Introduction to probabilistic and statistical reasoning, including probability distribution models and applications to current scientific/social issues. Roles of probability, study design, and exploratory/confirmatory data analysis. Prerequisite: Two years high school algebra. No credit for Sophomores, Juniors, or Seniors in the mathematical and engineering sciences.
Open to Degree and CDE students
This isn’t a course about the tools of statistics…it’s about statistical ideas and their impact on everyday life, public policy, and many different fields of study. You will learn some tools, of course, though you need little formal mathematics. If you can read and use simple equations, you are in good shape. Be warned, however, that you will be asked to think! Thinking exercises the mind more deeply than following mathematical recipes. This course is divided into four parts: i. Data production describes methods for producing data that can give clear answers to specific questions. Where the data come from really is important—basic concepts about how to select samples and design experiments are the most influential ideas in statistics. ii. Data analysis concerns methods and strategies for exploring, organizing, and describing data using graphs and numerical summaries. You can learn to look at data intelligently even with quite simple tools. iii. Probability is the language we use to describe chance, variation, and risk. Because variation is everywhere, probabilistic thinking helps separate reality from background noise. iv. Statistical inference moves beyond the data in hand to draw conclusions about some wider universe, taking into account that variation is everywhere and that conclusions are uncertain.
Stat 051 is a course with a focus on developing conceptual understanding of inferential logic. Students finishing STAT 051 students should be able to: • Understand and recognize appropriate methods for producing data. • Create and interpret basic descriptive statistics and graphs. • Recognize when it is appropriate to use sample data to infer information about a population. • Critically examine the way in which data is collected and explain how data collection impacts the type of inferences that can be made. • Interpret information from a variety of data visualizations and recognize different ways that multiple variables can be included in a display. • Calculate confidence intervals and interpret them effectively and in context. • Formulate and test statistical hypotheses and interpret results effectively and in context. Some brief content material (text readings and videos) will be assigned and due the night prior to each day’s class when that material is discussed. The videos will have embedded questions to gauge student’s understanding of the material.
** Please note this is subject to change** Item* Weight % Grading # of Drops** Pre-Class Prep 10 % Completion 2 Homework 15 Graded 2 Quizzes (7) 60 Graded 1 Final Exam 15 Graded 0
Kalkin Building 007 (View Campus Map)
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