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Master of Analytics Program Admission Rates Falling To Single Digits
dcblogs (1096431) writes "The 75 students in the 2014 Master of Science in Analytics class at North Carolina State University received, in total, 246 job offers from 55 employers, valued at $22.5 million in salaries and bonuses, which is 24% higher than last year's combined offers. But the problem ahead is admissions. There may not be enough master's programs in analytics to meet demand. NC State has received nearly 800 applications for 85 seats. Its acceptance rate is now at 12.5%. Northwestern University's Master of Science in Analytics received 600 applications for 30 openings its September class. That's an acceptance rate of 6%"
Drawing a wider conclusion about analytics programs from the figures from a mere handful of analytics programs.
That's too funny.
30 is only, but exactly, 5% of 600. Not 6%
Is that sensationalism ?
To coninue. So if it is statistical analysis, why not hire statisticians ? I feel like Data Analytics is another made up science degree , similar to "cyber security", in which student that have no background in CS, write papers on cyber attacks.
is this master of science in analytics the same as business analytics or data science? or is it more stats or something?
Or google, it would seem.
http://analytics.ncsu.edu/?pag...
Looks like mostly stuff I'd expect a maths grad to already know[1]. Maybe not the specific applications, but it isn't that true of anything?
[1] ANOVA? I did that as a non-maths undergrad. With a slide rule, uphill in the snow.
Confucius say, "Find worm in apple - bad. Find half a worm - worse."
Maybe they need to change it's name to something more exciting. Top World Analytical Tool. That would work better.
Be seeing you...
You must be one of the 5% with a masters of analytics!
Try Med School. You might have 100 or more applicants per seat.
Your hair look like poop, Bob! - Wanker.
There are a number of reasons why analytics is kinda a hard nut to crack. For poeple who genuinely enjoy physics and math as a discipline its frustrating to find yourself pidgeonholed in a single process as most analytics firms are outsource sweatshops for larger players like Boeing. Many firms just do one thing, like structure or fluid thermodynamics, and sometimes only on a single part or mind-numbingly enough a single subcomponent. Finding yourself staring at a combustor model or a bottle thread for 5 years is depressing and these firms will generally understand that. Expect to get short changed on licenses for software you use and your workstation wont come with super helpful things like a spaceball (navigation tool for 3d simulations)
the other problem with these outsource firms is theyre practically the only way to get a job at a larger firm, so youre going to have to do time in the trenches and hope some customer thinks highly enough of your understanding of their processes to steal you from the firm youre in. Until then expect a rather meager paycheck to be spent on your college debt. Your "laureate" or upper level engineers in some of these firms literally only work there for 30 years because theyre borderline incompetent and can simply go through the motions of bullying the IT department to help them launch simulation software. They know the customers products and terminology inside and out, but are too incapable as engineers to make it beyond approving your timesheets.
Good people go to bed earlier.
Is that really 'admission' rates? I mean, technically, semantically, I guess you could call it admission rates because it's literally the number of people of people entering the program because there are so few seats.
But really, in the vernacular, 'admission rates' have to do with the filtering process of who is allowed to enter based on qualifications, not if there's a seat available. Saying there's a low admission rate to me implies that their standards are too high, overfiltering applicants so that too few people are participating in the programs.
I guess I would have titled this article entirely differently, citing a lack of CAPACITY, not a low admission rate.
-Styopa
To coninue. So if it is statistical analysis, why not hire statisticians ? I feel like Data Analytics is another made up science degree , similar to "cyber security", in which student that have no background in CS, write papers on cyber attacks.
Based on the purposes it seems to end up being put to, "Data Analytics" is the synonym for "I completed reasonably advanced studies in statistics and/or computer science and then I went into advertising" that you can say without feeling the strong urge to end your miserable life.
This is never made that clear to students. Sure there's a notion that the liberal arts degrees aren't worth much. But then you look at the other classes and you don't really understand what the salaries are or how in demand those people are... Furthermore, the liberal arts programs always tell everyone how useful and valuable they are to your life and career and etc.
Here is an idea, what about a job future's market akin to the commodities future's market only with a longer time horizon. Commodities futures tend to project out months to a year in the future. But to be useful a job future's market would have to project out four to eight years.
You could have various companies agree to pay the university fees of new students in return for getting a reliable labor force. At the same time, it might be reasonable to build in a pay reduction upon being hired and an understanding that you'd work for that company for X years. Remember, these are the people that put you through school and gave you a job before you even knew what you were doing.
the alternative is continuing to saddle graduates with huge amounts of debt.
I've decided to stop wasting my time responding to AC trolls/sockpuppets... so if you want a response from me... login.
Walmart has an admission rate of 2.6% for low wage employees.
http://time.com/43750/walmart-...
We should hire some masters of analytics to explain to us that admission rates probably don't lead to the conclusions that you think they do.
Is it possible that we're just near the top of the Big Data bubble and that educational institutions haven't been able to bring specialized programs online fast enough?
It's starting to feel a little bit like 1999 again, just with different buzzwords:
- Social
- Big Data / Hadoop
- Cloud
- Internet of Things
In 1999, it was all just Web 1.0 and eyeballs. How far we've come :)