Notes on Mon May 11 Blackboard / Exam #3 / Final Exam schedule

See below for a list of topics we discussed during Monday’s Blackboard session. We also discussed the exam schedule:

  • Exam #3 will be a take-home exam (similar in format to Exam #2), which will be posted later today and will be due Monday (May 18)
    • Recall that the lowest of your three midterm exam scores will be dropped, i.e., your two highest midterm exam scores will be counted towards your course grade.
    • So if you are satisfied with your first two exam scores, you can skip handing in Exam #3. But I encourage you to at least attempt the exercises on Exam #3, since they will be good review for the final exam.
  • The final exam will be a set of WebWork exercises for which you will also submit written solutions.  The final exam exercises will be assigned next Wed (May 20), to be completed by Friday May 22.
    • There will be a set of 10 WebWork exercises for which you will submit answers online via WebWork
    • You will also need to submit written solutions for those WebWork exercises, so that I can check your work and allow the possibility of partial credit.
  • We will have Blackboard sessions today (Wed May 13) as well as next Monday (May 18) and Wednesday (May 20), to discuss the exams and go over some remaining new material.   Wednesday May 20 will be our last Blackboard session.
  • There will be no projects, so I will post a revised grading scheme: your course grade will be made up of your midterm exams, final exam, WebWork, quizzes, and participation (some additional ways of earning participation points will be posted this week.)

Topics discussed on Monday’s Blackboard session:

  • 0-60mins: went over Exam #2 solutions
  • 60-90mins: revisited class outline on binomial experiments, and discussed the binomial distribution formula
  • 90-125mins: set up example for computing a binomial probabilities in Google spreadsheet: Binomial Distribution Calculation

We will continue with that spreadsheet during today’s Blackboard session!  I will also discuss the exercises on Exam #3, so please join today’s Blackboard session.


Notes on Wed May 6 Blackboard Session: Intro to Binomial Distribution

Here’s an outline of what we discussed during Wednesday’s Blackboard Collaborate class session:

0-60min: We discussed HW9, specifically #2, as an example of a discrete probability distribution (and how we can use it to compute “cumulative probabilities”)

60-80min: We discussed HW7 #8, specifically how the various probabilities can be organized and displayed in a tree diagram (as an example of what is more generally called a probabilistic graphical model.

See the notes regarding probabilistic graphical models below.

80-100mins: We returned to binomial random variables and started looking at the binomial distribution formula. We will pick it up with that on Monday.  See also the Khan Academy video on this:

Probabilistic Graphical Models:

Via the wikipedia entry for probabilistic graphical model: “A graphical model or probabilistic graphical model (PGM) or structured probabilistic model is a probabilistic model for which a graph expresses the conditional dependence structure between random variables. They are commonly used in probability theory, statistics—particularly Bayesian statistics—and machine learning.”

For instance, take a quick look at Ch 8 of a textbook titled Pattern Recogition and Machine Learning, which is about such graphical models. Note that early chapters in the at textbook cover probability theory, probability distributions and linear regression!

See also this brief intro to the subject:


Notes on Mon May 4 Blackboard Session: Intro to Binomial Experiments

Here’s an outline of what we discussed during Monday’s Blackboard Collaborate class session

0 – 30min: introduced binomial experiments (see videos below)

30 – 40m: discussed the upcoming homework schedule:

        • HW7-ConditionalProbability: due Wed night (see OpenLab post re HW7-Exercise 8)
        • HW9-RandomVariables (due next Monday): get started with #2, 3, 5, 6; we will discuss #1 & #4

45m – 1h10: Bayes’ Theorem (see OpenLab post), Bayesian interpretation; statistics/probability texts using python (see textbooks page)

1h10m – 1h45m: examples of binomial experiments/random variables (see class outline)


Notes on Mon April 27 Blackboard Session / Exam #2 Announcement

On Monday we discussed the following topics:

  • 1st 30mins: we discussed the upcoming schedule of HWs and related OpenLab posts, and I announced the plan for Exam #2
    • Exam #2 will be a take-home (open book) exam which I will post later today, and will be due Sunday
    • Please join the Blackboard Collaborate session coming up today at 12p, when I will give a preview of the exam questions!
  • 30min-1h20m: we went through some examples of constructing and graphing the probability distribution of a random variables; in particular for the random variables/probability experiments of
    • X = number of heads observed when flipping a coin 3 times;
    • X = sum of two 6-sided  dice
  • 1h20m – 1h45m: we calculated the expected value E[X] of a random variable from its probability distribution

Notes for Mon April 20 / HW8 (Permutations & Combinations)

Here’s a brief recap of today’s Blackboard Collaborate session:

For the first approximately 40mins, we gave an overview of HW8, which consists of permutations and combinations calculations:

  • HW8 is a written homework assignment; you can find the pdf with the homework exercises under Files
    • HW8 is due next Monday (April 27)
    • I will create an Assignment in Blackboard where you can submit your solutions (preferably as a pdf, as you did for Quiz #3 over the weekend)
    • we went through HW8 #1 together–in particular I wanted to demonstrate how to show your work;
    • we will go through at least one more exercise from HW8 during Wednesday’s Blackboard session

We spent the remaining hour reviewing random variables and introducing probability distributions for such random variables.

Please review the Class Outline on those topics–in particular, it’s essential you understand the example involving the probability experiment of flipping a coin 3 times, and constructing the probability distribution for the random variable “X = the number of heads observed.”  We will build on that example when we discuss binomial experiments and binomial random variables.

You can review the Blackboard recording, and/or you can view this Khan Academy  video, which constructs the probability distribution for that same random variable:


Videos/Notes for Wed April 15: Discrete Random Variables

We introduced (discrete) random variables during our Blackboard Collaborate session today.  We went over the 1st page of the class outline on this topic (available in Files as “Class Outline – Day 17”).  We also discussed Quiz #3, which has also been uploaded to the Files. It is due Sunday (April 19). Instructions for submitting your solutions will be posted later today.

We watched the beginning of the following jbstatistics video introducing discrete random variables. We will continue with this topic next Monday, but I recommend watching the entire video to get a preview:


Blackboard Collaborate test session – today!

[I posted this as an announcement on Blackboard just now, which you may have already received as an email. I thought I’d post to OpenLab too.  Note that you can log in to Blackboard at]

I am going to run a test session in Blackboard Collaborate Ultra today, 12p-1p. If it’s possible for you to join, it would help me a lot if you do, even if only for a minute. I want to see how it will work for running class sessions. Also it would also be nice to hear from some of you and see how things are going through all of this.

Blackboard allows streaming audio and/or video from all participants, but there is also text chat if you’d rather just do that (or just join, you don’t have to chat at all!)

Here is the link for today’s session, which you can open on a computer or on your phone:

I tried joining a Blackboard Collaborate session yesterday from my phone, and it works pretty well.

I will likely run another test session tomorrow (Thurs) but I haven’t figured out what time yet.

Hope to chat with some of you soon!