4 ms·

Data Science is a form of statistics. Algebra II is a pre-requisite for statistics. How is replacing a pre-requisite with a more advanced class is a good idea?

kevinpet 3y ago
Simple, you teach a very low level spreadsheets course but label is "Data Science". Voila!
jordigh 3y ago
How is data science not just statistics, rebranded? When I studied statistics in university we studied clustering, regression, hypothesis testing, confidence intervals, visualisations, charting, general linear models... how is this different from data science? Is it just because we have more computing power, so we rebranded it? Instead of doing frequentist analyses because those are easy to do with smaller computers, now we do more Bayesian stats, on bigger computers, and therefore call it data science?
- topkai22 3y ago
  From the one data science course I took: compared to a traditional stats class, there is a bit more focus on data acquisition and pre processing, and more usage of our of the box tools, a bit less on some of theory (I don’t recall hearing about type I and type II errors). Of course, since it was a professional course there is probably the assumption that students already know these things…
- slt2021 3y ago
  statistics assumes you have data prepared and ready to work on. data science is more practical in a sense, you learn more to prepare real-life data for analysis. also statistics coursework doesn't cover ML part (at least the stats course that I took)
- tnecniv 3y ago
  I’ve periodically looked into it the differences and mostly it seems to come down to priorities. Statistics prioritizes mathematical rigor all the way through the process from collection to analysis. ML / Data science has more algorithmic concerns. Even the theoretical aspects of the two fields emphasize that distinction.
fatherzine 3y ago
"data science" -- science warping onto itself, forgetting that it's primary mission is to match data with reality.
oefrha 3y ago
It’s “data science” only in name. (Btw I hate the term data science; most practitioners of this profession practice pseudoscientific bullshit or worse.) From TFA: > The core issue of the CMF’s “data science” section is that it claims to be discussing data science while it is actually discussing data literacy. > ... > The CMF is replete with statements like “high-school data-science class students can learn to clean data sets – removing any data that is incorrect, corrupted, incorrectly formatted, duplicated, or incorrect in some other way [...] High school students can also learn to download and upload data, and develop the more sophisticated “data moves” that are important to learn if students are tackling real data sets.'' It’s more of an Excel class with some basic math sprinkled in.
deleted 3y ago
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kevinpet 3y ago

Simple, you teach a very low level spreadsheets course but label is "Data Science". Voila!

jordigh 3y ago

How is data science not just statistics, rebranded? When I studied statistics in university we studied clustering, regression, hypothesis testing, confidence intervals, visualisations, charting, general linear models... how is this different from data science? Is it just because we have more computing power, so we rebranded it? Instead of doing frequentist analyses because those are easy to do with smaller computers, now we do more Bayesian stats, on bigger computers, and therefore call it data science?

topkai22 3y ago
From the one data science course I took: compared to a traditional stats class, there is a bit more focus on data acquisition and pre processing, and more usage of our of the box tools, a bit less on some of theory (I don’t recall hearing about type I and type II errors). Of course, since it was a professional course there is probably the assumption that students already know these things…
slt2021 3y ago
statistics assumes you have data prepared and ready to work on. data science is more practical in a sense, you learn more to prepare real-life data for analysis. also statistics coursework doesn't cover ML part (at least the stats course that I took)
tnecniv 3y ago
I’ve periodically looked into it the differences and mostly it seems to come down to priorities. Statistics prioritizes mathematical rigor all the way through the process from collection to analysis. ML / Data science has more algorithmic concerns. Even the theoretical aspects of the two fields emphasize that distinction.

fatherzine 3y ago

"data science" -- science warping onto itself, forgetting that it's primary mission is to match data with reality.

oefrha 3y ago

It’s “data science” only in name. (Btw I hate the term data science; most practitioners of this profession practice pseudoscientific bullshit or worse.) From TFA: > The core issue of the CMF’s “data science” section is that it claims to be discussing data science while it is actually discussing data literacy. > ... > The CMF is replete with statements like “high-school data-science class students can learn to clean data sets – removing any data that is incorrect, corrupted, incorrectly formatted, duplicated, or incorrect in some other way [...] High school students can also learn to download and upload data, and develop the more sophisticated “data moves” that are important to learn if students are tackling real data sets.'' It’s more of an Excel class with some basic math sprinkled in.

deleted 3y ago

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