Statistics III

General characterization

Prerequisites

n/a 

Bibliography

Newbold, Carlson and Thorne Statistics for Business and Economics, 8th Edition, Pearson Education, 2013 (Other editions of this book (6th and 7th) may also be used (the numbering of the chapters and exercises being different).

All the materials including lecture notes, homework, solutions, links to videos and web resources etc. will be available on our moodle site. 

Teaching method

Statistics III is a blended learning course with face to face - f2f - sessions and asynchronous remote sessions. It is mandatory that the assychronous sessions are completed and understood before the corresponding f2f session.

Students are welcome to bring their own devices (e.g IPhones, Smartphones, IPads, Notebooks) to all the f2f sessions as these are BYOD sessions: they will need to be connected during classes (to moodle and adequate sources of information in real time). The course will be driven through students' proposed Case Studies (CS) that will create the need of using the several statistical techniques. Students will re-call (and, if fact learn) the several techniques because they will need to apply them to solve problems. Every class will be a challenge to all: time consuming, yes, but extremely interesting as the students will live and understand statistics! Typically, the f2f sessions will follow asynchronous sessions in a flipped classroom mode. Students will be graded in every class for their learning effort, by solving individual quizzes. Extremely important : besides Mock exams, no exercises to solve will be provided! One of the goals of this course is to improve the students' research attitude and abilities ; this will be done generating scenarios such that analysis and discussion out from an usual, controlled, comfort zone will occur improving the students' self-confidence and esteem abilities in order to allow a higher level of performance (during the course and life).

Evaluation method

Quizzes: Formative - 5% and Summative - 15%

the time range for the quizzes will need to be checked by the student and depends on the class run; IMPORTANT: after the deadline, no re-opens will be done; additionally do not solve the Quizzes just for the Grade BUT make sure you understand everything involved when you are solving them t he worst grade for each Quizz type will be dropped Case study team report - 20% ( IMPORTANT : students are advised NOT to split tasks, making sure that all the work is shared and understood by all the team members: as you enroll in the moodle course make sure you look at the video about the what to do and what to avoid during your CS work, to make sure you Grade as expected) The CS final report grade will be rectified by an internal group peer grading using the following criteria: participation and knowledge.

Final Exam (minimum 8 (rounded) out of 20) - 60%

Final grade = Max (Final Exam; Weighted Grade) 

Subject matter

Main topics will include (the assumption is that these topics should be already familiar to the students, analysed before e.g. during their undergraduate level studies): inference statistics and distributions, contingency analysis, analysis of variance, simple and multiple linear regression. Excel, Gretl (freeware) and/or SPSS will be used to conduct the statistical analysis. Research papers will also be used as sources of indicators to be interpreted.

Programs

Programs where the course is taught: