Welcome to MATH/STAT 242!

I love this course because it has real applications to everyday life and is still grounded in basic principles of logic and scientific thinking. 

The main learning goal of this course is that students will be able to... (drumroll)

...navigate data-based claims that permeate our society and develop expertise to make informed data-based decisions

more specifically, students will:

1. Gain insight into the statistical process as they execute a basic statistical study, and

2.  Develop expertise interpreting and critiquing a statistical study.

These learning goals work well together; as you learn how to critique a statistical study, you'll better be able to critique other studies, and visa versa.

All the assignments and lessons in this class are geared toward these learning goals.*

Books

You don't need to buy a textbook for this course. Here are a few I may occasionally refer to or recommend:

Our course will remain in virtual format, despite how the rest of PLU may adjust to blended learning. Here is what you can expect from me: 

• Communication: I will make it clear what the tasks are each day and what upcoming deadlines are.

• Purposefulness and Respect for students' time: I have carefully examined what topics can be cut so that our course is focussed with each lesson worth your time.  I've also re-examined the homework problems that I usually assign, making sure each homework problem is relevant and aligned with the learning goals for the course.

• Equity and Access: Some students in our class have siblings to care for, unpredictable work schedules, unreliable Wi-Fi, and other challenges that make it very difficult—if not impossible—for them to be able to participate in synchronous (i.e., live, real-time) class sessions. Other students want/need the live, real-time help with their learning.  Colleagues have advised me not to record our live real-time sessions because students will become shy and hesitate to participate.  What a conundrum!  So how do I serve all students, including those who want live in-person time as well as those who need access outside of class? Well, I have designed a course that blends both types of learning so that students can access course content outside of class and then meet in-person to ask questions and participate in activities that bring concepts to life. The live sessions will give us a chance to learn together in community. Students who miss our real-time class sessions will unfortunately not get the full experience and will most certainly miss out, however, in this blended approach those students might still be able to be successful in the course.

• Transparency:  Last semester, students were generally really positive about my teaching, but offered suggestions for how to make the course better. I have implemented many of these and will continue to try to make it clear what I'm thinking, why I'm doing it, and asking you how its going.  

Grades of  A, A—, B+, B, B—, C+, C, C—, D, and F are assigned at cutoffs of  93%, 90%, 87%, 83%, 80%, 77%, 73%, 70%, 60%, and 0%, respectively. 

Please see your PLU Catalog for general policies on grading, Incomplete, P/F, and W grades. Online you can also find the PLU policy in case of an academic emergency (e.g., natural disaster, epidemic, etc.).

This course is aligned with the following PLU Math Department Learning Objectives:

• Communication:  Be able to read, interpret, write about, and talk about mathematics (or statistics).

• Application: Be able to apply mathematical concepts to concrete situations.

• Disciplinary Citizenship: Develop collaborative skills, independence, perseverance, and experience with open-ended inquiry.

This course is aligned with the following Statistics Minor Objectives:

• Develop novice-level statistical thinking, particularly with respect to linking appropriate inferences to study design (e.g., correlation does not imply causation).

• Demonstrate the ability to appropriately select and use statistical models (e.g., normal distribution, t-distribution, binomial distribution) and statistical methods (e.g., regression, resampling).

• Develop facility with one or more professional statistical software programs.

This course is aligned with the following General Education Learning Outcomes (QR):

• Students will solve problems by interpreting quantitative information in context.

• Students will demonstrate the ability to work with mathematical notation, techniques, tools, and concepts.

• Students will create and critique logical arguments supported by quantitative evidence or symbolic relationships.

This course is aligned with the following General Education Learning Outcomes (NS):

• Students will understand and apply basic concepts from a particular discipline of the natural sciences.

• Students will identify and explain organizing models of a discipline. 

• Students will identify social and ethical issues pertaining to a discipline.

This course primarily focusses on statistical inference, including hypothesis testing, confidence intervals, and limitations thereof. The catalog course description is as follows: Data description, probability, discrete and continuous random variables, expectations, special distributions, statements of law of large numbers and central limit theorem, sampling distributions, theory of point estimators, confidence intervals, hypothesis tests, and regression using R statistical software. Prerequisite: MATH 151 (Calculus 1).

Things we will not cover in this class (but you can take Stat 342, 348, or 442 to learn more!) include: