Welcome to
MATH/STAT 145!
MWF 1:45-2:50 PM
Morken 216
I love this course because it empowers you to navigate statistical results and
grapple with the various issues that arise with data-based decisions!
Learning Goals*
The main learning goal of this course is that students will be able to... (drumroll)
...develop expertise working with, interpreting and communicating the stories of data
more specifically, students will:
Use data analysis methods to make decisions about biology, about your life, and your vocation
Analyze and critique statistical arguments offered in media and research journals
Understand and communicate in the language of statistics
Harness technology and tools that can be used to share the story of data
All the assignments and lessons in this class are geared toward these learning goals.* Specific topics include: data collection, experimental design, sampling, variability, uncertainty, distribution, association, causation, significance, hypothesis tests, interval estimates, and bivariate regression.
*More learning outcomes from the mathematics department and PLU's general education are given later.
Stuff you need
No Book purchase required
There is no book purchase required for this course. Readings will be made available via the course website. Here are some of the resources we will use...
Google Classroom
Based on feedback from previous students, I have transitioned to using Google Classroom (GC) with my website. You will need to scan your homework and submit as a pdf into GC.
To use your phone to scan homework to a pdf & submit to GC:
Submit with iPhone: https://youtu.be/EIUpRE_xPKc
Submit with Android: https://youtu.be/AbLFIgJq5sc
Why use R? R is...
free
powerful
popular
open-source
great on resumes!
R Statistical Software
This course uses R statistical software with R Studio (both of which are FREE!) Instructions for downloading and getting started are in ModernDive, here.
R can be intimidating (and at times frustrating) at first, but no computing expertise is expected of students entering this course. That means you can reach out to me and your peers for help with ANY questions. We will learn together!
PLU email
To be successful in this course, you will need to activate and use your PLU email (ending with @plu.edu). Your email will contain an invitation to the course website that we will use daily, as well as occasional announcements and notifications about the course.
Although we will use Google Classroom for delivering and submitting assignments and forums, in general we will use this course website for communicating course content.
Prerequisites
To be successful in this course, you should be comfortable with the material from Math 140 (precalculus).
You do not need to have computing experience, but we will use R statistical software. This may take some patience and grit at first, but it will be well worth the effort!
Course Format & What to Expect
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 we will cover with an eye for what is most important for students to learn. I will not assign readings or lessons unless they are appropriate for the topic of this class and the level of mathematics this course is designed for.
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.
GENERAL Weekly Schedule
I created this table to help you get a sense of what our week will typically look like at the start of the semester:
Coursework
Labs/Assignments: 55%
These include homework assignments, and in-class assignments (which can become homework if unfinished during class). Some may require or allow you to work together in small groups.
Exams 30%
This class has two exams:
Midterm Exam (15%)
Final Exam (15%)
More information about these will be given later.
Group Project 10%
More information about the project will be given later.
Check-up Quizzes / Miscellaneous: 5%
You can expect weekly check-up quizzes designed to help you receive quick feedback on whether you are grasping the main ideas of the course so far. There is no time limit.
NO quiz retakes are given, even for good reasons, such as illness. Instead, at the end of the semester students who complete their final course evaluations earn 5 extra credit quiz points (equivalent to one missed quiz).
Notice that these checkup quizzes/reports only add to 10% of your grade. They are designed to be low-stakes and low-stress feedback on your understanding of course materials.
*Maximum alowable in any category is 100%.
Grades
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.).
Incomplete grades are only assigned to students who have completed at least 50% of course work by the end of the semester, and who were unable to complete the course requirements due to circumstances beyond their control.
Learning Objectives (Formally)
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.