English for Specific Purposes: Course Outline & Lecture Notes

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ECOLE SUPERIEURE D’INFORMATIQUE ET DE GESTION-
ESIG GLOBAL SUCCESS
ENGLISH LECTURE FOR SPECIFIC PURPOSE
COMPILED BY
Sir. Julien HOUNGBADJI.
ENGLISH TEACHER (General and specific purpose)
AVAILABLE ON: ([phone]/ 99 76 06 76.
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SEMESTER: 4
Academic year: 2024-2025
COURSE OUTLINE
I- Features characteristics
II- Reading of
a. Statistics
b. Calculations
c. Measurements
d. Dimensions

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FEATURES CHARACTERISTICS
Industrial computing encompasses the use of specialized computers and
computing systems that are designed specifically for industrial applications.
Unlike standard commercial computing systems, industrial computers are
engineered to withstand the challenging conditions commonly found in various
industrial environments, such as extreme temperatures, dust, moisture, and
vibrations.
Key Characteristics and Features of Industrial Computing:
Robust and Durable: Industrial computers are built with rugged materials and
are often enclosed in a protective casing, making them resistant to dust,
moisture, and other environmental factors.
Extended Temperature Range: These computers can operate reliably under a
wide temperature range, from freezing cold to scorching heat.
Shock and Vibration Resistance: Industrial computing devices are built to
endure mechanical shocks and vibrations, a frequent condition in industrial
settings.
High Reliability: Due to the critical nature of many industrial applications,
these computers are designed for maximum uptime and reliability.
Customizable: Industrial PCs often come with options for customization to fit
specific requirements, such as additional I/O ports, specialized graphics
capabilities, or added storage.
Scalability: As industrial operations grow or evolve, industrial computing
systems can be expanded or upgraded to meet increased demands.

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Specialized Input/Output (I/O) Ports: Many industrial computers offer a
range of specialized I/O ports tailored to connect to a variety of sensors,
actuators, and other devices typical in industrial settings.
Fanless Design: Some industrial computers are designed without fans,
eliminating potential points of failure and ensuring they can operate in
environments where dust and particulates are a concern.
Long Product Lifecycle: Industrial PCs usually have a longer lifecycle than
consumer-grade computers, meaning they remain in production and support for
a more extended period, essential for critical systems where continuity is vital.

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STATISTICAL COMPUTING
Computational statistics or statistical computing focuses on the bond between
statistics and computer science to transform raw data into knowledge. You could
consider it to be the interface between statistics and computer science.
Computational statistics is a field of computational science that focuses on the
mathematical science of statistics. The field of computational statistics is
growing at a tremendous pace and there are a large number of advancements
being made in it. This has led to the statistics community urging that a broader
concept of computing needs to be included in the curriculum as a part of general
statistical education.
Environment for statistical computing
When speaking about an environment for statistical computing, it is necessary
always keep in mind following points.
1. Most important improvements in the statistical computing always profited
much more from progress in “general computing” and hardware
development than from progress in mathematical statistics.
2. The environment for statistical computing should offer not only its
statistical part but also to facilitate other tasks as storing and/or retrieval
of data from internal and external sources, report writing as well as other
publication activities, easy communication with colleagues and clients,
etc.
3. Systems should be open both as regards the changing interests of users
and the growing spectrum of tasks to be solved.
4. Last but not least, computers and operation systems are changing in
regular cycles and it takes for a system more than one cycle to reach
maturity. Unfortunately, after several cycles almost every program or
system is swept away by progress in technical and knowledge levels.

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Computational statistics, or statistical computing, is the interface between
statistics, computer science, and numerical analysis. It is the area of
computational science (or scientific computing) specific to the mathematical
science of statistics. The terms computational statistics and statistical computing
are often used interchangeably, although Carlo Lauro, a former president of the
International Association for Statistical Computing, proposed to make a
distinction between them. More precisely, he defined statistical computing as the
application of computer science to statistics, and computational statistics as
aiming at the design of algorithms for implementing statistical methods on
computers, including the ones unthinkable before the computer age.
What are the conflicts between statisticians and computer
scientists?
Computer scientists and statisticians tend to have complaints regarding each
other’s’ disciplines. Here are some of these complaints.
Complaints that computer scientists make regarding statisticians
 Statisticians lack in programming sophistication.
 They value standard techniques rather than innovative techniques.
 They care more about theory than about solving real-world problems.
Complaints that statisticians make regarding computer scientists
 They do not have the statistical foundations for data collection and
analysis.
 They do not consider the objectives as much as they should.
 They do not care for the representative nature of data.
What is R?
R is a language and an environment that is used for statistical computing and
graphics. It has similarities with the S language and environment developed at
Bell Laboratories by John Chambers and colleagues. R is a GNU project that
can be considered to be a different implementation of S. Even though there are