GOALS & OBJECTIVES

Statistics is a mathematical discipline that allows you to know how to best collect, analyze, and draw conclusions from data. A typical research problem can be summarized as follows:

  • Identify the question or problem.
  • Collect relevant data.
  • Analyze these data.
  • Draw a conclusion.

Thus, at its core statistics is a problem-solving subject. It does so by providing a set of mathematical tools for you to make sense of data and ultimately, connect scientific theories to the phenomena that we observe.

This course is designed to introduce you to the most important ideas and methods in statistics in a first-hand way, so that you can start getting comfortable with the tools you will be applying to data that you might encounter in the future.

By the end of the semester, you should be able to:

  • To understand the data and know how to explore them.
  • Use statistical software to summarize these data numerically and visually.
  • Ask questions about the data and design a plan to answer them.
  • Build statistical models/tests and understand which ones are more appropriate and why.
  • Make statistical inferences to help answer your initial questions.
  • Present results in a robust and clear way.
  • Understand the claims that others make from data and be able to critique them.

COURSE STRUCTURE

The course is divided into four phases of several units each. For each unit, a set of readings, videos, etc. will be posted on the course website. Lectures will cover the bulk of the theoretical ideas, whereas lab sessions will allow you to get familiar with application of these ideas to real data. These are deeply intertwined, and it’s important to make sure you understand both the theoretical and practical parts of doing statistics.

Classes will begin with a formal lecture. After that and a short break, we will get our hands dirty by walking together through jupyter-notebook tutorials, running in a R statistical language environment. This will allow you to put into practice what we have learned and more importantly, set a basis for you to be able to complete the assignments. Assignments will be posted at the end of the class. The deadline will be one week after the completion of each phase.

Assignments (Homework): The objective of the assignments is to give you a first-hand experience with statistics and data analysis. For that we will be using jupyter-notebooks, running in a R statistical language environment. You may start working on the assignments during the class session, but note that these are designed to take more than just the class time, so you will probably need to continue working on them in order to submit before the due date. The assignments will also train you for the exams and the final project.

Project: The objective of the project is to give you independent applied research experience using real data and statistical methods. The goal will be to synthesize what you have learned in class over the course of the semester, and to show that you understand which analyses are appropriate and interesting for which kinds of data.

Exams: There will be two exams, the first one halfway through the course and the second one at the end. Each exam will consist of jupyter-notebooks with theory and practice questions. Students will have 24h for their completion.

GRADING

  • Lab problems (Homework): 20%
  • Final project: 40%
  • First exam: (20%)
  • Second exam: (20%)
  • Participation (10%) (Extra credit)

EVALUATION

Final grades will be determined as: [90,100] = A, [80,89] = B, [70,79] = C, [60,69] = D, [< 60] = R. Grade curving may occur at the instructor’s discretion.

LATE WORK POLICY

There is a 10% penalty per week for late homework assignments (e.g., 2 weeks late means 20% penalty). Homework submitted 2 weeks after the original deadline or after the last day of the semester (whichever comes first) will not be accepted. Final projects submitted after the deadline will receive a 10% penalty and any project not submitted within 24hrs of the deadline will not receive any credit.

ATTENDANCE AND PARTICIPATION

For me, attendance is NOT mandatory, but I recommend it for your own learning. Slides will be always available after class each day, but you’ll get much more out of the class if you engage actively with the course by attending and asking questions!

All the lectures and tutorials are designed to elicit active learning through participation, and in general the best way to learn is to ask questions! In addition to helping yourself and your classmates learn, you will be making it a lot easier for your instructors to view grades on the edge of two categories more favorably.

EQUAL OPPORTUNITY ACCOMMODATIONS

All efforts will be made to minimize conflict with students’ religious schedules (e.g., holidays, prayer services, etc.) and/or any disabilities. Students should consult with the Equal Opportunity Services (EOS) office at the beginning of the semester in order to set up any necessary accommodations for the class.

RESPECT IN THE CLASSROOM

It is my intent to present materials and activities that are respectful to the diverse backgrounds and perspectives of students in the classroom. You may feel free to let me know ways to improve the effectiveness of the course for you personally or for other students or student groups. If you feel uncomfortable discussing this with me, you may voice your concerns to the Chair of the Department of Psychology Diversity and Inclusion Committee, Kody Manke.

SELF CARE

  • Do your best to maintain a healthy lifestyle this semester by eating well, exercising, avoiding drugs and alcohol, getting enough sleep and taking some time to relax. This will help you achieve your goals and cope with stress.
  • All of us benefit from support during times of struggle. You are not alone. There are many helpful resources available on campus and an important part of the college experience is learning how to ask for help. Asking for support sooner rather than later is often helpful.
  • If you or anyone you know experiences any academic stress, difficult life events, or feelings like anxiety or depression, we strongly encourage you to seek support. Counseling and Psychological Services (CaPS) is here to help: call 412-268-2922 and visit their website at http://www.cmu.edu/counseling/. Consider reaching out to a friend, faculty or family member you trust for help getting connected to the support that can help.