Hi Everyone,
It has been a pleasure reading this thread all week. Unfortunately I'm not teaching
Intro Stats right now. However, I am teaching VBA programming in Excel to Master of
Finance students and we use an awful lot of simulation and statistics. The class consists
of 3 hour sessions in a computer lab, once a week over 6 weeks. Yesterday in class (week
4) the students worked with 10 years of monthly adjusted closing prices from two stocks.
They had to write a program to find monthly returns of the stocks, the means and variances
of each, and then generate portfolios of the two stocks by varying weights to each in
increments of 10% or an increment input by use. Lastly, they found the minimum variance
portfolio.
After getting the programming down and recalling the basic gist of a two asset portfolio,
they created histograms of each stock's returns to see if modeling the returns as a
normal distribution may be reasonable. After which, they simulated new stock return data
by generating random returns from a normal distribution and a t-dist with same mean and
variance of original sample returns. They examined how the efficiency frontier and minimum
variance portfolio varied with new data. Homework for next time is to expand the exercise
further by introducing investment in two stocks and a "risk free" asset. Here
we'll play around a good bit with how varying the interest rate of the risk free asset
impacts the portfolio composition. While it isn't quite on topic - thought I'd
share.
Also would love to have Robin's data set on population of countries to predict land
area. I'm quite sure Monaco is an outlier on this one!
Michelle Sisto
EDHEC Business School
Nice, France
From: sbi-bounces(a)causeweb.org
To: sbi(a)causeweb.org
Cc:
Date: Mon, 02 Feb 2015 21:50:45 -0500
Subject: Re: [SBI] Happy Groundhog Day! What happened in your introductory statistics
class today?
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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),
Allan Rossman
--
Allan J. Rossman
Professor and Chair
Statistics Department
Cal Poly
San Luis Obispo, CA 93407
arossman(a)calpoly.edu
http://statweb.calpoly.edu/arossman/
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--
Robin Lock
Burry Professor of Statistics
St. Lawrence University