scribbles tagged ‘Excel’

drivers for change

Friday, July 2nd, 2010 | tags: , , ,  |

To celebrate a year of togetherness with Thomas, Excel has reviewed the financial side of our relationship.  This is what Excel says:. 

  • £350.00 (approx) Fully comp insurance with lots of nice stuff
  • £35.00 (approx) annual MOT
  • £33.00 (approx) annual road tax
  • £350.00 (approx) Service costs for a car with over 80K milage
  • £830.53 (exact) Diesel costs

This is less than the annual financial cost of commuting to and from work using public transport and on foot.  At a non financial level Thomas cuts 2 hours a day from that commute time, an uncomfortable journey, no seats, 2 changes that involve standing outside and jostling to get a place on the next stage of the journey. 

Changing my commute will be a core driver for changing my job…


3 bits of fabulous banter »

8pointsomething333333333333333334days

Thursday, April 2nd, 2009 | tags: , ,  |

8pointsomething33333333333334How long ago did I create my facebook profile picture album?  

I’m not abusing facebook, not at all, no, we’re actually very good friends 78.33335589% good friends.   Excel can confirm the decimal point and can even convert the Facebook fraction of a day  into hours, minutes and seconds.   Excellent.   I’ll just be left with the problem of working out what to use this information for…


1 wonderful musing »

WES ©

Tuesday, March 24th, 2009 | tags: , , , , , , ,  |

WES ©:   Wendy Experience Scale*

What is this?

This is a tool for assessing product and services experiences.   The tool uses a questionnaire  developed with the help of Excel and 84 pots of tea.   The  WES © can be administered to any Wendy  that uses a product or service that you want to assess.   The WES © will tell you whether that product or service meets the stringent, to be published, Wendy  International Standard of Experiences (WISE).    Unlike assessment tools such as the SUS which focuses merely on usability with  Likert scales**,   the WES ©   focusses on product and service relevant experiences including usability with  9 semantic differential scales*** .     The scales tap into the following experiences:

  1. Fabulousness
  2. Aesthetics – Visuals
  3. Fitness for purpose
  4. Financial value
  5. Aesthetics – Tactility
  6. Usability
  7. Complexity
  8. Engagement
  9. Predictability****

 

 

 

 Also known as ‘ FAFFAUCEP’   (pronounced faff-Oh-sep)

The WES © is currently in a Beta release stage and is available for use* by product and service developers on condition that they ask advance permission and provide me with a full report of the product, service,  assessment conducted including the results which will be used to build the  WISE standards.

Administering the WES ©

Let a common all garden Wendy use your product or service  to complete a common task that it was designed to enable.   Provide a unbroken supply of tea during use.   Observe the Wendy complete the task collecting usability style observational data.   When the Wendy has completed the task,   or given up  provide her with a copy of  the WES © and ask her to mark an X on the line between each pair of experience  descriptors that indicates her experience on  this continuum.   There is a practice item that you should encourage the Wendy to complete then discuss her answer to make sure that she understands how to use the scale.     As the Wendy completes the scale ask her to describe examples that have lead to her reporting this experience.   This information will be extremely useful for either developing marketting materials or deciding what to change to improve the experience.

Below is an example of a WES ©  completed by my marking X’s on each scale item describing my experience of my wireless radio.   You can make your own practice scale that covers some dimension of the Wendys or the product being assessed.   In the example below the practice item asks about whether the Wendy considers the product a worthy conversation piece.

Practice by identifying  where you are  on this scale:

never talk about it

————-X——

tell the whole  world about it

 

Where is the Wireless Radio on these scales?:

Absolutely Fabulous

–X—————–

Crappy
Cover-it-with-a-brown-bag ugly

———–X——–

purrrrrrr-rity  
                                   Just what I need

——X————-

Don’t see why I’d want to use it
You’d have to pay ME to use it

———–X——–

Take all my cash, and credit, NOW!
Squeeze, stroke, and lickable

——–X———–

Cooties, don’t touch IT!
Did I brake it or what?

—————-X—

Works a treat                  
I can  use it first time

—-X—————

training-required nightmare
   Snore, Snore, Snore

————-X——

Fun, Fun, Fun

Its  obvious what it was going to do

—–X————–

it was full of surprises

 

 

 

 

Analysing WES © Results:

Allocate the location maked on the line with a weighting number between 1 and 10.    

For even number questions the weightings increase towards the left,   for odd number questions the weightings increase towards the right.     Sum all the weightings.       The total possible score is 90.   Higher scores indicate better Experiences.  

Coding the example provided above looks like this

Fabulousness

–X—————–

9  from right
Aesthetics – Visuals

———–X——–

6 from left
                                 Fitness for purpose

——X————-

6  from right
Financial value

———–X——–

6 from left
Aesthetics – Tactility

——–X———–

5  from right
Usability

—————-X—

8 from left
Complexity

—-X—————

7  from right
 Engagement

————-X——

7 from left

Predictability

—–X————–

8  from right

 Total score = 62/90 = 69%

The  average of multiple  WES © scores can be  used  to provide  overall Experience score for the product.  

The   normalisation data to enable comparision across different products and services  and  indicate the value of the score relative to a benchmark will be published as part of WISE.   Note that without the normalisation data it is possible that all procucts receive scores in the 80’s (a  roof effect)  or below 20 (a floor effect).     Our expert, on-site, Wendy (me)  recommends that prior to the publication of WISE we should assume that any score under 60 is at best a mediocre product or service and any score under 45 is an experience that should be avoided.

For in depth analysis each item should be verified with the  observational measures taking during the use phase and the comments made by the Wendy’s when completing the questionnaire.  

In this example we can clearly see that the tactile aesthetics (score = 5) provided the biggest opportunity for improving Wendy’s experience.   Wendy talked about the radio being a bit too big to put in her pocket,   she liked the bouncy rubber bits but all the little buttons were a bit too small and pointy to enjoy pressing them,   she prefers rubber-buttons (who doesn’t?!) and the industrial-safety feel for portable.    

 

Next Steps

The WES ©  development team haven’t decided whether to gather normalisation data on the vo version, refine the  item labels before collecting normalisation data  or just chuck the semantic differential format and  develop  WES © (v1) based on a creatively cunning perverison of  Kelly’s Repertory Grid technique.  

 

* Use is permitted by prior agreement with the inventor (me,   Wendy!)

** the linguistically pedantic should note that Likert scales tend to use split infinitives such as ‘strongly agree’ which can irritate those completing the scale undermining its efficacy in cases where people choose not to select any options that include split infinitives for purely curmudgeonly reasons.   This makes the scale unreliable for responses from educated people from Yorskhire.

*** The semantic differential is based on the assumption that everyone interprests the scales in the same way.   Unfortunately,   this assumption is not true rendering the WES © useless to anyone other than Wendy.

**** For some products or services predicatability is not a positive experience quality (e.g. games).   Administrators are advised to either scope the item to refer to the service or product  controls.  


2 bits of fabulous banter »

one over the eight

Monday, October 6th, 2008 | tags: ,  |

Bar‘one over the eight’ is defined by a UK phrases website as ‘the drink that renders you drunk’.

My one over the eight is actually number 3 with weak beer   (under 4.5% alc.)   with Liquor my one over the eight is drink number 2.

These non-trivial life-style details have caused the normally supportive Excel to get a mardy on because 9 does not equal 2 or 3.


5 bits of fabulous banter »

where do you want to go tonight…

Saturday, September 20th, 2008 | tags: , , ,  |

Lucid dreaming is apparantly quite rare.    Excel has told me that the  10 friends and family who replied to my emailed question ‘do you lucid dream?’ were all wildly over educated, regularly creative (musicians, poets, designers, teenager), and all except 1 are either  not-married  or over the age of 30.   More specifically:

5/10 people do Lucid dream,  including:

  • 2/5 males
  • 3/5 girls
  • 3/3 immediate relatives

It’s fun,   I’d highly recommend it if you don’t already indulge…


4 bits of fabulous banter »

101 Reading Wendyhome

Sunday, July 13th, 2008 | tags: , , , ,  |

Google analytics reported visitor loyalty (probably unique IP addresses?) for one week in July  2008 as significantly* BIGGER  than  during one week in January  2007.

