Dispersion measures are fundamental, because unlike mathematics, statistics work with random variables. For example, the big media worked with deterministic values, such as candidate A has 45% and B with 30%. For mathematics, A is clearly ahead, but for statistics, I don’t know. Today they present it in a statistical way, as they talk about the “margin of error”. If the “margin of error” is 15%, the two are technically tied.
Descriptive statistics are numbers that summarize and describe all information. In this case, the data sets or simply data. But. This information will depend on what we evaluate, such as population or sample, as stated in the previous post. Getting Started The central theme of this post is just “describing” the data. Therefore, they do not represent more specific conclusions of the sample in relation to the population. The technique used to extend conclusions from the sample to the population is statistical inference, a topic that does not make sense to children. An undergraduate statistics course is the most appropriate place.