STAT 216 - Introduction to Statistics
- Contact information
- Course description and learning outcomes
- Required textbook and supplemental readings
- Course information - syllabus, calendar, and project instructions
- Course resources
- Data sets
- Various apps for potential project data collection
See your D2L Announcements page for your instructor's contact information.
Course Student Success Coordinator
Office: Wilson 2-263
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;
- 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?
Introduction to Statistical Investigations (ISI) by Tintle, Chance, Cobb, Rossman, Roy, Swanson, and VanderStoep (Wiley, 2016). MSU negotiated a reduced price for the textbook and custom e-textbook package available only from the MSU Bookstore (ISBN -9781119385943). The custom e-textbook is required to access videos that will be assigned as part of the reading prior to each class. The print textbook is optional, but you should have access to the textbook (print or e-book) during each class period.
If you prefer to purchase the custom e-textbook alone, you may purchase itfrom the MSU Bookstore or here.
- Probability: Supplement to Section P.3
- Normal distribution: Supplement to Section 1.5
- Bootstrapping: Supplement to Sections 2.2 and 3.3
- Fall 2018 Syllabus
- Project Instructions
- Fall 2018 Course Calendar:
- How to succeed in an active learning course
- Stat 216 YouTube Channel
- ISI Resources:
- Tableau Resources:
- Christian Stratton's Conditional Probability Visualization Applet
- Math Learning Center (MLC) is open 9 am to 7 pm Monday - Thursday and 9am to 5pm Friday. Do use it as a resource! Solutions to the textbook explorations are available in a binder to use while you're in the MLC.
- We use Brightspace (D2L) to organize the course, so log in and find your section.
- If you have any problems logging in, read their password help page.
Link to ISI Data sets here. Data sets for course explorations, investigations and assignments are available below.
- World Bank Indicators (WorldBankIndicators.xlsx)
- Current Population Survey from 1985 (cps.csv)
- Nearsighted children study (ChildrenLightSight.csv)
- Roller Coaster Data (RollerCoasters.csv) and Description
- Gapminder data (gapminder.csv) from gapminder R package
- Head injuries in alpine skiers and snowboarders (HeadInjuries.csv)
- New Jersey Prisoners (NJPrisoners.xlsx)
- Arsenic Levels in New Hampshire (arsenic.txt) - Bootstrapping supplement
- Polar bear weights (polarbear.csv) or Excel file
- Tuition costs (Tuition.csv)
- Birth weight data (Birth_Weights.csv) - Quiz 4
- OkCupid data for Women (OkCupidWomen.txt) and for Men (OkCupidMen.txt) - Regression and Correlation activity
- Contractor audits (Audits.csv)
- Murderous nurse (Murderous_Nurse.csv) - Exploration 5.1 data
- CloseFriends (CloseFriends.txt) - Exploration 6.3 data
- Memorizing words (Chap6 Investigation.txt)
- JJvsBicycle (JJvsBicycle.txt) - Exploration 7.2 data
- Auction (Auction.txt) - Exploration 7.3 data
- E. coli time (Ecoli-time.txt) and E. coli sand (Ecoli-sand.txt)