# Mean, Median, and Mode

Learn about statistical measures, more patricularly, the central tendecies : mean, median, and mode.

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## Data as a collection of integers

The core concepts of data structures in different programming languages are identical, although the implementation varies syntactically.

Moreover, the algorithm or sequence of instructions is deeply associated with the core concepts of data structures. But before that, we need to know a few elementary discrete mathematical algebraic concepts, which are also associated with data structures.

The concepts of data structures in various programming languages inherit their roots primarily from discrete mathematical algebraic concepts known as datasets. So, before getting into the core concepts of data structures, theoretically, we need to understand the concept of datasets.

What’s a dataset? A dataset is a structured collection of data points, often organized in a specific format. For example, datasets can be depicted as sets of integers like {14, 1, 58, 3, 85} or {1, 2, 2, 4, 5, 6}.

Humans started storing data and started doing operations on them before any programming languages’ forays into data structures. In that sense, we have implemented those old concepts of algebraic datasets very recently into programming languages.

In programming languages, we thought of arrays first; then, we found arrays weren’t enough. Therefore, we implemented concepts like stacks, queues, linked lists, trees, hashing, etc. Data structures are now used in every programming language to store data in an organized and efficient manner. And to do that, we need an efficient algorithm. That is the basic concept. Moreover, discrete mathematical algebraic datasets, algorithms, and data structures are also being combined into meaningful entities.

We’re more or less forced to do so because the volume of data is increasing faster than ever. Effective algorithms that can be used to sort large amounts of data are getting more attention than ever.

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