Statistics for Economics and Management
Code
1305
Academic unit
null
Department
null
Credits
7,5
Teacher in charge
Luis Catela Nunes
Teaching language
English
Objectives
On a daily basis, economists and managers are confronted with decision-making processes in contexts of uncertainty. Statistics offers a number of tools allowing the measurement of this uncertainty by making use of statistical data, thereby leading to better decisions. The Statistics for Economics and Management course focuses primarily on inferential statistics whose purpose is to better understand particular characteristics of a given population using only sample data, whether they are observational or experimental.
One of the main objectives of this course is that students develop the ability to think statistically. Statistical thinking means the understanding of the necessity, the advantages and the limitations of available data, and the ability to conduct a statistical study in its various phases, since the formulation of the problem, through data collection and statistical analysis, to the interpretation of results. It is intended that students recognize that the real world is a complex system of interconnected processes, that there is variability in all processes, and that understanding and reducing variability is a critical factor for success. Recognizing the omnipresence of variability is part of the essence of Statistics.
This course focuses on understanding fundamental statistical concepts, on developing the ability of using basic tools of statistical inference in solving real world problems, and on the interpretation of results. Mathematics and probability theory will be used in order to obtain a better understanding of the applicability of statistical inference or when it is necessary to identify the conditions under which statistical inference is valid.
Prerequisites
Mandatory Precedence:
- 1304. Data Analysis and Probability
Subject matter
This course will cover the following topics (the recommended textbook chapters appear in parentheses):
Continuous random variables and distributions (5);
Point and interval estimation (6, 7, 8);
Hypothesis testing (9, 10, 14);
Simple and multiple linear regression (11, 12, 13).
A detailed calendar of all activities and topics covered throughout the semester will be posted in moodle.
Bibliography
The textbook used in the course is: Newbold, Carlson, and Thorne, Statistics for Business and Economics, Pearson Education, 2013 (the latest edition is the 8th; but any other edition can be used although the numbering of the chapters and exercises differs).
All informations, announcements, slides, homeworks, databases, and other material, will be available on the course moodle webpage at: http://moodle.novasbe.pt
Teaching method
The understanding of key statistical concepts and tools and the development of statistical thinking is achieved through the use of several real world examples. Various problems and actual case studies are presented and explored in the lectures (2 per week) and practical sessions (1 per week). The fundamental concepts of statistics and the mathematical derivation of the fundamental results are covered in detail during the lectures. In the practical sessions, several problems and exercises are discussed, and it is important that students participate in the discussion by presenting their solutions, suggestions, questions, and comments. For these practical sessions, students must form groups (maximum of 3 students per group) to work on the various issues proposed along the course and to prepare the final course assignment. For some practical sessions, and according to the instructions of the TAs, students should bring a laptop /tablet (at least one per group) to work on projects that use data collected from the internet or databases in Excel. In the moodle page will be posted several "quizzes" for each topic that all students must answer for a self-evaluation of their knowledge. The moodle page also offers a discussion forum that students should use (respecting the instructions referred there) as a learning tool by sharing suggestions, questions, discussions, or other topics relevant to the course.
Evaluation method
The final grade in the course is calculated according to the following weights:
Midterm exam: 35%
Final exam: 50%
Final course assignment: 15%
Quality of class participation and homeworks: will be taken into account to adjust up/down or maintain the final grade obtained from previous components.
The final exam covers all topics of the course. If the grade in the final exam is less than 8.0, the student will fail regardless of the remaining components of the assessment.
A students that misses the midterm exam will have a grade of 0 (zero) on that midterm exam. If this absence is regarded as justified by the Pedagogical Council, the final exam will include a set of additional questions about the topics assessed in the midterm exam. In this case, the grade obtained in the additional questions will replace the midterm exam grade. If the final assignment is not delivered by the deadline announced in moodle it will have a grade of 0 (zero).
For students enrolled in grade improvement, the grade obtained in the final exam counts 100%. For students who undertake the resit and special final exams, the grade on that exam counts 100% for the final grade.
The final and midterm exam will include a formula sheet (available in moodle) and tables with statistical distributions. The only material allowed in the midterm and final exams is a pen and an electronic calculator. No additional information sources, beyond those that appear in the exam sheet, are allowed.