January 2007 (July 2008)  :

  • 8 (22) visitors visited between 7 and 14 times.
  • 11 (27) visited 15-25 times.
  • 11 (21) visited 26-50 times.      
  • 0   (32) visited 51-100 times.

 Up to 29 (101)  visitors (unique IP addresses)  , other than my good-self, return frequently enough for me to assume they drop-by on a daily basis.      Out of pure, unfettered, cussedness  I am also assuming that at least half of these loyal visitors are naughty, naughty, spam-bots or or other bots of an icky nature, as opposed to pleasantly pert bots.   This assumption  still leaves me  with about 50 regular, daily, visitors who may actually be people!          

 

* Significance in a formal  Statistical sense identified by using Excel’s t-test function for a one-tailed, independent groups t-test that lead to the rejection  of the null hypothesis, h0, p< 0.001

 h0  ‘= there are no more people reading my blog regularly in July 2008  than in January 2007′

The result is statistically very  powerful but I have  low confidence levels in it  because of the low signal-noise ratio introduced by the way the variable (a loyal blog reading person) is operationalised (unique IP address)  that introduces a lot of noise mostly  from  bots.  

Even worse than low statistical confidence is  my  inappropriate test-selection.   Inappropriate because although the data  fulfills some of the assumtions of the independent groups t-test  e.g. parametric,    it is sufficiently naughty to potentially violate other assumptions such as truely independent groups.  

In summary,   we can probably ignore the statistical significance of the numbers because of all the non-number related issues.  

Statistical escapades put aside,  I am still convinced that  the  Wendy House  has quite a few more regular readers now than in January 2007.  


2 bits of fabulous banter »

branding. part 1

Saturday, April 5th, 2008 | tags: , , ,  |

facilitator:   what’s this?

Wendy: an excel pie chart?

facilitator:   anything else?   a branding symbol

Wendy:   errrrrrmmmmm…

facilitator:   Mercedes

Wendy:   I’m a pedestrian

facilitator:   [?????]


what do you think of that »

Excel expounds on decision quality

Saturday, October 27th, 2007 | tags: ,  |

Decision quality is inversely proportional to the rate of decisions made and directly proportional to prior experience of making similar decisions provided the hormone level remains constant which the bugger never does.  


what do you think of that »

Excel explains #6: drinkies and pies

Friday, September 7th, 2007 | tags: , ,  |

OH Look at this!  

Excel is trying to tell me something about pies and drinkies.

I’m not sure what exactly Excel is trying to tell me.    I like green*,   gradual shading,   tea, ale and pie so I’ll  immerse myself in the visual aesthetic of  the pie chart experience and understanding might emerge with time and fermentation.  

Well done Excel,   you surely must be  right.

Previous sporadic entries in this series where Excel produces:

  1. a Laptop purchase decision prediction
  2. Astrological reasons  for why I’m single
  3. explaintion of variable Breaking distances with car colour
  4. Explanaition of why some bloggers get more comments than the :: Wendy House  ::
  5. Scatttered    reasons for why I’m single.

* thanks to Raymond for pointing out the essentialness of the  green-shaded-3D-pie.


3 bits of fabulous banter »

penchant for petite

Wednesday, December 27th, 2006 | tags: ,  |

twenty-third  post in  a  size-ist  Wednesday series  of “why wendy’s single“.    

Reason # 23: penchant for petite

Excel collected evidence on my previous relationships that

  • lasted longer than 1yr
  • lasted less than 1 yr, near misses.
  • didn’t get beyond preliminary dating.  

