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? <!-- --> 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/ _______________________________________________ SBI mailing list SBI(a)causeweb.org https://www.causeweb.org/mailman/listinfo/sbi -- Robin Lock Burry Professor of Statistics St. Lawrence University