Assignments¶
To prepare students to tackle the course’s motivating questions - especially What habits of mind do we need to develop to be effective and ethical statisticians? - there are a variety of assignments in this course. Each week will be a mix of reading about topics in statistics, discussing and debating concepts, putting our readings into practice, and constant reflection about our learning and professional development. Due dates are posted on the Detailed Course Schedule and are due on the stated dates at 10am.
Note
The Detailed Course Schedule lists the due dates for the course. To view it, please log into your Smith account.
Engagement & Class Preparation¶
For each lecture meeting and lab, there will be readings and/or a pre-class activity. These readings and activities are intended to be your first contact with the course material. Engaging with these materials in good faith before class will help you get the most out of the in-class activities.
Group Problem Sets (GPsets)¶
Group Problem Sets are designed to be completed in class with possibly some work out of class to clarify details that your group discussed. The goal of these GPsets is to put the ideas from the readings and pencasts to work in examples.
GPsets are due on Thursdays at 10am unless otherwise noted on the Detailed Course Schedule. Often there will be more than one GPset due on each Thursday. Please consult the Detailed Course Schedule.
Labs¶
The labs are designed to be completed in class with some work out of class to practice the ideas from the pre-lab assignments. Pre-labs are due before the start of lab on Thursdays. Labs are due on Fridays at 10am unless otherwise noted on the Detailed Course Schedule.
Projects¶
There will be one group project for the semester. In this project, you will use what we have learned in this class to investigate one data set of your choosing. There will be lab time set aside to work on the project.
The project will also scaffold explicit development of writing skills that SDS has laid out in our writing plan. Specifically, our course will focus on three of the listed writing goals:
Writing Goal 2 - Engage in a writing process that includes brainstorming, outlining, initial drafting, peer review, editing, and revising;
Writing Goal 4 - Prioritize the important parts of the process and/or project to communicate
Writing Goal 5 - Clearly communicating the research question and how analysis will support the question in the introduction.
Starred Problems¶
Each week, you will complete a starred problem. The goals of these problems are to 1) apply what we’ve discussed in class on your own, 2) reflect on your learning so far, and 3) practice for the knowledge checks. To accomplish these goals, starred problems will all follow the same procedure:
Study what we have learned so far
Put away all course resources
Download that week’s starred problem off Moodle
Write your solution to the problem and upload it into Moodle
Once properly uploaded, the instructor solution will appear
Compare your solution to the instructor solution 6.Complete a reflection worksheet about this problem and what you would like to review as a result of doing this problem
These problems are based on completion (ie. you get the credit or not) based on both your solution and the content of your reflection. This means that you can get the problem totally wrong and still get full credit if you take the time to honestly reflect on your progress. This assignment structure is based on an assignment structure from Smith’s Engineering Program.
Starred problems are due on Mondays at 10am unless otherwise noted on the Detailed Course Schedule.
Knowledge Checks¶
There are 4 Knowledge Checks, during which you can collect statistics medals. There are 15 medals, each representing core skills for the course. During each knowledge check, you can attempt as many or as few medals as you would like. Your goal, by the end of the semester, is to collect all 15 medals.
The first badge challenge will have the first 5 medals available, the second will have the first 10, and the third and fourth knowledge check will have all 15 medals. You do not need to (nor should you) attempt all medals on each knowledge check, but you do need to collect all 15 medals by the end of the term.
Note
The weekly starred problems will be in the style of the knowledge check questions.
