## Saturday, February 19, 2011

### Quick Look: Uphill Struggle

When the parent's work schedules both coincide with a school day, it's often my displeasure to have to retrieve the small one from school. And because I don't drive, that's a ~30min round trip, which involves a fairly steep hill.

I don't much care for it.

I didn't track how many times that happened last year. But out of shear curiosity, and because I can, I tried modelling the set up to get an estimate.

You could probably work it out with probability alone. But that's too much like hard work.

Assuming...

Firstly, we assume I can randomise the parent's shifts - that is, there's no particular pattern to them. We also assume that their shifts are independent of each other and of school days and school holidays. That's not strictly true. But since there isn't a strong, underlying pattern linking them, we just ignore it.

Same goes for holidays, which in this model are also arranged at random. We can also ignore date, month, etc. because of the above assumptions and because it's just easier that way.

And finally, we ignore sick days, study days and over-time, since they aren't really predictable, and should hopefully average out over repeated trials.

I've also included a 10% chance that, for whatever reason, I won't have to pick the sister up. That number's just a random guess.

Hand-waving explanation

First you create three sets representing a year's worth of shifts for each of my parent and a year's worth of school. You then randomly delete a year's worth of holidays, bank holidays, and training days from the sets.

Finally, you count on how many days, shifts and school days coincide.

You can look at the code here.

Since this is another random use of the Monte Carlo method - you run the model 10,000 times and then draw a histogram of the resulting counts.

Hey Look!

It's a normal distribution
Which isn't that surprising.

The average is around 32 times a year, with about 78% chance that I'll have to pick up the young 'en between 27 and 37 times in any given year.

Oh, and obviously if you increase the 10% probability mentioned above, the average will get smaller (and vice versa)
And that's pretty much it. Any questions?

Oatzy.

## Friday, February 18, 2011

### Misplaced Hate and Pointless Arguments

Two of my friends recently (independently) wrote blogs on conceptually similar subjects. And not liking to be left out, I thought I'd throw in my own opinion.

The subject in question is excessive hatred in inconsequential matters; in Aerliss's case tech-snobs, and in Andrew's case Gaga-intolerance.

[I'm simplifying. Read their blogs for the full stories.]

But I'm going to go with a slightly different approach. One of my better qualities is my willingness to admit when I'm wrong. And the truth is, I've been guilty of both those things, and I was wrong to.

So because I like to try and explain things - and like the sound of my own blog voice - that's what I'm going to do.

Rotten Apple

Time was, I had - at least what seemed like - legitimate reasons for disliking Apple, and iPods, and so on; their extortionate prices, the more obnoxious of the fanboys/girls, Steve Jobs' dickishness, and the fact that Apple products are treated as if they're some form of perfection that we should all be aspiring to... But that's beside the point.

Eventually it came to be that I was well known for my general dislike, to the point where people would (and still do) say thing like "if you get an iPhone, Chris will disown you". And was at one point mocked when I said,

"Today sees the release of the iPhone in American, and despite the arguments we had over at Andrews blog, I really would like one. It's just so smooth and shiney [sic]."

Of course, back then, there really weren't any other smart phones quite on the same level.

Strong followings create strong oppositions. The more devoted the fans, the more pissed off and irrational the 'haters'.

The sobering moment for me came when I was sneering at an iPhone advert, and was called-out for being just as obnoxious as the Apple-snobs I so despised.

Don't get me wrong, when fanboys get all Apple-snobbish around me, I still feel an overwhelming urge to slap some sense and humility into them. But otherwise, I've mostly just stopped caring.

And it does makes me feel a little uneasy, and guilty, when people expect me to automatically hate everything Apple-related. Also, Blackberry.

Attention-seeking, Talentless...

In fact, I have nothing against Lady Gaga. So I'm going to talk about Justin Bieber instead.

I didn't really care about his existence for a long time. And when I first heard his music, I found it not to my taste. Whatever. But when I started using Twitter more, his existence became somewhat unavoidable [until].

As Andrew points out, like it or not, everyone's entitled to their opinion.

So when I'm listening to, say, T-Rex and the little sister tells me to "turn off that crap music", while blasting some crappy dance music from her phone like a chav on a bus; while I may feel morally obliged to slap her for having such a disastrously wrong opinion, she is still (technically) entitled to that opinion.

Even if she is wrong.

Fact is, when it comes to celebrities, 'hatred' and disputes of opinion are seldom reasonable. You don't like their music? So what. Don't listen to it. But it's never that simple.

