Statistics: QR:Basic Statistical Methods 1

Foundational course for students taking further quantitative courses. Exploratory data analysis, probability distributions, estimation, hypothesis testing. Introductory regression, experimentation, contingency tables, and nonparametrics. Computer software used. Credit not awarded for more than one of STAT 141 or STAT 143.

Dates: May 22 - June 30, 2023 Credit not given for more than one of STAT 141 or 143. Asynchronous online

The main goal of this course is for you to be statistically literate. The goal is not to memorize a lot of formulas and procedures, but to understand the thinking that goes into using data to understand the world, so that you can use statistical results, and basic statistical methods successfully in their field of study and in daily life.

1: Students should gain an understanding of and appreciation for the utility and limitations of data and statistical methods for solving real-world problems. 2: Students should gain an appreciation for the methods of data collection, including an understanding of potential pitfalls, biases, and ethical issues. 3: Students should gain facility with the terminology, notation, and tools generally found in an introductory statistics course. In particular, students should be comfortable reading and understanding an article citing summarized statistics, and be able to dissect it into relevant course-related components. 4: Students should demonstrate a basic understanding of the laws and rules of probability, and how they relate to statistics, particularly the ideas of randomness and statistical significance. 5: Students should demonstrate facility with basic statistical methods, including confidence intervals and hypothesis tests, and more importantly, students should understand when a particular method is appropriate, and how to appropriately interpret results in the context of a stated problem. 6: Students should be able to formulate and communicate solutions to problems in clear, grammatically correct, precise English.

The structure of this course is pretty straight forward. There are 5 content modules in the course that will cover about 18 chapters of the book. Each module is one week long with the week running typically Wednesday to Tuesday (11:59 PM). Modules will typically be open several days in advance so as to allow folks to work ahead. Each module will cover between 2-5 chapters to from the textbook. Each chapter will have a narrated PPT video that covers the ‘highlights’. Most chapters will also have a narrated application/example problem. There will be an assignment for each chapter in MyStatLab (MSL). At the close of each module there will be timed test. All tests will be ‘open notes’. MyStatLab (MSL) Homework 25 % (25% late penalty per day) Tests (5 @ 15%, also in MSL) 75 % Extra Credit possible