Statistics Medals¶
The 15 medals that represent core skills for the course are listed below, in the order that they appear in the course:
Describe and evaluate context for a statistic, statistical test, or procedure, including any sampling biases and the data collection design
Compute and contextualize notions of typical and spread
Create appropriate graphical summaries given the data and context of the data; Articulate the limitations and strengths of each type of graphical summary
Compare and contrast sample distributions and sampling distributions; Compare and contrast sampling and resampling; Compute and accurately describe standard error to a non-expert
Compute and accurately describe confidence intervals to a non-expert; Articulate how confidence intervals relate to statistical inference
Compute appropriate probabilities within a given context; State and apply Bayes’ Rule
State the four steps of a hypothesis test; Relate hypothesis testing to probability distributions; Detail the limits and potential abuses of hypothesis testing
Define Type I and Type II errors; Explain how Type I and Type II are connected
Describe issues of running multiple hypotheses in one hypothesis test to both an expert (using probabilistic ideas for support) and a non-expert
Create linear models; Detail the meaning of each coefficient in a contextually meaningful fashion
Evaluate linear models using statistical measures; Articulate limits and potential abuses of using linear models
Identify potential confounding variables; Identify if, where, and how Simpson’s paradox is at play in a given context
State and apply the Central Limit Theorem; Describe how the Central Limit Theorem relates to the normal distribution
Describe the normal distribution including detailing features related to skew and standard deviation; articulate the differences between normal and t-distributions; articulate the differences between cumulative and density curves
Apply ANOVA and χ^2 tests appropriately, articulating each step of the tests
Weekly flow for the course¶
Each week, you will have group problem sets, a lab and either a starred problem or a knowledge check due each week. The course will operate as follows:
Day |
Course Preparation and/or Activity |
Assignment due |
|---|---|---|
Monday |
Group Problem Set in class |
Starred problem |
Wednesday |
Group Problem Set in class |
(none) |
Thursday |
Lab in Class |
Pre-lab; Group Problem sets from Monday, Wednesday, and previous Friday |
Friday |
Group Problem Set in class |
Lab from Thursday |
Workload¶
According to federal standards, each five-credit course should equate to at least 225 hours of work over the semester. If you are taking 16 credits, that equates to 720 hours of work over the 15 weeks of the semester, from the first day of classes until the end of the final exam period. In the case of this course, you will spend nearly 15 hours each week on my class alone (including our six hours of class meetings per week).1
In considering the work for this course, I believe that the approximate 9 hours per week outside of class will breakdown something along these lines:
3 hours of class prep - One hour per lecture for reading the book and prep activities
1 hour per week of lab prep and/or wrap up
1 hour per week on the project
1 hour per week on the starred problem
3 hours of “flex time” used to supplement any of the above areas and/or go to student hours
Notice that there are 3 hours of flex time. This is to accommodate weeks were you might want to spend more time on an assignment. For example, you might spend extra time studying in the weeks leading up to a knowledge check.
If you find that the time you are spending on this class is a lot more than 9 hours per week outside of class or a lot less, let’s check in.
Spending time on You¶
The current system is designed to keep you working more than 40 hours per week just on your courses. This means that the hours not working on class work are precious and should be treated as such. This does not mean that every hour of every day should be filled with things deemed important by others, but more as a call to be intentional with your time. A few questions you might want to ask yourself include:
Are you spending time on yourself and your wellbeing? What are you doing to restore yourself? How much time and space do these activities need to be effective?
Are you giving to your courses the time that you want to be? Are you giving them the time during part of the day when your brain is ready to engage new ideas?
Are you working doing your best thinking hours? If so, do you have any flexibility to adjust your daily schedule to be more present with your studies?
Are you devoting time to being with your friends and/or your family? Are you present during those times?
Are you losing hours to things or activities that are not high on your priority list? Alternatively, are you losing hours or days that you cannot recall what you did that day or why it so consumed you?
The adage tells us that “time is our most precious resource.” This statement frustrated me as a student because “I’ll have time after college/graduate school/post doc.” I have come to believe that this moment is the time that we have and if we are not intentional with our time today, right now, we will lose, not hours, not days, but months and years. I am working on a process of aligning my time to reflect my priorities as an educator, a researcher, a friend, and a family member. This is not a process that is completed in a few hours or a few days, but rather it is an iterative process of repeated and constant reflection.
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Each of our 75 minute meetings is “counted” as 90 minutes. Since we meet 4 times per week, our “in-class contact time” is counted as 6 hours.