A Comprehensive Guide for Public Speaking at Scientific Conferences

Introduction

I served as a judge for some of the student presentations at the 2016 Canadian Statistics Student Conference (CSSC).  The conference was both a learning opportunity and a networking opportunity for statistics students in Canada.  The presentations allowed the students to share their research and course projects with their peers, and it was a chance for them to get feedback about their work and learn new ideas from other students.

Unfortunately, I found most of the presentations to be very bad – not necessarily in terms of the content, but because of the delivery.  Although the students showed much earnestness and eagerness in sharing their work with others, most of them demonstrated poor competence in public speaking.

Public speaking is an important skill in knowledge-based industries, so these opportunities are valuable experiences for anybody to strengthen this skill.  You can only learn it by doing it many times, making mistakes, and learning from those mistakes.  Having delivered many presentations, learned from my share of mistakes, and received much praise for my seminars, I hope that the following tips will help anyone who presents at scientific conferences to improve their public-speaking skills.  In fact, most of these tips apply to public speaking in general.

I spoke at the 2016 Canadian Statistics Student Conference on career advice for students and new graduates in statistics.

Image courtesy of Peter Macdonald on Flickr.

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Maximizing Your Learning Potential at Professional Conferences – A Detailed Guide

Introduction

During last summer, I attended the 2016 Annual Meeting of the Statistical Society of Canada (SSC).  I spoke on the career-advice panel at the 2016 Canadian Statistics Student Conference (CSSC), and I met some colleagues and professors to share ideas about our mutual interests in statistics, statistical education, and the use of social media to promote statistics to the general public.

From observing and talking to many students at this conference, I realized that most of them did not use it effectively to maximize their learning potential.  A conference like this is a great opportunity for networking, career development, and – eventually – finding a job, but I suspect that most statistics students do not comprehend the depth of its value, let alone how to extract it.  Thus, I’m writing this advice column to help anyone who attends a professional conference.

Image courtesy of Rufino from Wikimedia Commons.

Objectives

Most statistics students want to succeed academically and find a job after completing their education – that job could be within or outside of academia.  Thus, at any professional conference, they should have the following objectives:

  1. To learn new ideas in your fields of interest
  2. To meet others who share your professional interests
  3. To learn soft skills from veterans in your industry for developing your career
  4. To build valuable relationships in your professional network

Unfortunately, based on my anecdotal observations, many students in statistics, math and science don’t seem to grasp Objectives #3-4.  These students tend to be passive in their attendance and shy in their participation.  When they do try to pursue Objectives #3-4, they are often unprepared and do not take advantage of all of the learning opportunities that are available to them.

The first step in maximizing your learning potential at a professional conference is recognizing that it takes preparation and hard work.  To do it well, you need to take all 4 objectives seriously and practice them frequently.  Attending a professional conference is a skill, and developing this skill requires thought and effort.  It involves much more than just showing up, talking at your turn, and listening at all other times.

Hopefully, the rest of this article will help you to develop this skill in an intelligent way, but you must realize that there is no substitution for hard work.

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Career Advice Panel – Statistical Society of Canada’s Annual Student Conference

I am excited to go to Brock University in St. Catharines, Ontario, and speak at the Statistical Society of Canada‘s (SSC’s) Annual Student Conference on Saturday, May 28, 2016!  This one-day conference will be a chance for statistics students from all over Canada to share their research with each other, network with industry professionals, and get career advice from the career advice panel.  I will be one of 3 speakers on this panel, and I look forward to sharing my advice and answering the students’ questions.  Read the Final Program Booklet to get the schedule and learn about the backgrounds of all speakers at this conference.

If you will attend this, conference, please feel free to come and say “Hello”!

ssc-logo

This event will occur before the 2016 Annual Conference of the Statistical Society of Canada.

 

Spatial Statistics Seminar in Toronto – Tuesday, May 21, 2013 @ SAS Canada Headquarters

I volunteer with the Southern Ontario Regional Association (SORA) of the Statistical Society of Canada (SSC) to organize a seminar series on business analytics here in Toronto.  The final seminar of the 2012-2013 series will be held on Tuesday, May 21 at SAS Canada Headquarters.  If you’re interested in attending, please email seminar.sora@gmail.com with the following subject to get a confirmation: Registration: Seminar by BBM Canada 

Speakers: Derrick Gray and Ricardo Gomez-Insausti – BBM Canada 

Title: The Power of the Latitude and Longitude – An Application of Spatial Techniques to Audience Measurement Data

Date: Tuesday, May 21, 2013 

 

Location: 

SAS Headquarters Office 

Suite 500

280 King Street East

Toronto 

 

Networking: 2:00 – 2:30 pm 

Introductory Remarks: 2:30 – 2:45 pm 

Seminar Time: 2:45 – 3:45 pm 

Discussion and Networking: 3:45 – 5:00 pm 

Read the entire post to see the abstract and the speakers’ biographies.

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Presentation Slides: Machine Learning, Predictive Modelling, and Pattern Recognition in Business Analytics

I recently delivered a presentation entitled “Using Advanced Predictive Modelling and Pattern Recognition in Business Analytics” at the Statistical Society of Canada’s (SSC’s) Southern Ontario Regional Association (SORA) Business Analytics Seminar Series.  In this presentation, I

– discussed how traditional statistical techniques often fail in analyzing large data sets

– defined and described machine learning, supervised learning, unsupervised learning, and the many classes of techniques within these fields, as well as common examples in business analytics to illustrate these concepts

– introduced partial least squares regression and bootstrap forest (or random forest) as two examples of supervised learning (0r predictive modelling) techniques that can effectively overcome the common failures of traditional statistical techniques and can be easily implemented in JMP

– illustrated how partial least squares regression and bootstrap forest were successfully used to solve some major problems for 2 different clients at Predictum, where I currently work as a statistician

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