CREDITS Animation & Design: Waldi Apollis Narration: Lucy Billings Script: Lucy Billings Click here to see more videos: https://alugha.com/FuseSchool Hi, I’m Lucy and in this video, we are going to look at the different types of data that exist and how it can be classified. Starting with data collection... If data is collected by or for the company that is going to use it, it’s called primary data. If the data comes from somewhere else, it’s secondary data. Secondary data can have many benefits… like saving time and money, or providing information on past events. But you must carefully consider the reliability and validity of the source. This is true for all statistics. Whenever I read a statistic that interests me, I always check where the data came from and who funded it. Because quite often you’ll discover that there is an underlying ulterior motive. In fact, if there is one thing, I want you to take home with you, it is always to keep a critical eye on any data and “facts” you read or watch. Fact check everything, look at who is publishing the information. What is their motive? Are they neutral, or biased? But anyway, I slightly went off course there. So that’s primary and secondary data collection. Now for types of data. Data can be qualitative or quantitative. Things like gender, favourite colour, religion, opinions… anything that is non-numerical is qualitative. It’s descriptive information. Whereas numerical things… so things that can be quantified or counted… they’re quantitative data. Quantitative data can then be discrete or continuous... Discrete data can only take certain values. Like how many siblings you have… You can’t have 2.63 siblings. Whereas continuous data can take any value. It can be measured… like your height. You don’t have to be either 174cm or 175cm. You can be somewhere in between. Our final thing to discover is what is the difference between univariate and bivariate data... The prefix “uni” means “one” - like a unicorn with 1 horn, and a unicycle with 1 wheel. So univariate data is data with one variable. We can do different things with univariate and bivariate data… Which we will look at in other videos, and you can actually have data with more than 2 variables. This is then multivariate data, which we don’t really need to worry about at this stage. There we have different types of data. The question we are asking determines how we collect our data and how we then analyse it. Watch our other videos to learn about some of the different statistical tools we can then use. VISIT us at www.fuseschool.org, where all of our videos are carefully organised into topics and specific orders, and to see what else we have on offer. Comment, like and share with other learners. You can both ask and answer questions, and teachers will get back to you. These videos can be used in a flipped classroom model or as a revision aid. Twitter: https://twitter.com/fuseSchool Access a deeper Learning Experience in the FuseSchool platform and app: www.fuseschool.org Friend us: http://www.facebook.com/fuseschool This Open Educational Resource is free of charge, under a Creative Commons License: Attribution-NonCommercial CC BY-NC ( View License Deed: http://creativecommons.org/licenses/by-nc/4.0/ ). You are allowed to download the video for nonprofit, educational use. If you would like to modify the video, please contact us: info@fuseschool.org
The study of finches led to the development of one of the most important scientific theories of all time. In December 1831 a naturalist called Charles Darwin boarded the HMS Beagle, bound on a surveying voyage of South America. Whilst the ship and crew carried out coastline surveys, Darwin was fre
Learn the basics about halogenation within the alkanes and alkenes part of organic chemistry. Our teachers and animators come together to make fun & easy-to-understand videos in Chemistry, Biology, Physics, Maths & ICT. JOIN our platform at www.fuseschool.org This video is part of 'Chemistry for
The Mean | Statistics & Probability Bob is training for a race and is timing himself to check he’s getting faster. Times (in minutes): 51 48 45 44 47 50 44 47 45 43 49 44 43 44 His times are a bit inconsistent. He wants to find his average, to get a better understanding of what time he is likel
