- Statistics For Data Science Cheat Sheet Maverick Lin
- Statistics Definitions Cheat Sheet
- Statistics Cheat Sheet For Data Science
- Statistics Cheat Sheet Pdf
The choice of statistical analysis to use is mostly governed by the type of variables in a dataset, the number of variables that the analysis needs to be conducted on, and the number of levels/categories within a variable. As long as we have a good understanding of the data that we are dealing with, the selection of statistical analysis to use should not be too intimidating.
Data Science Cheet Sheet. Data science is a concept to unify statistics, data analysis, machine learning, domain knowledge and their related methods in order to understand and analyze actual phenomena with data. Below is an extract of a 10-page cheat sheet about data science, compiled by Maverick Lin. This cheatsheet is currently a reference in data science that covers basic concepts in probability, statistics, statistical learning, machine learning, deep learning, big data frameworks and SQL. Statistics Cheat Sheet Basic Statistics Definitions: Statistics – Practice or science of collecting and analyzing numerical data Data – Values collected by direct or indirect observation Population – Complete set of all observations in existence Sample – Slice of population meant to represent, as accurately as possible, that population.
I have always wondered why most statistics textbooks do not contain a table that consolidates all the different statistical analyses at a glance, how they relate to one another and when to use each of them. A quick search on the internet uncovers a number of similar cheat sheets, but none of them presents the information in a way that was intuitive to me.
Statistics For Data Science Cheat Sheet Maverick Lin
In the cheat sheet that I have created, the rows represent the different types of independent variables (also known as predictors or covariates), while the the columns represent the different types of dependent variables (also known as criteria or measures). The intersection of the rows and columns then informs the appropriate analysis to use, and the small text below each analysis shows the quick steps for executing the analysis in SPSS.
This post is the first of a mini-series in Demystifying Statistical Analysis, where I hope to help make understanding statistical analysis simpler, by drawing the connections between different statistical analyses as well as explaining their differences. Midi player mac free download.
You’ve got data, you’ve got a hypothesis, you even gathered the courage to test it. But how do you choose the right test? Well, really you should have thought about this before you collected the data. Maybe you did and maybe you didn’t. I won’t judge (ok, maybe a little). Instead, I’ll offer you a handy cheat sheet that could help you navigate through the various tests and their assumptions whenever you need to do that.
Statistics Definitions Cheat Sheet
When I just started my PhD program, I had very little knowledge of applied statistics in behavioural sciences. I had a computer science degree and could do probability, but was not friends with t-tests and ANOVAs. Thankfully, statistics courses were a degree requirement and I enjoyed them so much that I ended up teaching and tutoring undergraduates in the following years.
Statistics Cheat Sheet For Data Science
This cheat sheet came about while I was taking the introductory univariate statistics course back in 2009. It took a significant number of neurons to remember all the tests and their assumptions, so I decided to follow Einstein’s advice and “Never memorize something that you can look up.”
Statistics Cheat Sheet Pdf
Yellow blocks show the questions to answer / decisions to make about your data, orange blocks show transformations required to use the tests and blue blocks show the tests and their assumptions. Don’t forget, this cheat sheet is just a start and is not a complete guide. Once it helped you pick a test, deep dive into the test’s details in your stats book or online resources.