CST Colloquium: “Sports Data Science” – Thurs, Nov 14

There is a CST Colloquium talk on Thursday which is related to statistics. I will be there, and I strongly encourage you to attend if you can.

(To incentivize you to attend, you will earn 1pt towards your participation grade if you do attend! Also, you get free pizza.)

Here are the details:

CST Colloquium Series

Title: Sports Data Science

Presented by: Claudio T. Silva,  NYU

Thursday November 14 from 12:00 to 1pm

Room N918

Refreshment (pizza & soda) will be served.

CST Colloquium Series Title: Sports Data Science Presented by: Claudio T. Silva,  NYU Thursday November 14 from 12:00 to 1pm Room N918 Refreshment (pizza & soda) will be served.
CST Colloquium – Sports Data Science

Quiz #3 – Wed 30 Oct

Just a reminder that we will take Quiz #3 in class tomorrow (Wednesday Oct 30).

Please work through as much of “HW7-ConditionalProbability” as you can before class; the quiz will consist of one or two quick exercises based on the exercises in HW7.

In particular, make sure you understand Exercises #3-7 from HW7.  It may be helpful to have the conditional probability class outline pdf open while you do the homework.

 

Math Club talk on “Probability and Games” – Thurs Oct 10

Please note that the college is closed both tomorrow (Wed Oct 9) and next Monday (Oct 14), so we won’t have class again until Wed Oct 16.  In the meantime, please review the introductory material on probability we started discussing yesterday, and start working on the “HW5-Probability” WebWork set (due Fri Oct 18).
In addition, I wanted to let you know about a Math Club talk on Thursday which is very relevant to our course. I will be there, and I strongly encourage you to attend if you can. (To incentivize you to attend, you will earn 1pt towards your participation grade if you do attend!  Also, you get free pizza.)

Here are the details (taken from the Math Club’s OpenLab site):

 

Date: Oct. 10, 2019

Time/Room: 12:45-2pm in N1002

Speaker: Johann Thiel (NYCCT)

Title: Probability and Games

Abstract: In this talk we will analyze various games of chance, including the Monty Hall Problem and Race to the Finish from Let’s Make a Deal and Plinko from The Price is Right. We will use both theoretical and computational methods to understand the probabilities of winning such games.

 

Pizza will be served at 12:45pm.

Exam #1 – Wednesday, Oct 2

As I announced in class, we will take our first midterm exam next Wednesday (Oct 2).  The exam will cover the material up to and including linear regression.  See below for some tips on how to prepare for the exam.

Note that since the college is closed on Mon Sept 30 (& Tues Oct 1), the exam will be during our next class meeting. The exam should take no more than one hour to complete, so we can use the first 30mins of class on Wednesday to discuss any questions that come up as you study for the exam.

To prepare for the exam:

  • start by finishing WebWork set “HW4-PairedData” (due Sunday, Sept 29 at 6p)
  • review the outlines/notes/spreadsheets for Classes#1-8 (available under Files and the Schedule page)
  • review the WebWork exercises and solutions from “HW2-Graphs”, “HW3”, and “HW4-PairedData” (solutions for HW4 will be available Sunday evening immediately after it closes; solutions for the previous two HW sets are available now)
  • in particular, review the following WebWork exercises:
    • HW2-Graphs: #2, 3, 4, 10, 11, 13, 14
    • HW3: #1, 2, 3, 5, 10
    • HW4-PairedData: #1, 3, 6, 13, 14, 20, 21, 22

First OpenLab Assignment – Introduce Yourself

Your first OpenLab assignment is to

This assignment is due Friday, September 6.  Completing this assignment will earn you one point towards the participation component of your course grade. Late submissions will receive partial credit.

Assignment. Write a comment in reply to this post (scroll to the bottom to find the “Leave a Reply” box–if you’re viewing this from the site’s homepage, you will need to click on the post’s title above, or click on the Comments link to the left):

In a brief paragraph (3-5 sentences), introduce yourself in whatever way you wish (what do you want your classmates to know about you?  Some ideas: where you’re from, where you live now, your major, your interests outside of school, etc.)