STAT 216 - Introduction to Statistics
Fall 2024
Required Textbook
Two "textbooks" are required for this course:
- Montana State Introductory Statistics with R - free online textbook
- STAT 216 Coursepack - workbook with reading guides and in-class activities, purchase at the MSU Bookstore.
Please read through the syllabus linked below for more details about the course.
Quick Links
Classroom Format and Organization
Stat 216 will meet 3 times per week. Each week, students will:
- read assigned sections of the online textbook and watch videos on that week’s content prior to attending your assigned in-person class day, including concept check video quizzes posted on Gradescope,
- meet with your fellow students in your assigned classroom three class periods per week for in-class group activities and discussion,
- complete one assignment in Gradescope.
Contact Information
Your Instructor
See your D2L Announcements page for your instructor's contact information.
Course Student Success Coordinator
Jade Schmidt
Office: Wilson 2-263
email Jade
Assistant Course Student Success Coordinator
Melinda Yager
Office: Wilson 2-260
email Melinda
Course Supervisor
Dr. Stacey Hancock
Office: Wilson 2-195
email Stacey
Course Description
Stat 216 is designed to engage you in the statistical investigation process from developing a research question and data collection methods to analyzing and communicating results. This course introduces basic descriptive and inferential statistics using both traditional (normal and t-distribution) and simulation approaches including confidence intervals and hypothesis testing on means (one-sample, two-sample, paired), proportions (one-sample, two-sample), regression and correlation. You will be exposed to numerous examples of real-world applications of statistics that are designed to help you develop a conceptual understanding of statistics. After taking this course, you should be able to:
- Understand and appreciate how statistics affects your daily life and the fundamental role of statistics in all disciplines;
- Evaluate statistics and statistical studies you encounter in your other courses;
- Critically read news stories based on statistical studies as an informed consumer of data;
- Assess the role of randomness and variability in different contexts;
- Use basic methods to conduct and analyze statistical studies using statistical software;
- Evaluate and communicate answers to the four pillars of statistical inference: How strong is the evidence of an effect? What is the size of the effect? How broadly do the conclusions apply? Can we say what caused the observed difference?
MUS Stat 216 Learning Outcomes
- Understand how to describe the characteristics of a distribution.
- Understand how data can be collected, and how data collection dictates the choice of statistical method and appropriate statistical inference.
- Interpret and communicate the outcomes of estimation and hypothesis tests in the context of a problem.
- To understand the scope of inference for a given dataset.
Data Sets
Data sets for course activities and assignments are available below.
- World Bank Indicators (WorldBankIndicators.csv))
- Montana fishing log (FishingLog.csv)
- Roller Coaster Data (RollerCoasters.csv) and Roller Coaster Description
- Gapminder data (gapminder.csv) from this Github repository
- New Jersey Prisoners (NJPrisoners.csv)
- Arsenic Levels in New Hampshire (arsenic.txt) - Bootstrapping supplement
- Polar bear weights (polarbear.csv)
- Tuition costs (Tuition.csv)
- Birth weight data (Birth_Weights.csv) - Quiz 4
- OkCupid data for Women (OkCupidWomen.txt) OkCupid data for Men (OkCupidMen.txt) - Regression and Correlation activity
- Contractor audits (Audits.csv)
- Murderous nurse (Murderous_Nurse.csv) - Exploration 5.1 data
- Peanut allergies (PeanutAllergy.csv) - Assignment 5 data
- Staring at drivers (StaringDrivers.csv) - Assignment 6 data
- Life expectancy (LifeExpectancy.csv)
- Ski resorts (SkiResorts.csv)
- Tennis ball data (TennisBallData.csv) - Quiz 7 data
- Pregnancy test (PregnancyTest.csv)
- Activity tracker data (step.csv) - Assignment 8
- Bear Complaints
Data Sets for Course Activities and Labs
- Module 2 Activities: American Indian Address (Becenti.csv)
- Module 3 Guided Activities: IPEDS (IPEDS_2018.csv)
- Module 3 Lab: IMDb movies data set (Movies2016.csv)
- Module 3 Lab: Nearsighted children study (ChildrenLightSight.csv)
- Module 4 Guided Activity 6: IPEDS (IPEDS_2018.csv)
- Module 4 Activity: MLB Stats (baseball.csv)
- Module 4 Lab: Penguins (Antarctica_Penguins.csv)
- Module 5 Guided Activity 7: Sleep Study Data (LosingSleep.csv)
- Module 5 Activities: Helper-hinderer study (infantchoice.csv)
- Module 6 Guided Activity 8: Cashless Society Data (cashless.csv)
- Module 6 Activity: Male boxers (Male_boxers_sample.csv)
- Module 7 Guided Activity 9: Good Samaritan (goodsam.csv)
- Module 7 Activity: Edibility of Mushrooms (mushrooms.csv)
- Module 8 Guided Activity 10: Head injuries in alpine skiers and snowboarders (HeadInjuries.csv)
- Module 8 Activity: Glycemic control in diabetics (diabetes.csv)
- Module 8 Lab: Contagious Yawning (YawnData.csv)
- Module 9 Guided Activity 11: Color Interference (interference.csv)
- Module 9 Guided Activity 12: Snakes Data (vipers.csv)
- Module 9 Activity: Swearing data set (pain_tolerance.csv)
- Module 10 Guided Activity 13: Behavior and Performance (rude.csv)
- Module 10 Guided Activity 14: Moon VR (Moon_VR.csv)
- Module 10 Activity: Dinosaur (dinosaur.csv)
- Module 10 Lab: Trustworthiness (Trustworthiness.csv)
- Module 11 Guided Activity 15: Crocodylian Measurements (Crocodylian_headwidth.csv)
- Module 11 Guided Activity 16: Golf Driving Distances (golf.csv)
- Module 11 Lab: Big Mac Index (big_mac_adjusted_index_22.csv)