Difference Between a Random Sample and Time Series

Difference Random Sample versus Time Series
Jaap de Jonge, Editor, Netherlands

As far as I understand the basic difference is that:
- A time series is a sequence of data points, measured typically at successive time instants (per second, minute, hour, day, week, month, year). So time series data have a natural temporal ordering.
- A random sample has no natural ordering of the observations. It is a collection of data without any order, be it in time or any other. It is randomly collected data.

Difference Random Sample versus Time Series
Martin haley, Lecturer, United Kingdom, Member

- Random Samples are used when we want to use the probabilities if chance. The basic rule for random sample is that everyone in the population has an equal chance of selection. The difficulties are identifying everyone in a population.
- The issue with Time Series is that whilst they a series of measurement shown over time to identify a trend, within economics such as inflation or unemployment rates, the analysis is dependent upon the same method of calculation being applied to the time period in question. But governments are very good at changing the method.