MATH & COMPUTER SCIENCE COLLOQUIA

TENTATIVE SCHEDULE

Winter 1998:
 
 

DATE

TIME

LOCATION

SPEAKER

TITLE
Thursday, March 12 3:00  pm  WS 162 Dr. Sujay Datta (NMU) "Statistics: Taming the Uncertain and Claiming the Truth"   (abstract)
Tuesday, March 17  10:00 am   WS   164 Mr. Brad Kowalski (Marshfield Clinic)   "Trends in the Field of Computers - 1998"  (agenda)
Tuesday, March 17 11:00 am  WS  164 Mr. Brad Kowalski 
(Marshfield Clinic)		 Company Information Session
Tuesday,   March   31 3:00 pm   WS 162 David Powers, Thomas Pietro, and Brian Larson (NMU) "REAL WORLD EXPERIENCES:  Computer Science Internships"  (abstract)
Tuesday,   April    7 2:00 pm  WS 162 Don H. Faust "Logics of Evidence:  Motivation and Mathematical Structure"  (abstract)
(* to be announced)

Please contact Jeffrey Horn for questions on this papge (jhorn@nmu.edu).  (full contact information)

Fall 1997:        (old schedule, for historical info)
 


 

ABSTRACTS

"Statistics: Taming the Uncertain and Claiming the Truth"
Dr. Sujay Datta
ABSTRACT: Sceptics deride it by saying: 'Lies, damn lies and statistics'!
Enthusiasts glorify it by saying :'Truth, absolute truth and statistics'!
So what is it really? A clever device to mislead people or a useful
toolbox to dig out the truth? As Sir Ronald A. Fisher, the 'father of
statistics' once said, 'Statistical science is the peculiar aspect of
human progress which gave the 20th century its special character;...it is
to the statistician that the present age turns for what is most essential
in all its more important activities'. We have always known from our
conventional wisdom that 'one should not count the chickens before they
are hatched', or that 'to guess is cheap but to guess wrongly may cost
a great deal'. It is the science of statistics that legitimizes attempts
to count unborn chickens (i.e. to predict the uncertain future) by
quantifying the extent of uncertainty in it, or in the second case,
facilitates damage-control by quantifying the error involved in the wrong
guess. After all, 'Life is the art of drawing sufficient conclusions from
insufficient premises' (Samuel Butler), and statistics is the
indispensable 'paintbrush' for this art.
 In this presentation, we will try to analyze the logical basis of
statistics, and give a series of interesting examples (of considerable
practical or historical significance) where statistics was successfully
used to solve challenging problems.

* * * * * * * * * * * * * * * * * * * * * * * * * *

 "Trends in the Field of Computers - 1998"
Mr. Brad Kowalski    (Laboratory Information Systems, Manager, Marshfield Clinic, WI)

        Quick Background
        Trends in Computer Hardware
        Trends in Operating Systems
        Trends in Languages
        Major Industry Problems
        How Computers relate to Healthcare
        Questions

 * * * * * * * * * * * * * * * * * * * * * * * * *

 "REAL WORLD EXPERIENCES:  Computer Science Internships"
Dave Powers, Tom Pietro, and Brian Larson   (Mathematics and Computer Science Department,  NMU)

 Dave Powers, Director of the Computer Science Internship Porgram, will explain the benefits and requirements of the Computer Science internship program.  Information will be provided on past internships and how a Computer Science student can get involved in the program.

Tom Pietro,  a senior and Computer Science major, will discuss his internship experience at the Champion Paper Mill in Quinnesec.

Brian Larson, also a senior and Computer Science major, will present interesting perspectives regarding his internship at IBM in Rochester, Minnesota.

Time will be provided for questions and answers.  All majors and minors in Computer Science, Computer Programmin, and Computer Information Systems (CIS) are encouraged to attend.

 * * * * * * * * * * * * * * * * * * * * * * * * *

 "Logics of Evidence:  Motivation and Mathematical Structures"
Dr. Don H. Faust    (Mathematics and Computer Science Department, NMU)

Classical logic is a logic for the representation and processing of knowledge which is both confirmatory and absolute, and hence, is a logic which is in fact inadequate for dealing with those many circumstances when our knowledge is evidential.  A logic attempting to deal with such evidential knowledge, called Evidence Logic, will be described and then analyzed in terms of its mathematical structure.
 


(last updated 3/30/98, Jeff Horn)