- Docente: Sara Capacci
- Credits: 5
- SSD: SECS-S/03
- Language: English
- Teaching Mode: Traditional lectures
- Campus: Bologna
- Corso: Second cycle degree programme (LM) in Health Economics and Management (cod. 8880)
Learning outcomes
The course will introduce students to descriptive statistics, hypothesis testing and linear regression in a healthcare setting. At the end of the course students will be able to perform basic statistical analyses on healthcare data and interpret and discuss the results. The course will prepare students for the course in Econometrics.
Course contents
- Descriptive statistics: measures of central tendency, measures of dispersions and graphical displays
- Random variables, probability distributions, the Normal Distribution, the Standard Normal Distribution, the Student’s T distribution
- Populations and samples, point estimation and confidence intervals for a population mean for the case of known and unknown variance.
- Hypothesis testing for the mean and for the difference between two means
- Introduction to Simple and Multiple Regression
Readings/Bibliography
- Rosner, B. (2016) “Fundamentals of Biostatistics”, Cengage.
- Plichta Kellar, S.B. and Kelvin, E.A. (2013) “Munro's statistical methods for health care research”. Wolters Kluwer Health/Lippincott Williams & Wilkins.
Teaching methods
During the course theoretical and practical sessions will be held. During practical sessions empirical knowledge of the proposed methods will be reached through real-world case studies performed using Stata.
Stata is available in all the computer labs in the Campus. Moreover, a Campus licence of Stata is available to all students enrolled in the course.
The UNIBO e-learning platform (VIRTUALE) will be used to share teaching materials and to assign periodical home assignments to students.
Home assignments serve to reinforce class concepts and get familiarity with the software. Students are allowed and encouraged to work together on home assignments. However, a separate write-up is expected from each student, in his/her own words. Home assignments will not be graded, and solutions will be provided.
Assessment methods
Online test. The course has a required cumulative final examination. You must take, and pass, the final examination to receive a passing grade in the course. The final exam will be an online test on the EOL platform. Students are required to enrol using Almaesami.
Extra credits opportunities. During the course, it will be possible to earn extra credits, which will be added to the online test grade. Details will be provided in class.
The grading system is on a 0-30 range, the following grid applies:
- <18 failed
- 18-23 sufficient
- 24-27 good
- 28-30 very good
- 30 cum laude honors
Teaching tools
The following tools will be available on the UNIBO e-learning platform (VIRTUALE)
- Slides/lecture notes: summarising theoretical concepts shown in class
- Do files, lecture notes and Stata datasets: with these tools students are able to follow the practical sessions step by step and to completely replicate them at home.
- Stata Assignments and Solutions which will be regularly proposed to students
- Miscellanea: exercises, focus notes, sample tests will be uploaded when needed
Office hours
See the website of Sara Capacci