SUNY-Geneseo/Physics & Astronomy
Fall 2021
Math 160: Elements of Chance
(Phys 228)
MWF 8:30 - 9:20, Fraser 119

 

   Dr. Pogo  (pogo at geneseo.edu)
   Where's Pogo?
   Office: ISC 228D
   
Assignment #1 (Due Nov 29) Data for Assignment #1 General Info About Normal Distributions
Assignment #2 (Due Dec 6)
Assignment #3 (Due Dec 13)
 
  Summary of Answers to all three assignments
Excel from Nov. 15 (Basic results of in-class experiment measuring desks...)
Excel from Nov. 17 (Making histograms of size of desks...)   
Histograms from Nov. 17 (Looking at histograms and estimating μ, σ, σm).
Excel from Nov. 19
 
(Results of in-class experiment with drawing randomly numbered cards.
Also includes extra tabs for our flipping pennies experiment, and for plotting normal distributions using multiple methods in Excel).
Excel from Nov. 22
 
(In-class example of finding best fit lines, covariance, two kinds of
correlation coefficients, and R2 values).
RMP Data from 2012
 
(We haven't used this yet, and I'm not sure we will. It's some "real" data for finding best fit lines, covariance, correlation, and R2 values).
Excel from Nov. 29
 
(Some results for in-class example of inference testing, finding α, β, and power. Not everything is here though; most of the work and results were just on the whiteboard!
Excel from Dec. 1 (Binomial & Poisson distributions)
 
 
(the following articles were never used...)
Here's an article to read and review in class.
Here's the original source of the data in that article.
 
What am I doing here? By the end of this course, you should have improved in your ability to think about statistics and probability,  to identify the tools needed to study a particular problem, and to read and critically evaluate quantitative information presented in the media. The course format involves extensive reading and discussion of newspaper and journal articles, computer activities, writing assignments, and student projects.

 

What do I have to read? You already got 5 books at the start of the semester...
How will I be graded? Your grade will be determined by:  
      Assignments:         30%
      Exam 1                 20%
      Exam 2                 20%
      Final Exam            30%
  

Final Exam: The final exam will be held in Frazer 119 on Monday, December 20, 2021, from 8:00 am to 10:30 am. It will be comprehensive (that is, it will include questions from Exam 1, Exam 2, and all the assignments)

Assignments: For now, homework will be "written". Still, professionalism counts and will affect your grade. I don't want a scribbled list of 6 numbers that all lack context. It looks like we'll only squeeze in 3  assignments, which means that each will count for about 10% of your grade... so think of them as take-home exams that you have a week (or more) to work on!

What if I have trouble with the homework? Come "see" me during Discord office hours (link sent by email or Canvas; TR 8:30-9:20, MW 9:30-10:20, MTW 1:00-2:00) and I’ll try to point you in the right direction. 
 
Also, I know that most of you will work in groups, and I won’t attempt to stop it. However, the learning is in the doing. Nobody on this planet learns from copying somebody else’s work, no matter how clear or correct it is. Every part of every problem that you let somebody else do for you is something that you are deciding that you just don’t want to learn. You will not have their help on exams! 

Learning Outcomes

These outcomes are unchanged from the original syllabus.
At the end of this course, students will:

  • ✗ Critically evaluate the design, including sampling techniques, of a statistical study.

  • ✓ Effectively use Excel to perform statistical computations and display numerical and graphical summaries of data sets.

  • ✓ Model and analyze measurement data using the appropriate distribution, e.g., normal, binomial, chi-square.

  • ✓ Compute and interpret the coefficient of correlation and the line of best fit for bivariate data.

  • ✗ Explore relationships between categorical variables using contingency tables.

  • ✓ Construct and interpret confidence intervals to estimate means and proportions for populations.

  • ✗ Apply the abilities described above to critically review articles from current newspapers , journals, and other published material.

I expect that the final third of the course will prioritize the elements shown in brown.