The video "Data Science & Statistics: Levels of measurement" by 365 Data Science explores the different levels of measurement, which are divided into two main groups: qualitative an
Data Science & Statistics: Levels of measurement
Channel: 365 Data Science
Uploaded by 365 Data Science on 20170811
Categories: People & Blogs
Tags: levels of measurement, measurement, nominal, ordinal, interval, ratio, types of data, introduction to statistics, measuring scale, types of scales, levels of measurement in statistics, nominal ordinal interval ratio, level of measurement statistics, level of measurement, scale of measurement statistics, scales of measurement, qualitative and quantitative data, Nominal variables, what is the level of measurement for temperature, temperature level of measurement, statistics, big data
d quantitative data.
Qualitative Data
Nominal: Consists of categories that are not represented by numbers and do not follow any specific order, such as car brands (Mercedes, BMW, Au
di) or the four seasons [00:09].
Ordinal: Consists of groups and categories that follow a strict, logical order, even though they are expressed with words rather than numbers. An ex
ample is rating food options from negative to positive (disgusting, unappetizing, neutral, tasty, delicious) [00:26].
Quantitative Data
Interval: Represented by numbers where the di
fference between values is meaningful, but there is no true zero. A key example is temperature measured in Celsius or Fahrenheit, where 0 degrees does not represent the complete abs
ence of temperature [01:01].
Ratio: Represented by numbers that have a meaningful difference and a true zero point, meaning zero indicates the complete absence of the variable. Exam
ples include length and temperature measured in Kelvin [01:11].
https://www.youtube.com/watch?v=eghn__C7JLQ
Data Science & Statistics: Levels of measurement
365 Data Science · 213K
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