Justin Bieber is one of those particular divisive individuals - you either love him or hate him. Well, actually, there are people who occupy the 'couldn't care less' middle ground, but they can't be heard over the sound of squealing 14 year old girls, and the loud mockery of people who by all rights shouldn't give a damn and should know better.

And what goes for the Biebs, goes for the Gaga.

In these instances, there's a lot of herd mentality involved - you'll typically align your opinion of a divisive artist with that of your friends; even if you secretly have a few of their track on your 'guilty pleasures' playlist.

The other thing is, these artists tend to be very easy targets. If you're vocal about disliking someone like Beiber, and you make jokes about them, your friends will laugh and agree with you, and you get a sort of encouragement and reinforcement from it.

Unreasonable Reasoning

People often aren't as in control of their actions and their thoughts as they'd perhaps like to believe. Whether we like it or not, we're quite easily influenced, and manipulated.

First of all, otherwise reasonable opinions can become exaggerated over time. This might be the result of reinforcement from peers. Or your opinion can just plain be influenced by your peers.

Whether or not we like to admit it, there's sometimes a certain amount of jealousy and/or envy at the root of pointless hate as well. Similarly, other times, we dislike things because other people like them and/or they're popular. It doesn't make sense, but we do it anyway. Because we're all beautiful, unique snowflakes... *cough*. Or sometimes because a certain person or people that we don't like, likes them.

When these matters develop into arguments, another thing you get is escalation - even an argument that starts based in logic and reason can develop over time into a meaningless shouting match. And this usually reinforces and magnifies now empty opinions, as well as encouraging stubbornness.

And when that happens, your only hope is to call it quits and get out with your dignity in tact. Because when that happens, no-one ever 'wins'.

That's why I try not to get into arguments regarding Mac vs PC, religion vs atheism, conservative vs liberal, etc. It's a exercise in futility, and I have better things to do with my time.

Really, the best response to all this, and the people who insist on bothering you with this nonsense, is to say "So fucking what. Go bother someone who gives a damn".

And if you're really dead set on having pointless arguments, you'll find the Pointless Internet Argument Forums here. Otherwise, for the love of God, keep it to yourself.

Oatzy.

[Learned the error of my ways. Mostly.]

## Wednesday, February 16, 2011

First of all, you've probably noticed the new logo. Unless you're reading this in an RSS reader. If you are, go to the blog and gaze into it's logo-y goodness.

See what I did there? I totally earned that A in GCSE Design Graphics.

I like it, at any rate.

The actual title came from when the blog was still called 'Oatzy's Blog'. Which was a terrible title, but I couldn't for the life of me think of anything better. But I did have a subtitle idea - "Answering the questions no-one asked". In the end, I just thought "fuck it", and went with that.

If you were wondering about the orange, it's a kind of throwback from the website I made (no longer online) for our 'Young Enterprise' thing in sixth form - our company was called 'Purple Oranges'. But that's a whole other story.

Aside from that, I've been 'hired' to make the website for Dearne Valley Swimming Club, which my mum and little sister are involved in.
[I also re-drew and vectorised their logo at no extra cost]

Now, according to this flowchart, seeing as it's for my mum, I should work for free. Not that I've ever charged for building a website.
[no longer his]

But I have been 'paid' this time, with a bottle of rum. And frankly I'm content with that.

And if I'm honest, I enjoy doing it anyway.

Or I did; We're past the interesting part, and it's all just adding content now. Which is dull.

Here is the link. There's only an under-construction page there at the moment, and I doubt you'd be interested anyway, but with each link I post to it, the page's search rank will get incrementally better - it's currently on page 3, with the old, no-longer-functioning site dominating the first page of results.

In fact, if you're interested, you can see the work in progress design here, or just look at the image below
 - the site is now complete.

I'm not completely content with it, if I'm honest. I think I've laid it out a little too much like a blog, among other thing. But it might just be that I've been looking at it for too long. The important thing it, the people I'm making it for seem to approve. So can't complain.

That said, if you have any suggestions, constructive criticism or flattery, do feel free to offer it up.

Oatzy.

## Wednesday, February 09, 2011

One of the things that stuck in my mind from the last blog's analysis was 2007
The top two films for RT Score and Audience Score were Juno and No Country for Old Men. No Country got the Oscar and the highest RT score, but Juno got the highest Audience Score - this was one of the instances where the hypothesis of the last blog failed.

Now there was something I thought about in passing when I was writing the last blog, but I didn't bother mentioning it. But I thought I'd revisit and look in to it.

So that 'thing' is sample bias - that is, the people voting on films on RT (and creating the audience score) may not be representative of the general population.

