Introduction
Welcome to the world of statistics!
Statistics is a broad, daunting term, encompassing all aspects of data: analysis, collection, representation, and arrangement, to name a few. However, it is not overly difficult to understand some basic terms and get a general idea for what statistics really means.
Included in this section of the website are explanations regarding the different sides to statistics, alongside a list of vocabulary with basic definitions. If you are new to statistics and are unaware of some aspects, there is some useful information on this page that you can use to inform yourself about the phenomenon.
Data Visualization
A very important component to statistics is statistical modelling, which is essentially the ability to represent and interpret data in a visual form. Below is a guide I made that explains some basic mathematical models to know.
Videos by Will
The following videos were made by myself for eager statistics learners. I hope you find them informative!
Video Recommendations
The following videos were not made by me, but are videos that I highly recommend to anyone who has an interest in statistics. Under each video, I have included a short description of why it is so great and applicable for statistics learners.
This video is a perfect introduction to Bayes Theorem, an important theorem in inferential statistics. Bayes Theorem is fundamental in explaining the way many statisticians come to conclusions, and it is important to familiarize oneself with this concept.
This video introduces the idea of binomial distribution, and uses an anecdote to demonstrate how it is applicable to real life.
Vocabulary
data
collected facts and figures
statistics
the study of data and processes relating to data, including organization, modelling, inference, and more
probability
a branch of mathematics/statistics describing the likelihood of an event
continuous
a type of data that spans all real values between an interval
discrete
a type of data defined to specific, particular values
statistical inference
using data or parts of data to come to a conclusion (inference) using data analysis
bayesian inference
using Bayes' theorem to update a prior hypothesis after more knowledge is gained
correlation
the statistical relationship between two variables; does not imply causation
causation
a statistical relationship where one variable or factor has an effect on the other
probability distribution
a presentation of the probabilities of different possible outcomes for a given situation
poisson distribution
discrete probability distribution that explains the likelihood of independent events occurring within a time interval
stochastic process
also called a "random process," a stochastic process is a group of random variables indexed by time