that assume values on the entire (x,y) plane, or just on the circumference of a circle, or anywhere that you can imagine that is essentially equivalent (in some sense) to pieces of a real line.