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Basic Probability Theory, Arbitrary Artwork, and Communications in the framework of Computer Science at an undergraduate level. A guide to developing an education…
This article will follow the format:
Intro — Part 1 : Basic Probability Theory — Part 2: Arbitrary Artwork — Part 3: Communications — Conclusion and Course Format
Introduction
In short I have found a few subject matters of personal interest which I hope to employ as points of specialisation to augment my journey as an undergraduate computer science student. This is my second degree, hobby, fledgling career, whatever term permits it to be taken seriously enough to dedicate to but not so much that it is the majority of what I do in life, yet.
Navigating my way through these various topics I will detail how I hope to encompass my existing goals in technology with personal areas of interest in the hopes of becoming a better developer. I believe the subject areas I have chosen can augment my educational journey in a way which enables me to build more creative and meaningful applications, as well as decide a technological sense of professional direction for myself. It’s machine learning meets personal education/goals with an attention to detail which hopefully ensures each micro step is achieved, and each macro goal is completed in order to strengthen my professional skills for the long term.
Part 1: Basic Probability Theory
Below is a definition of Probability Theory as defined by Britannica:
(Please note I have left some of the hyperlinks in for personal use, as many are relevant in the wider context of what I do.)
“Probability theory, a branch of mathematics concerned with the analysis of random phenomena. The outcome of a random event cannot be determined before it occurs, but it may be any one of several possible outcomes. The actual outcome is considered to be determined by chance.
The word probability has several meanings in ordinary conversation. Two of these are particularly important for the development and applications of the mathematical theory of probability. One is the interpretation of probabilities as relative frequencies, for which simple games involving coins, cards, dice, and roulette wheels provide examples. The distinctive feature of games of chance is that the outcome of a given trial cannot be predicted with certainty, although the collective results of a large number of trials display some regularity. For example, the statement that the probability of “heads” in tossing a coin equals one-half, according to the relative frequency interpretation, implies that in a large number of tosses the relative frequency with which “heads” actually occurs will be approximately one-half, although it contains no implication concerning the outcome of any given toss. There are many similar examples involving groups of people, molecules of a gas, genes, and so on. Actuarial statements about the life expectancy for persons of a certain age describe the collective experience of a large number of individuals but do not purport to say what will happen to any particular person. Similarly, predictions about the chance of a genetic disease occurring in a child of parents having a known genetic makeup are statements about relative frequencies of occurrence in a large number of cases but are not predictions about a given individual.
This article contains a description of the important mathematical concepts of probability theory, illustrated by some of the applications that have stimulated their development. For a fuller historical treatment, see probability and statistics. Since applications inevitably involve simplifying assumptions that focus on some features of a problem at the expense of others, it is advantageous to begin by thinking about simple experiments, such as tossing a coin or rolling dice, and later to see how these apparently frivolous investigations relate to important scientific questions.”
Here is an illustration of Basic Probability Theory:
As a huge fan of Maths, I’m working on how it links to Computer Science and forms the basis of many fascinating aspects of life. I am currently focusing on better understanding basic probability theory and how it evaluates card games, sports and matters of macro and micro economics in the digital age.
CURRENT ENDING. THIS ARTICLE IS A WORK IN PROGRESS.
I hope to add the other sections at my earliest convenience, along with a detailed course format on each of my initial 8 courses. I have completed approximately 40% of the work already, and hope to complete it all — including exams — within the first few months of 2019. My #100DaysOfCodeChallenge will see me complete some courses and make significant progress with others, based on the plan and various course structures and content.
