Universitatea de Medicină şi Farmacie Grigore T. Popa Iaşi Comisia pentru asigurarea calităţii DISCIPLINE RECORD/ COURSE / SEMINAR DESCRIPTION

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1 Universitatea de Medicină şi Farmacie Grigore T. Popa Iaşi Comisia pentru asigurarea calităţii DISCIPLINE RECORD/ COURSE / SEMINAR DESCRIPTION 1. Information about the program 1.1. UNIVERSITY: GRIGORE T. POPA UNIVERSITY OF MEDICINE AND PHARMACY OF IAŞI 1.2. FACULTY: MEDICAL SCHOOL / DEPARTMENT VI: PREVENTIVE MEDICINE AND INTERDISCIPLINARY 1.3. SUBJECT: MATHEMATICS-COMPUTER SCIENCE 1.4. STUDY FIELD: MEDICINE 1.5. STUDY CYCLE: UNDERGRADUATE 1.6. STUDY PROGRAMME: IN ENGLISH 2. Subject data 2.1. SUBJECT: 2.2. Module leader: Prof. Gabriel Dimitriu, PhD 2.3. Seminar leader: Lecturer Adrian Doloca, PhD 2.4. Year of study I I 2.5. Semester in which is taught I/II 2.6. Evaluation type C1/E Subject status Compulsory 3. Duration of the course (hours per semester) 3.1. Number of hours / week 3.4. Total number of learning hours 4 (1 st sem.) 3 (2 nd sem) Number of hours / week 3.5. Total number of learning hours 2 (1 st sem.) 1 (2 nd sem) 28 (1 st sem.) 14 (2 nd sem) Seminar / lab 3.6. seminar / lab 2 (1 st sem.) 2 (2 nd sem) 28 (1 st sem.) 28 (2 nd sem) Distribution of activities in the course (1 st sem./ 2 nd sem) hours Study based on the manual, printed course, bibliography and notes 14/10 Additional research in the library, on specialized e-platforms and field study 10/3 Preparation for seminars, practical courses, portfolios and essays 14/14 Tutoring 3/3 Assessment 3/3 Other activities Number of hours of individual study 41/ Number of hours per semester 100/ Number of ECTS 4/3 4. Previous Knowledge (if applicable) 4.1. course related Not applicable 4.2. skill related Not applicable 5. Requirements (if applicable) 5.1. course conditions The courses will be held in a lecture hall using a computer and a video projector 5.2. seminar / laboratory conditions Using the computer network in the computer laboratory

2 6. Specific Skills Acquired Professional skills displayed by knowledge and skills Transversal skills (role skills, professional and personal skills) To know the terminology used in informatics To prove the ability to use correctly, in specific contexts, the basic notions in informatics and statistics To prove competence in the analysis and interpretation of descriptive statistical parameters and confidence intervals. To identify and choose adequate statistical methods to solve different problems To perform spreadsheet computations (MS Excel) for pharmaceutical data management To handle hypothesis tests (comparison tests: z-test, t-student, Fisher). To know methods for calculating and interpreting linear regression and correlation coefficient To demonstrate permanent concern for scientific training To be involved in various activities, such as symposiums, congresses, creation of scientific studies To attend scientific projects, compatible to the requirements of the European educational system 7. Course Objectives (confirmed by the grid of specific skills acquired) 7.1. General Objective To be able to perform a descriptive statistics for a given experimental data set To be able to perform an inferential statistics for a given experimental data set 7.2. Specific Objectives To know the program MS Excel for managing pharmaceutical data, descriptive calculations and a basic statistical analysis 8. Contents 8.1. Course (1 st semester) Teaching Methods Observations The objectives of the discipline. The contents of the lectures. General notions about information theory. The representation of the Excel information. Computer, algorithm, programming language. examples. Informatics areas of application The architecture of the computers. The components of the computer: central processing unit (CPU), internal memory, interface equipments, peripheral equipments Windows operating system. Software categories. What is an operating system? The characteristics of the Windows operating system. Windows versions. Archive programs. Antivirus programs. Program MS Excel (I): Essentials of the Excel program. Orientation in Excel documents (spreadsheets). Relative and absolute references. Working with spreadsheets in MS Excel. Using formulas in a spreadsheet. Program MS Excel (II): Building plots (charts) in Excel (also using Chart Wizard). Types of plots in Excel. Printing spreadsheets in Excel. Program MS Excel (III): PivotTables and PivotCharts (I) - Creation of a PivotTable. Creation of a PivotChart. Examples. Program MS Excel (IV): PivotTable and PivotCharts (II) Using filters in PivotTables. Data totalization in Excel. Examples. Excel functions: DAY, MONTH, YEAR, WEEKDAY, INT, MOD, FACT, ABS, MAX, MIN, IF, COUNT, COUNTIF, SUM,

