Data is a collection of facts, such as values or measurements. It is useful to design for humans and their various needs and activities if data is correct , adequate , relevant and its significance understood by designers.

1. Use of Data
& percentiles
………
for design
Ar. Surashmie Kaalmegh
Associate Professor
BID ,LAD College , Nagpur

2. We use data for design
……..

3. What is Data?
 Data is a collection of facts, such
as values or measurements.
It can be numbers, words,
measurements, observations or
even just descriptions of things.
Qualitative vs Quantitative
 Data can be qualitative or
quantitative.
 Qualitative data is descriptive
information (it describes something)
 Quantitative data, is numerical
information (numbers).
Discrete data can only take certain
values (like whole numbers)
Continuous data can take any
value (within a range)

4.  Family size
 Class size
 No. of cars owned
 No of languages
known
 No of students sleeping
…….
 Ex.: 1,2,3,4,5,6,7,….
 Age
 Weight
 Time taken to go to school
 Temperature
 Calories in a
hamburger…………..
 Ex.: 2 hrs & 30 mins &12
sec or 9.22 Kgm Or 3 yrs.
4 months & 2 days .
Continuous DataDiscrete Data

6.  People come in all
shapes and sizes

7. Body types : Somatotype
There are three extremes of body types.
William Sheldon’s system

10. Is it enough or
adequate?????

11. What is a
percentile?
 In statistics, a percentile (or
centile) is the value of a
variable below which a certain
percent of observations fall.
 Example: the 20th percentile
is the value (or score) below
which 20 percent of the
observations may be found.
The 25th percentile is also
known as the first quartile
(Q1),
the 50th percentile as the
median or second quartile
(Q2),
and the 75th percentile as
the third quartile (Q3).

12. Measuring a population
Of
1,2,3…….112,113.

14. Myth of designing for the "average"
person
 Since there are no people whose body
dimensions are all at the 50th percentile.
 Body dimensions aren't linearly correlated so
people with short arms don't necessarily have
short legs, etc.
 While the use of the 5th and 95th percentiles on
one body dimension may exclude 10% of the
population, the use of these on 13 dimensions
actually can exclude 52% of the population.

15.  The 5th and 95th percentiles are the lines that set of the "edges of the
curve" in a distribution over a bell curve. If you draw the bell, and
mark the 5th and 95th percentile spots, those marks separate the bulk
of the curve from its edges. The 5th percentile sets off the bottom
edge and the 95th percentile sets off the top edge of the curve.

16. Percentile & Averages :

17. Measuring human
beings

18. Design approaches:
 'Middle-out' anthropometric
design favours the 'average'
person, fitting people within
a certain range to either side
of the 50th-percentile mark.
 An 'ends-to-the-middle' design
approach optimises fit for people
at the outskirts of the
anthropometric curve as well as
those at the peak.

20. Ego design & Pro crustus

21. Design for tall & short

22. Design for adjustable

23. Design for more

24. Design for all

25. Anthropometry:
 Anthropometry is the study
of human sizing - the
dimensions of the different
parts of the body.
 The simplest and most
common form of
anthropometry is Static
Anthropometry, where
people are measured in
unmoving, defined
postures.
What Is Anthropometry?
Anthropometry is the
measurement of the size,
weight, and proportions of the
human body.
For all studies we take simple
body measurements
such as weight, height, hip and
waist circumferences

27. Static & dynamic measurements
STATIC MEASUREMENTS:
These are standard measurements of
human body when standing , sitting etc.
Body parts remain stationary so easy to
measure length, heights, widths , thickness
depths etc. ……….. Example standing ,
sitting or sleeping.

28. Dynamic
Measurements
Are Needed If These Task are to
be
Performed Comfortably By The
Users
Hence a series of measurements
are
Required to understand in how
many ways
A task may be accomplished . As a
human tendency…………
normally and specifically

29. DYNAMIC POSTURES AND
MEASUREMENTS

30. Sampling
in a survey
 Surveys can only measure
a sample of the people
they are interested in.
 Samples sizes range from
10's to 1000's, depending
on the scope and purpose.
 In order to have a good
match between the sample
and the 'population',
generally a mix of random
and targeted selection is
used.
 To make sure for
example that a
minority group has
enough
representation.
 The larger the
sample, the less
likely it is to have
an unexpected bias.

31.  It's a characteristic of
human variation that
most people are near to
the average, then there
are proportionately
fewer and fewer people
towards the extremes.
 In ergonomics it is
normally the extremes
that we are interested in,
because that is where
any given aspect of a
design will start to "not
fit".
 The percentage of
people who are
smaller than a given
size is called a
"percentile", and
typically designs are
specified to fit from
1st/2nd/5th
percentile to
95th/98th/99th.

32.  Because the actual size of
(say) the 2nd percentile is
determined by the size of
only 2 percent of the
sample, sample size has a
dramatic effect of the
reliability of the resulting
data - in a sample of 50 the
smallest subject is the 2nd
percentile, so if that
individual happens to be
particularly small, or the
same size as the 2nd
smallest,
 THUS IT MAY NOT BE
SUCCESSFUL .
 It is difficult to recruit
volunteers who are
extremely large or small,
and in general government
health surveys are much
more successful at this than
commercial clothing
surveys. For that reason
clothing surveys
characteristically show
people to be taller &
lighter than do government
surveys .

33. Testing
 It's never safe to go
directly from
anthropometric data
to the finished
design. Any dataset
has an error rate, and
also the way the
measurement was
taken may not relate
all that well to the
way people will fit
into and use your
design in real life.

35. What percentiles to use?
 Once you've identified the right
anthropometry data, and
understood the measurement,
you have to decide what
percentiles to design for. It's
best to see this question in terms
of excluding a percentage of
users from the design, and then
formally to consider:
 What happens for excluded users
- discomfort, inconvenience,
danger etc? The more severe the
consequences, the fewer
exclusions you can allow.
 Do the excluded users expect
this (e.g. a very tall person may
be used to being cramped in an
economy aircraft seat, but not in
a luxury car)?
 Can you warn the excluded
users?
 Are there degrees of
exclusion that you should
consider, beyond the basic
target? For example, set
95th percentile for one
non-critical dimension and
99th for another that is
more crucial.
 How much would it cost to
increase the design range?

38. With an aid……

40. How to measure ?

52. So when designing a
product always
consider the most
suitable database …..