Whether you realize it or not, statistics is a part of your everyday life. Increased awareness and literacy in statistics provides the opportunity to be a more informed citizen and consumer, a more critical analyst of research, and creates opportunities for more effective communication with data. This course is meant to improve your ability to understand and communicate with data that matters in the real world. This is a skill that you will likely need in other courses during your education at LUC and can be applied in your everyday life now and in the future. Whether you have had a statistics course before or whether the concepts are new to you, this course is an opportunity to develop your skills to understand presented data, as well as effectively communicate and analyzing data using statistical techniques.
The course assumes no prior knowledge of statistics, but participants who are less confident about their mathematical skills or less familiar with basic statistics should plan to spend additional time preparing for class using posted videos and readings.
After successful completion of this course, students are able to:
1. Understand the options for describing and presenting data
2. Understand basic principles of statistical inference
1. Apply statistical reasoning to real world examples
2. Effectively summarize data using descriptive statistics, tables, and graphs
3. Interpret and critically evaluate presentation of data and analysis in graphs and tables
4. Perform basic data description and analysis using the R software environment
Once available, timetables will be published in the e-Prospectus.
Mode of instruction
The course will involve interactive sessions to practice interpreting, analyzing, and displaying data from real world examples. Most of the conceptual learning will be done though online videos and readings. This learning will be reinforced through its application in in-class activities and discussions, which means that it is vital that students come to class prepared. We will also have interactive lab sessions to practice programming in R and producing figures and outputs to communicate quantitative data effectively.
Participation in class discussions and lab sessions – 5%, Weeks 1-7 (Learning outcomes 3, 5, 6)
Weekly in-class quizzes – 35%, Weeks 2-7 (Learning outcomes 1, 2, 5)
Lab assignments – 10 %, Weeks 1-7 (Learning outcomes 4, 6)
Group project presentation– 10%, Week 7 (Learning outcomes 3, 5, 6)
Final exam – 40%, Week 8 (Learning outcomes 3, 5, 6)
In accordance with article 4.8 of the Course and Examination Regulations (OER), within 30 days after the publication of grades, the instructor will provide students the opportunity to inspect their exams/coursework.
There is a no re-sit policy at Leiden University College.
There will be a Blackboard site available for this course. Students will be enrolled at least one week before the start of classes.
Derek Rowntree, Statistics without Tears: An Introduction for Non-Mathematicians (Penguin UK, 2018).
Video material from https://www.khanacademy.org/math/statistics-probability
David M. Diez, Christopher D. Barr, Mine Çetinkaya-Rundel, Open Intro Statistics, 4th edition (2015). This textbook can be downloaded for free at the website: https://www.openintro.org/stat/os4.php.
This course is open to LUC students and LUC exchange students. Registration is coordinated by the Education Coordinator. Interested non-LUC students should contact email@example.com.