The 27th Annual Spring Conference will be a remote conference.
Having seen that the burden of travel to South Lake Tahoe has been a barrier
to attendance for many of our colleagues over the years, the decision was made
to make this spring's conference a remote one. Please join us at the Spring
Conference.
Please check back here again in the future for updated information.
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Conference Registration
Registration for the conference closed at 5 pm, April 26, but it is not too
late to
join CMC3 or make a donation.
Remember, the funds raised are not only used to pay conference costs, they also
are used to fund scholarships for community college students.
Keynote Speaker: Dr. Patrick Phillips The Power of Chance in Evidence-Based Medicine
The COVID-19 pandemic has been a reminder for all of us that disease
affects every aspect of life and decisions about how best to treat and
prevent disease are rarely straightforward. Medical statisticians are
tasked with the job of designing and analyzing clinical research studies
to generate the best evidence to support medical decisions.
In the era of Big Data, Artificial Intelligence, Massive Social Networks,
and Quantum Computers, it is surprisingly still an invention from the
early 20th Century that given the most reliable evidence for medical
decision-makers: The Randomized Controlled Trial. What gives this type
of research study its power is nothing more sophisticated than the tossing
of a coin.
In this
presentation (Powerpoint),
I will show why this is the case and talk about
how simple statistical methods remain at the heart of Evidence-Based
Medicine.
As part of the UCSF Center for Tuberculosis, Dr. Patrick Phillips is an
Associate Professor in Residence in the Division of Pulmonary and Critical
Care Medicine with a secondary appointment in the Department of Epidemiology
and Biostatistics. Prior to 2017 he was senior statistician at the MRC
Clinical Trials Unit at UCL in London.
The objective of Dr. Philips' research is to design, implement, and
optimize clinical trials for new treatments for tuberculosis in order to
deliver safer and more efficacious regimens for patients. Dr. Philips leads
the Trial Design and Statistics core of the PanACEA consortium evaluating
novel regimens for the treatment of TB, serves as consultant statistician
for the US CDC-funded TB Trials Consortium (TBTC), and is a member of the
ACTG TB Transformative Science Steering Group. Dr. Philips has worked
on late-phase clinical trials in tuberculosis for more than fifteen
years, most recently as trial statistician in the STREAM Stage 1 and the
TBTC/ACTG S31/A5349 phase III trials and vice-chair of ACTG A5414
SPECTR-TB. Ongoing methodological areas of interest include the evaluation
and use of surrogate endpoints, the conduct and analysis of non-inferiority
trials and trial design with a focus on adaptive designs. Dr. Philips
is an associate editor for the journal BMC Trials.
Saturday Student Speaker: Forrest Day Optimizing Solar Energy Production With Python
An overview of a method for finding the optimal direction of a solar panel.
This method, based on vectors, combines empirical data with an established
sun position algorithm to develop a single model for power output. Numerical
integration is then used to determine which orientation produces the most
energy.
Forrest is a student at Modesto Junior College with plans to study
electrical/computer engineering or computer science. While he enjoys learning
about all STEM fields, his longstanding interests are electronics and
programming. As such, his hobbies include anything from amateur radio to
video game modding.
Schedule Saturday, April 29
9:30 - 9:40 am
9:40 - 10:20 am
Presenter: Forrest Day, Modesto Junior College
Faculty Mentor: Yolande Petersen, Modesto Junior College
An overview of a method for finding the optimal direction of a solar panel. This method, based on vectors, combines empirical data with an established
sun position algorithm to develop a single model for power output.
Numerical integration is then used to determine which orientation produces
the most energy.
10:20 am - 10:40 pm
10:40 - 11:45 am
Room 1: Using RStudio Cloud for an Introductory Statistics Class
Presenter: Lori Lewis, Santa Rosa Junior College
Come code with me! This is a general basic introduction to using
RStudio cloud. I will give information on how to open an R script.
I will show you how I use RStudio instead of a graphing calculator for
my introductory statistics class. We will work together in the console.
I will share a pdf of some basic code used in an introductory statistics
class that you can copy and paste to make different calculations such
as mean, standard deviation, etc.
Room 2: Cultural Compentency: Providing Equitable Math Instruction Through Cultural Relevance
Presenter: Dr. India White, Big Ideas Learning, LLC
Scores from the National Assessment of Educational Progress suggest that
if current educational practices remain the same, the achievement gap
between Caucasians and African descent learners will be eliminated
around 217 years. To close the gap, teachers must be equipped with
methods to conduct equitable instruction that is culturally relevant.
11:45 am - 12:00 pm
12:00 - 1:00 pm
Room 1: Hardy, Ramanujan, Cormac McCarthy, and Taxicab Numbers
Presenter: Pat McKeague, MathTV
The story of Ramanujan and Hardy and the taxicab number, as told by the
novelist Cormac McCarthy, gives us an interesting problem to bring into
our courses. And it can be used to liven up dull dinner conversations.
I know because I have done just that.
Room 2: APEX: Python Activities for Statistics Courses
Presenter: Lily Lum and Matthew Bertens, City College of San Francisco
Are you interested in incorporating Python programming in your statistics
course? A group of math and biology faculty at City College of San
Francisco are collaborating with San Jose State University to embed
Python-based activities in their introductory statistics and biology
courses. The vision of SJSU's APEX (Applied Programming Experience)
program is to "expose diverse students to computer programming.
These experiences are intended to de-mystify computer programming and
help students better understand the relevance of programming to their
interests, in turn helping to inform future education and career
choices in this increasingly digital world." We will share our
experiences on how we implemented some Python-based activities in our
classrooms.
The COVID-19 pandemic has been a reminder for all of us that disease
affects every aspect of life and decisions about how best to treat and
prevent disease are rarely straightforward. Medical statisticians are
tasked with the job of designing and analyzing clinical research studies
to generate the best evidence to support medical decisions.
In the era of Big Data, Artificial Intelligence, Massive Social Networks,
and Quantum Computers, it is surprisingly still an invention from the
early 20th Century that given the most reliable evidence for medical
decision-makers: The Randomized Controlled Trial. What gives this type of
research study its power is nothing more sophisticated than the tossing
of a coin.
In this presentation, I will show why this is the case and talk about
how simple statistical methods remain at the heart of Evidence-Based
Medicine.
