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夢と現実の間
Between dreams and reality

負ける気がしねぇ!!

Tracy desu yo, pessimist and world’s worst procrastinator. Uni student with still a lot of things to learn. Interests include otome games, Naruto and Japanese.

: Loves pink, food, ice-cream.

Summer is my eternal love.



Waiting for:


chitchat:



recent update :
Ah.... /sigh/
written on Monday, June 22, 2015 @ 11:47 PM ✈

So....... usually I like stats since out of the 8 subjects per year it's the only one that's not /purely/ science. It's a nice break. Especially since 8 of the 12 weeks is actual stats, and the last 4 weeks is algebra and requires minimal study (ah that stuff was good).

BUT



It all changed this year (TT) This year there is no algebra to save me and it was 12 weeks of stats. To top it off, there is no longer any theory exams and everything is purely on the computer. Why? Because the stuff became that complex you can no longer analyse the data by hand. So...... I'm totally gonna have fun in tomorrow's 3 hour computer final. Going to be so blind afterwards. Exam worth 40% and the other 60% came from 6 x 10% assessable exercises.

Also I hate to say this but....... this is the year I'm going to lose my HD streak in stats sigh _ Lost too many marks already from assessable exercises and unless I get 90% tomorrow HD is out of the picture. I miss the last two years of stats where I got 95-100% in the prac midsems :/ (Never knew what I got in the theory finals though since they never give those back).

Anyway this year I had an epiphany of why stats is so hard. I really don't think people understand. I think maths is pretty straight forward most (most!) of the time since it's like do "THIS." But with stats it's not maths..... it's literally half maths and half English....... and playing detective. First you read this deceivingly short paragraph and you think "oh yeah, seems simple okay" and then you realise your working out takes like 5 microsoft word pages > > 

And you have to hope you picked the right model otherwise your analysis is moot. And after looking at all the figures the last part which is my utter weak point is saying what those numbers MEAN. Here's just the quickest example I could find from our work:

"The key, regardless of the complexity of the spline, is that there appears to be a couple of points of inflection around the 1000 and 4000 feet depths and this probably reflects the light penetration into the water and/or the fact that different species of phytoplankton can live in different light levels and depths but most are concentrated at the surface."

Like. What. Is. THIS??

I kid you not there is nothing about thinking about light penetration and species of phytoplankton in the actual question, the only data we got was "depth" and "chlorophyll concentration." Fuarrr my mind does not expand out of the box that far.

For me, the death words in statistics is:
"transform"
"not normal data"
"logit"
"on the backtransformed scale"

 (╯°□°)╯︵ ┻━┻

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