I was originally concerned that the users of RT may be predominantly younger people; so then, their opinion and taste would be over-represented in the score. But I dismissed that idea as being a stereotyped view of internet users.

But realistically, it's best not to make assumptions either way if you can get actual details.

Rotten Audience

The are two sites I look at for site demographics. The first is Alexa, which you may have heard of. It has some benefits, but unfortunately for more detailed analysis, they want your money.

The other is Quantcast, which is a lot better, but sometimes their numbers are only estimates (not the case for RT). This is the one I'm using here. Here's what the demographics look like
NB/ this is US only demographics, which make up ~60% of the total visitors to RT. But the results are very similar for other countries.

Percentages to the left of the graphs are the actual distributions of the users. The 'index' numbers to the right show how those distributions compare to the internet as a whole.

Misrepresented Judges

So the 'hypothesis', or at least one the the hypotheses, of the last blog was that the Audience score could in some way be used as a predictor of Oscar winners, in so much as it reflects the 'wide appeal' of the films.

Of course, this only works if the taste of the voting comity for the Best Picture matches well the tastes of the people visiting Rotten Tomatoes and contributing to the Audience Score.

The membership of the Oscar comity is fairly secret, or at least, undisclosed. But we do know it's made up of ~6,000 industry professionals, so it seems safe to assume they're likely predominantly in the 35-60 age group, with maybe an even male/female split. And this could be a source of the weak correlation, since RT users are predominantly in the 18-49 age group - skewed slightly towards younger ages.

But do the different demographics have different tastes in film?

I suppose not necessarily. There are certainly some overlaps between these two groups. But on the other hand, maybe the difference between which films RT users vote highest, and which films gets Oscars is a reflection of these differences in tastes.

As it is, there's no way to manipulate RT Audience scores to better reflect the different demographic make up, and no way to improve on their predictive power.

So just some thoughts.

Oatzy.

## Friday, February 04, 2011

### T-Shirt Calendar

When I was putting together the Life by Numbers blog, I was thinking about other things I could track, without the tracking thing becoming too intrusive.

First couple of things I did was signing up for miso to track TV and film viewing habits, as well as RunKeeper to track my movements on foot (which wouldn't be logged with FourSquare). So far, RunKeeper - or perhaps just my phone's GPS - have been a bit of a disappointment. But that's a whole other story.

The other thing I did was to take a picture a day of myself. I had nothing in mind specifically to do with the pictures, but thought why not?

The obvious use is to do one of those time-lapse, slideshow thing. But those are dime-a-dozen. And besides that, the pictures aren't all head on and centred, so you wouldn't really get the same effect.

Details

Instead, I thought about what was actually in the pictures - what could be gleaned from them.

First things that come to mind are (a) when I shave, and (b) when I get my haircut. And they're things I might come back to once I have more than a months worth of pictures; I don't shave that often.

So the only other thing is what I'm wearing.
The above is a sort of calendar - Sunday 2nd of January to Friday 3rd of February - where each square is coloured to match (as closely as possible) the primary colour of the t-shirt I wore on that day.

The last square's crossed out because I haven't decided yet what t-shirt I'm going to wear tomorrow.
 - I wore a green t-shirt.

There's not really much logic to it, beside that when I pick a t-shirt I don't pick one I can remember wearing within the last week. Yes, I have several green t-shirts.

Otherwise, it mostly just looks like Elmer the Elephant. But it is an interesting way of represent the dataset, even if it serves no useful purpose other than to suggest that green might be my favourite colour.

Oatzy.

## Thursday, February 03, 2011

### Revisited: Tweets by Gender

So I first looked at this here, with a follow up here. The conclusion was that among the people I follow, the women do tweet more than the men.

So it's now about 4 months since that last post, so I thought I'd have a quick look at how things have changed.

As a quick recap for those too lazy to click the link above, here are the results from last time (now in graph form)
If you want to know about the technical details, you will have to click the link.

And here are the new numbers
It's pretty much the same deal, but it's there for those interested. And just to further clarify whatever point it is I'm trying to make, here's a boxplot comparison of the numbers (made in R)
The three circles over the female's numbers are outliers. And once you factor out the outliers, you find the numbers are actually quite similar. But the middle quartiles (the box parts) are still slightly lower for the males.

The other thing I did, for the shear hell of it, was the rates for the last 4 months; the other graphs are 'lifetime' rates.

You can get the dataset for all these numbers - as well as totals, days online, changes in rates, etc. - here.

This isn't something I'm going to try and work out myself, because frankly it's not worth the amount of effort it would require.