This course offers a first introduction to Statistics so that the students feel comfortable when working and in a data analysis environment (e.g. during Statistics II and WP). This course improves mathematical and analytical thinking and reasoning, use of IT tools, encourages interpersonal relations and teamwork and provides learning experience in integrating knowledge across.
Weekly - Available soon
Total - Available soon
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, will be available in our moodle site.
Students are welcome to bring their own devices (e.g IPhones, Smartphones, IPads, Notebooks) to class as this is a BYOD course: you will need to be connected during classes (to moodle and adequate sources of information in real time).
The course will be driven through practical exercises. Students will learn solving exercises.
Classes will be divided into individual and team building knowledge. Students will be graded in every class for their learning effort, by solving individual and team quizzes.
Final exam (minimum 8 out of 20) – 70%
sources of information in addition to those previously mentioned are not allowed.
1) Descriptive statistics
o data structures and data types
o displaying data
? statistical indicators
• mean, mode, median
• percentiles / quartiles
• range, variance, standard deviation, coefficient of variation
? graphical analysis (histogram, box-plot, bar chart and pie chart)
2) Probabilities (outcomes, Venn diagram, the rules, conditional)
3) Random variables
o Discrete and continuous
o Some models
? Bernoulli, Binomial, Hypergeometric
? Uniform (discrete and continuous)
? Standard Normal (Z) and Normal
? Statistical Tables: Z and t-Student
4) A brief introduction to Statistical Inference
o Sample vs Statistical Population
o Estimates vs Parameters
? The mean value