Allan, et al -
Nice idea! Saw your message right after I came out of class and
should have responded then when it was fresh. This was day 9 of a
42 class semester and we're finishing up the chapter on descriptive
statistics/graphics (after initial classes on data production,
sampling, experiments). First exam is later this week and first
project (describing their own dataset) is also due at the end of
the week.
Today's topic was least squares regression (after doing
scatterplots and correlation last class). Started with a Fathom
demo where students put a movable line on a scatterplot to show the
trend (we meet full time in a computer classroom), had Fathom show
the "squares" and find SSE to see whose line was best. Then let
them move their lines around to try to lower SSE until they found
essentially the least squares line.
Once they saw how to find the fit automatically in Fathom we
looked at several situations: Hgt to predict Wgt (interpreting the
slope), population of countries to predict land area (showing
influential points/outliers), presidential approval rating as a
predictor of election margin, page number in Consumer Report Guide
to predict fuel capacity of a car (no relationship). They then did
another Fathom demo, dragging a point around to see the effect on
the least squares line, especially when the the point became very
influential.
We finished up by introducing r^2 as the proportion of
variability in response explained by the predictor. This involved
one more Fathom demo where they made the movable line horizontal to
see that the "best" constant is the mean, giving the total
variability as its sum of squared errors, then found the
"improvement" with the least squares line to measure the variability
explained by the predictor.
Lots of Fathom today, but that changes next class (Wednesday)
when we switch to StatKey and start in on simulations to lead to
bootstrap confidence intervals - a topic more relevant to this list.
Robin Lock
St. Lawrence University
On 2/2/2015 12:34 AM, Allan Rossman
wrote:
Happy
Groundhog Day!
I continue to find it inexplicable that neither private
colleges nor public universities see fit to cancel classes out
of respect for this august occasion. But this year I've
decided to try to make the best of this lamentable oversight,
and I need your help!
I think it might be fun to ask introductory statistics
teachers to compare notes on what's happening in their classes
on one particular day. What better day than Groundhog Day for
revisiting the same question over and over, and over and over,
and over and over, from multiple perspectives?
I'm writing this after Groundhog Day has officially begun in
Punxsutawney, Pennsylvania, but it's shortly after 9pm on
Super Bowl Sunday here in California. So, to get the ball
rolling on this whimsical idea (I strongly prefer the word
"whimsical" to "silly" in this context), I'll use future tense
to anticipate what will happen in my class on Monday. I plan
to be sound asleep when Punxsutawney Phil makes his celebrated
prognostication. (Too much information: Thirty years ago I
did indeed make the trek to Gobbler's Knob with my future
bride before sunrise on February 2, but I won't be up so early
or anywhere near Punxsutawney this year!)
My introductory students and I in STAT 217-09 at Cal Poly will
begin the fifth week of our ten week term on February 2 by
finishing up a discussion of principles of well-designed
experiments.We’ll
discuss a study conducted at Harvard about whether students
spend $50 differently depending on whether they’re told that
it’s a “tuition rebate” or “bonus income.”Then we’ll consider one
of the first studies of the drug AZT for reducing
mother-to-child transmission of HIV.We’ll culminate this
discussion by collecting some in-class data on a very simple
randomized experiment investigating whether grouping of
letters can affect memory. All students will receive the same
30 letters in the same order, but some will find convenient,
recognizable three-letter groupings and others will see more
irregular groupings of letters.
Then
I expect to have time to introduce a study about whether
swimming with dolphins is beneficial to patients who suffer
from clinical depression. We'll discuss the design of the
study and do a quick exploration of the 2x2 table of results,
setting the stage for simulating a randomization test to
assess whether the difference between success proportions in
two treatment groups is statistically significant. Carrying
out this simulation in class, using cards and then an applet,
will have to wait until February 3 when the excitement of the
momentous day has passed. (Or who knows, perhaps my students
and I will find when we awake on Tuesday that we are destined
to magically relive Monday again and again...)
Please indulge me in this fanciful exercise by replying to
this Simulation-Based Inference listserv with a description of
what happened, or will happen, in your introductory statistics
class on Groundhog Day 2015. Maybe we statistics teachers
will learn something interesting by exchanging this
information and reflecting on the variety of responses.Even if not, we can honor
the grand tradition of Groundhog Day by engaging in a
substantially less grand but only marginally more silly (oops,
I mean whimsical) one.
With best wishes for the special day and for an early spring
(to those of you who must endure winter),