# What does it mean "analyze sample time series data when only a single series is available"?

Since the book says, it will use time series to mean either realization of a process or a process, I have no idea how to interpret the following sentence.

"This notion, called weak stationary(i.e.autocovariance is independent of time but only depends upon time separation of variable), when the mean is constant, is fundamental in allowing us to analyze sample time series data when only one series is available."

1. How do I analyze the data if only one series is given? In particular, it could mean one stochastic process which makes sense. However for a specific realization say $$(x_{t_i})$$ is measured data points at $$t_1, I do not see it makes sense to me. There is no distribution associated to say $$x_{t_1}$$ as I have only one point. I guess the interpretation is several realizations of the process being required.

2. Why mean is constant is important here?

Reference: Stoffer and Shumway. Time Series Analysis and Its Applications, paragraph right before Sec 1.4 on pg 19