Page 312 - Special Topic Session (STS) - Volume 4

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major or university departments is becoming questionable. But more
importantly, is the content of statistical education. The important question that
need to be addressed is how to draw the balance while preparing students to
the jobs of the future between a) what is currently taught to acquire a strong
analytical and theoretical grasp of statistics and b) what should be taught to
increase employability of newly graduate. More segmented recommendations
should be thought of to differentiate between what should be done (if any) in
statistical education for undergraduate statistical major, for undergraduate
statistical minor and for graduate statistical program.
Given the pace of change associated with the fourth industrial revolution,
quick fixes need to be introduced to statistical education including:
a) Introducing software for analyzing big data and for data visualization,
b) Developing joint academic programs that combine statistics and
information technology,
c) Designing more state-of-the-art courses that look at data collection
and data analysis in a more comprehensive way that take into
consideration sources of big data,
d) Establishing protocols to foster the use of big data in research,
e) Exposing students to internet of things, artificial intelligence, and, how
they will become a source of data, and,
f) Creating opportunities for students majoring in statistics for summer
training or internship in information technology companies.
These fixes should not refrain the statistical community from making more
strategic reform in teaching statistics.

Statistical national systems/offices – Official statistics will face the fact that
Bureau of Statistics will not remain as “the” major data production
organizations and should avoid ignoring other not-state actors who are mainly
private sector companies. These companies might be after business
opportunities in creating or analyzing big data or might own big data as a bi-
product of new technologies associated with the fourth industrial revolution.
In the era of data science, the following suggestions need to be taken into
consideration:
a) Adopting an inclusion approach to engage owners and users of big
data within the national statistical systems,
b) Changing the culture of statisticians from considering big data a threat
for “good data” to an opportunity to improve the quality of big data
and to reduce its limitations, as combining big data with traditional
data can increase the timeliness and level of segmentation of the data.
c) Reforming the content of official statistics, such reform might include
(but not limited to) transportation statistics to reflect volume of
transportation network companies (Uber), expenditure to reflect
national and international online shopping, foreign trade statistics to

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