Based on a chart infested detailed examination of this data Excel has informed me that my relationship success  (lasting for more than 1 year)  predictors include  the boy being under

  • 5’10”  
  • 135lbs
  • 32″ inside leg
  • 32″ trouser waist

According to Excel,    size does matter.   In the US,   boys of these proportions that are also over the legal age  for consenting naughtiness  are not common.      Looks like I’ll have to work on aligning my attitudes with the  ‘big is beautiful’ philosophy or volunteer to take some social deviant treatment lest I  become susceptible to commiting a social  crime akin to another local gal, LeTourneau.        


what do you think of that »

Excel said so. Pluto is unsure.

Wednesday, October 18th, 2006 | tags: ,  |

unlucky thirteenth episode in  Wednesday a highly scientific series  establsihing exactly “why wendy’s single“.    

Reason # 13:   Excel said so. Pluto is unsure.

I decided to consult Excel about the ‘why’ of my singleness.   We put some numbers together and massaged them into many wonderful tables and charts.   Excel said there are  too many Independent variables reasons involved.    The likelihood of these many  independent variables  multi-dimensions aligning like planets*  to produce result in an appropriate boyfriend nearby decreases exponentially with each identified singleness reason, independent variable, dimension  predictor.   These exponential distrubtions align with Excel’s earlier observation that  potential boyfriends are so scattered they are all,  but one, scattered off the plot.    

Eventually Excel told me that it was ‘the way of the world’ that a Wendy should be single.  The  Pluto  world.   Pluto rules my astrological sign.   Pluto has recently been demoted from planetary status.    Pluto’s probably in therapy to deal with the psychological impact of demotion rather than wasting time effecting change in my life.  

Excel concluded by saying it’s  not my fault and I should consider an insurance policy to protect myself from things that are not my fault.  

* Syzygy is apparantly the shortest word including three ys  in the English language.   It’s a new word for my scrabble playing repetoire.


5 bits of fabulous banter »

Excel explains: popular people

Saturday, June 10th, 2006 | tags: , , ,  |

a careful inspection of the chart below reveals some spectacular truths.   For example:

  1. Jenn (Piehole) is on  track to become like Raymond (oldnewthing).   They both have very shiny black hair and tanned complections.   I’d never realised this similarity until Excel pointed it out to me,    but its undeniably true.  
  2. I am going to have to turn into Jen (quarterlife crisis) before I can make headway on being as popular as Jenn.   Jen and I both have fair skin and wear jeans.   It’s striking how Excel can spot these similarities and show you the way.

Excel shows how to become popular

I’m planning to keep consulting with Excel to improve my general popularity level,   eventually becoming like Raymond.   My next move is to get a good tan and maybe some contact lenses to make my eye’s brown.

note: edited to adjust the number of n’s in Jen because I got it COMPLETELY wrong


2 bits of fabulous banter »

braking distances vary with car-colour

Thursday, March 16th, 2006 | tags: ,  |

This Excel bar chart told me that silver cars have superior braking-distances to brown cars when driving behind LooSea.  

Who would have guessed?

Excel bar chart of braking distances by car colour


what do you think of that »

potential boyfriend scatterplot

Sunday, March 12th, 2006 | tags: ,  |

They all scattered off the plot.   Except one

Excel Chart of one boyfriend on a Scatterplot  


2 bits of fabulous banter »

Excel told me to do it

Tuesday, March 7th, 2006 | tags: ,  |

This psychic chart says that I will buy a new laptop in the 3rd week of March after a tax rebate.   It predicts I will be happy and not worry about maintaining a terminal-Tinkerbell.

Excel spreadsheet says buy a laptop

It’s amazing how clever Excel is at telling us the way things will be.  

I call it the ‘Excel Oracle Effect” (eOe).     Excel has predicted that I will be using it  to solve  73% of the tricky questions in my life.    The first 9% of these will be covered in the  next project:    a  ‘boyfriend application generation and classification’  chart.    

Pie chart or Scattergram?   What do you think?


4 bits of fabulous banter »