Introduction to Statistics and Data Science (202-0-20)
Instructors
Danielle Kaye Sass
Meeting Info
Harris Hall 107: Mon, Wed, Fri 9:00AM - 9:50AM
Overview of class
This course introduces students to the discipline of statistics as a science of understanding and analyzing data. Students will learn the importance of data collection and generation, methods to analyze data, and how to use data to make inferences and conclusions about real world phenomena. Students will also become better consumers of everyday statistics — news, social media, infotainment, etc.
Registration Requirements
Prerequisite: High School Algebra
May not receive credit for both STAT 202-0 and STAT 210-0
When selecting an introductory statistics course to fulfill a major/minor requirement, students should consult the Undergraduate Catalog and/or the department to confirm the course they want to register for will fulfill the requirement.
Learning Objectives
1. Use statistical software to wrangle data (i.e., manage and process data).
2. Use statistical software to perform exploratory data analyses. That is, explore data numerically and visually to gain understanding through data and generate hypotheses and inferences to later test.
3. Recognize the importance of data collection, identify limitations in data collection methods, and determine how they affect the scope of inference.
4. Have a conceptual understanding of the unified nature of statistical inference.
5. Apply estimation and testing methods to analyze single variables or the relationship between two variables in order to understand natural phenomena and make data-based decisions.
6. Model numerical response variables using a single or multiple explanatory variable(s).
7. Interpret results correctly, effectively, and in context without relying on statistical jargon.
8. Critique data-based claims and evaluate data-based decisions.
Teaching Method
The course is taught using a blend of flipped and discussion/lecture design. Most classes will be devoted to daily class activities where students will either work by themselves or in groups. We also come together to discuss the work towards the end of class. Students will be expected to adequately prepare for each class, so they are able to work through the daily activities and discuss the work with instructors and fellow classmates. Each class will typically end with a discussion of the concepts and ideas for that day's material. There will be some days that will be more discussion/lecture oriented, but for the most part classes will be dedicated to working with real data.
Evaluation Method
Students will be evaluated through (1) activities/small assignments; (2) reading checks; (3) exams; (4) a final project
Class Materials (Required)
(1) Free online textbook, Introduction to Statistics and Data Science (https://nustat.github.io/intro-stat-data-sci/)
(2) Free statistical software Posit Cloud (https://posit.cloud)
Class Attributes
Empirical and Deductive Reasoning Foundational Dis
Formal Studies Distro Area