Developing Comprehensive National Statistics

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‫اتحــــــــــــادية‬ ‫هيئــــــــة‬|Federal Authority
National Statistics
Presented by Dr. Ali M. Al-Khouri
In: Abu Dhabi Statistics Conference 2013
12-13 May 2013 | Ritz Carlton | Abu Dhabi | UAE
Exploring the Role of Modern
Identity Management Infrastructure
in Developing a Comprehensive

• Introduction: Statistics .. A Definition
• Statistics Scope and Boundaries
• Data and the Element of Uncertainty
• Modern Identity Management Systems
• Concluding Remarks
Agenda

Agenda

Statistics: a classical definition…
A mathematical subject dealing with
“the collection, tabulation, analysis, interpretation
or explanation, and presentation of data”.….

• A science in the realm of
mathematics.
• Deal with massive data,
collate into meaningful
information
• Historical evidence
• Confident predication
with a degree of
certainty.
Statistics: is a science ..

• explosive growth in the amount of data created in
the world, both structured and unstructured.
• It continues to accelerate and surprise us in terms of
sheer volume.
Social media
is producing a
tremendous
amount of
new data.
Information Age

Climate Change
every day, we create
2.5 quintillion bytes of data ..
(2,500,000,000,000,000,000)
90% of the data in the world
today has been created in the last two
years.
IBM Report
We are truly in a
digital explosion era!
The Age of Big Data ?

• Barrage of data
streamed at us!
• Showering us with
massive rain of data?
• Question: how can we
create a meaningful context?
• Can we filter this stream into something
more structured so that we can make
sense of what we have and thus present
it in a manner that is useful?
The Complexity of Context ..

Agenda

Statistics helps us in structuring the data into matrices
and truly brings us closer to a deeper understanding
that is hidden in the numbers associated with the data.
enhance
understanding
& constitute
knowledge
(meaningful
information).
Statistics Value

• Boundary or
constraints under
which a Statistical
Analysis is reported
Scope of Statistics

Population in statistical terms
is the key subject of interest,
specifically in demographic
analysis.
The People Dimension

Describes the
characteristics of a
product or process
using information
collected on it.
Hypothesis formation
stage where
“statistical thinking”
plays a major role.
Draw conclusions on
unknown process
parameters based
on information.
Uses probability,
leading to either a
confirmation or
rejection of the
hypothesis.
Statistics spans over several distinct phases
Scope of Statistics

Analytical with Validation of the Population
“Scale Up” or the Extrapolation Analysis.
Scope of Statistics

Here comes the
importance of the
Data and Data
Collection. Depending on the size of the population, statisticians would
draw a sample from the population for the required analysis.
Importance of Data (Collection)

Agenda

www.emiratesid.ae © 2013 Emirates Identity Authority. All rights reserved 18
Data as the lowest level of abstraction
Data in statistics is an abstraction of the
population and has three levels- raw.
Knowledge at the highest level.
Information at the next level
Information
Data in Statistics

Data abstraction depends on the
scheme of Data Collection ..
Information
Data in Statistics

Information
Data in Statistics

• Statistics by definition
is an approximation.
• It is an estimate
• It is based on probability
• Utilizes distribution analysis
• Since we use hypothesis
and sampling, there are
always variables that
depend on assumptions
Uncertainty in Statistics

Agenda

• Many government
launched modern
identity management
infrastructure.
• Use of advanced
identification and
authentication
technologies.
Modern Identity Management Systems

Bi-Annual IMAGE Users Group Forum | Paris, France 15-18 April 2013
‫اهلوية‬ ‫بطاقة‬

Modern Identity Management Systems
Formation &
Development
Enrolment
June 2005 Dec 2012
99%
2000-2005
Enrolled
Population

Government Collaboration
Keeping Population Register up to date
Support Decision Making
Integration Platform

Integration Platform Architecutre

Examples of Statistical Analysis
y

(Un)Certainty in Statistics
The base of statistical
analysis:
• Confidence Interval:
provides the
measure of certainty
• Probability:
provides the
measure of uncertainty

Statistical Analysis of Population
• Function of considered variables and
relationships.
• Bound by the Confidence Interval (CI) and
the Probability (P) of the occurrence of an
event in the population.
Statistical Analysis =
f{ Variables, Binomial relations, CI, P}

Statistical Analysis of Population
• There is a limit to how true is the analysis
• This limit is defined by the Probability and the
Confidence Interval.
• Probability could be 100% (1) but the true
limit is the Confidence Interval (CI).
Statistical Analysis =
f{ Variables, Binomial relations, CI, P}
limit P-->1 f(Statistical Analysis)= CI

CI and P: Accuracy vs Precision of Statistical Analysis
high CI would
provide an
analysis with
higher precision.
i.e.,
(reproducibility)
of a given
measurement

higher
probability
would provide
an analysis with
higher accuracy
i.e., deviation
from the
accepted value

combination
of CI and P
determine the
value of a
Statistical Analysis.

Statistical Analysis = f{ Variables, Binomial relations, CI, P},
limit P-->1 f(Statistical Analysis)= CI
As CI ,,,,,, f(SA)
since limit P1 f(Statistical Analysis) CI
Corollary of the above
Role of Modern Identity Management Systems
pushing the CI higher

• Increase the
Confidence Interval
• Improve the Probability
• Enhance the Analysis
• Reduce Uncertainty
• Reinforce Predictability
• Exalted Data Collection
from qualified data.
Role of
Modern
Identity
Management
Infrastructure
Role of Modern Identity Management Systems

Quality of Data in Statistics

Agenda

• Statistics need to be viewed as a critical
approach to building Knowledge and supporting
social, environmental, and economical
development.
• It should also be viewed in a
framework of 3E’s: Efficiency,
effectiveness, and efficacy.
Concluding Remarks

• National statistics should be evaluated based on how
effective, efficient, and efficacious they are, in terms
of how well they support and strengthen national
capacities in different fields.
Concluding Remarks
speed & accuracy of
government decisions
ability to
forecast
cut costs
save energy
Improving public services
optimise infrastructure
enhance citizens
quality of life
reduce environmental
footprints
fuel innovation
development of diverse
sustainable economic growth

Concluding Remarks
$300 billion
potential annual value to US
healthcare.

• Many national statistical systems are not able to
effectively meet data demand.
• Constraints include: inadequate institutional & human
capacities, infrastructure, funding, etc.
Challenges …

Shortage of Skills
By 2018,
United States will face
shortage of around
2 million
managers and analysts
with know-how to
create and use data to
make effective decisions.

• International pressure to form higher quality
government statistical information.
Data Quality Challenges

Change ..
• Current strategies and approaches are
likely to change.
• Governments will be forced to re-examine
their traditional systems and consider new
ways and approaches to statistical
analysis, and use of Big Data.

Read our recent research from:
http://www.emiratesid.gov.ae/ar/media-center/publications.aspx
More Information:

Thank You
Dr. Ail M. Al-Khouri
Director General
Emirates Identity Authority
United Arab Emirates
ali.alkhouri@emiratesid.ae
www.emiratesid.ae
“Data is a new class of
economic asset,
like currency and gold.”
World Economic Forum 2012

Developing Comprehensive National Statistics

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