Learn Statistics Daily!
What you'll learn
- Learn the fundamentals of statistics
- Learn how to describe data, find central cendency and data viability
- Understanding probability
- Increased quantitative and numerical reasoning skills!
- No special software or other materials are required.
- This course is unsuitable for people with very low numerical aptitude.
Statistics is a subject like salt, needed in every food. The process of gathering, analysing, and interpreting data is all covered by statistics, which also offers a conceptual framework. The mathematical underpinnings for machine learning and data mining are provided by statistics, which is employed in many fields of scientific and social study as well as in business and industry.
The principles and methods of statistics as they are used in a wide range of fields will be thoroughly introduced to students in this course, especially data shaping, central tendency, data viability, z-scores and most importantly the probability! for the central centendency mean, median, and mode are illustrated along with practice problems; and skewed distributions are explained, as well as how to calculate the weighted mean. For the data viability, this course will help you to understand and explain variability (spread) in a set of numbers, including how to rank data and interpret data such as standardized test scores
The information and abilities you need to begin data analysis are given to you in this course. You'll investigate ways to utilise facts and utilise statistics. Each topic is explained with various parameters so that learners can use the command in many practical scenarios. Some images/ contents used in this course are under license: Creative Commons Attribution licence (reuse allowed), presented by Frank H Netter at the Quinnipiac University. We adapted the material, added more supporting files, and quizzes.
Who this course is for:
- Anyone interested in learning basic statistics
The Scientific Programming School, with 60,000+ students is an awesome e-education start-up initiative to provide professional training and practice courses for Scientific Coding, Linux, and Big Data. It is also an interactive and advanced e-learning platform that gives you the opportunity to run scientific codes/ OS commands as you learn with playgrounds and Interactive shells inside your browser. Scientific Programming Instructors specialize on Linux, Devops, HPC and Data Science coding with scientific programming. Currently we support three OS (Ubuntu, RHEL and SuSE) and 50+ programming languages including the commercial ones like Matlab. At the Scientific Programming School you start learning immediately instead of fiddling with OS, VMs, SDKs and/ IDEs setups. It‘s all setup with Docker on the cloud.