the statistic in the wardrobe

When I was at university (back in the Dark Ages) I had to take a statistics course.  I knew it wouldn’t go well and it didn’t.  I had a book by Derek Rowntree called Statistics without Tears.  I remember throwing it across the room and crying “You lied!” You can still get the book, it is actually very good and as I had a  maths A-level under my belt you would have thought I would be have been fine with stats.

I now realise it wasn’t the stats that were the problem but the subject matter.  If there was less talk of X and Y and more of skirts and dresses, or curly kale and sprouting broccoli I would have been top of the class.  So today I bring you wardrobe statistics where SD stands for Silk Dress not Standard Deviation and Chance Variation refers to the oppotune discovery that the pink scarf looks fantastic with the lime green jacket 🙂

You may remember that I took up the challenge of Project 333 last summer.  This year I have decided to reverse the project.  I am keeping a tally of the clothes I wear over a three  month period and then restricting myself to those clothes only for the rest of the summer (I am optomistic that it will be a blazing hot day on St Swithun’s day).

At the end of month one there is a definite trend appearing.  I am wearing almost entirely jersey (bamboo and cotton) and the colours are generally muted with bright accessories.  I am wearing more earrings (I used to just put a pair in and leave them) and have discovered I rather like big dangley ones.  I rarely wear trousers other than leggings with tunics and I almost  never wear a coat.  I am usually barefoot or wear Toms or Fitflops.  This a big reveal as although I have culled my shoe collection quite severely I still  never wear many of them.  Regardless of the weather I tend to wear summery light clothes and just layer up if it gets cold.  I haven’t worn socks or tights all month.

For those of you who would like the figures they are as follows.

  • Tops:  I have worn 10 different tops 16 times in total
  • Bottoms: I have worn 6 bottoms a total of 15 times.
  • Dresses: I have worn 7 dresses a total of 15 times
  • Cardigans:  I have worn 6 cardianas a total of 16 times
  • Scarves:  I have worn 5 scarves a total of 15 times
  • Shoes:  I have worn 6 shoes a total of 30 times, the fitflops 18 times!
  • Coats/Jackets:  I have worn one coat twice and one jacket once.

Colours are very blue heavy.

  • Blues: 27
  • Pinks: 12
  • Grey: 11
  • Neutrals: 9
  • Teal: 8
  • Purple: 7
  • Black: 2
  • Green: 1

I recently had my colours done and I think I am pretty okay with the ones I am wearing but apparently should be wearing more yellow and orange.  I hate both of them on me so I can’t see that happening soon.

In the meantime it has been an interesting look at how I use my wardrobe and you will be delighted to know you will be getting another update at the end of May.  Bet you can’t wait 🙂

 

10 thoughts on “the statistic in the wardrobe

  1. Well, how interesting. This seems like a very interesting way to approach the declutter of our wardrobes. See what you really wear and keep only that. That’s pretty clever! I sure like this version of stats more than my college class, too.

    • I’ve heard variations on this where people turn clothes hangers around when they wear something or move them from one wardrobe to another. But I am a bit of an Excel geek 🙂

  2. When we put in a new built-in wardrobe I filled it in order of the clothes I wore most often, then those I really loved. Anything that didn’t fit had to be sold/donated. What I find hard is managing work and casual clothes. Working part-time means I spend pretty much equal time in both so I try to keep items that can work in both situations e.g. smart jeans that can be dressed up with a blazer or down with a t-shirt. When I’m at home my favourite skirt is a long cotton jersey one- so comfy!

    • The workplace home balance can be tricky, although it does rather depend on the workplace. I’ve noticed that many places are a lot more relaxed than they were even 10 years ago. I am fortunate that I work from home, so though I have a few smart outfits they have been chosen to be ones I would also wear on a normal day dressed down. In fact today is one of those dresses, dressed up with heels and a jacket. Today with fit flops and a cardigan wrap.

  3. Great way to analyse! 😉
    I used to loathe orange and then fell for a simple orange skirt that I have worn so much, the lining is worn out and having to be replaced (or it would have been in my 6 items challenge and changed the whole selection!). I was surprised how many things/colours I can wear it with, from black/grey/brown to purple/burgundy/teal/green/red, not so much blues, though (mind you, navy works!), just by adjusting accessories like tights, scarves or belts…
    I think yellow is difficult – I love pale pastel yellow with light grey, though, that’s an old favourite. Stronger yellows can really make a person look sallow, so perhaps it’s about finding the right one! I do like mustard, another colour I can wear with the orange skirt (with the greens/purples!), but find I’m not sure it works with my iron grey hair, now.

    • Funnily enough I was admiring a pair of pastel yellow and grey striped socks belonging to my husband yesterday and thought they made a lovely combination!

  4. Recently found your blog through Recovering Shopaholic and I read all your blog posts in one sitting! I really like it. I’m curious about your “getting your colors done.” What system was used and what was your outcome? For instance, I used a SciArt analyst in Atlanta and found I’d been dressing as a Winter when in reality I’m a True Summer. Once I got used to the new color palette I love it and I get more compliments. Now I predominantly wear blues, teals, purples and pinks. Before it was black, white, brights.

    • Thank you 🙂 I had my colours done by a Colour Me Beautiful Analyst and am Warm with soft and
      light undertones. And the colours do seem to suit me.

  5. Pingback: clothes statistics | one pair of shoes at a time

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