3 SUMIF,PRODUCT, SUMPRODUCT, AVERAGE, AVERAGEIF, AVEDEV, VAR, STDEV, GEOMEAN, HARMEAN, SUMX2MY2, SUMX2PY2, SUMXMY2 Program MS Access (I): Introduction. Basic notions. Creation of a table belonging to a MS Access database. Program MS Access (II): Creation/opening a MS Access database. Update the structure of a table in MS Access database. Sorting and filtering in MS Access. Program MS Access (III): SQL language. Database interrogations using SQL queries. Program MS Access (IV): Relationships between tables belonging to a MS Access database. Program MS Access (V): Design and usage of the forms in MS Access. Program MS Access (VI): Design and usage of the reports in MS Access. Program MS Access (VII): Import and export data in MS Access. Presentation of the statistical data. The position parameters. Measuring of the data variation. The variation parameters: simple and synthetic parameters of variation. Variance and standard deviation. Coefficient of variation. The inter-quartile range. The selection of the variation parameters. Centered and absolute moments. The definition of the centered and absolute moments. The relationship between centered and absolute moments. The shape parameters: skewness parameter and kurtosis parameter Elements of the probability theory. Random variables and probability laws. Discrete random variables. Continuous random variables. The probability density function. The repartition function. The characteristics of the probability distributions. The standard (reduced) normal distribution and the general normal distribution. Statistical sampling. The estimation of the parameters. The estimation of the characteristics of a population. Confidence intervals for the representative population parameters. Determining the minimum sample size. Testing hypotheses. The comparison between the sample mean and the representative population mean. The comparison between the means of the two populations. The comparison of the two sample variances. Analysis of the relationships between phenomena. Regression and correlation. MS MS MS MS MS MS MS Bibliography 1. Wayne D. Biostatistics Basic Concepts and Methodology for the Health Sciences. John Wiley&Sons, van Bemmel JH, Musen MA (editors). Handbook of Medical Informatics. Springer, Bland M. An Introduction to Medical Statistics. Oxford University Press, Boiculese L, Dascălu C, Dimitriu G, Moscalu M, Doloca A. Metode descriptive și elemente de analiză

4 statistică a datelor medicale. Iași: Ed. Performantica, Boiculese L, Dimitriu G, Moscalu M. Elemente de Biostatistică. Iaşi: Ed. PIM, Dimitriu G, Doloca A. Introducere în informatică. Iaşi: Ed. CERMI, Seminar / Practical lessons Teaching Methods Observations Presentation of the computer network facilities in the computer laboratory and the programs installed on this computer network. Windows operating system. Working with several windows in Windows operating system. Copying, moving and selection one/many objects (files, folders) using Windows. Creation of the formulas using Equation Editor in MS Word. Program MS Excel: Orientation in Excel spreadsheets. Applications. Program MS Excel: Building plots, introducing the formulas in Excel, setting the order of the operators in a formula, modify/delete/copy/move a formula in Excel. Relative and absolute references in Excel. Applications.Program MS Excel: Using the statistical Excel functions in data processing. Applications. Program MS Excel: PivotTables and PivotCharts. Applications. Program MS Access: Creation of a MS Access database using templates. Applications. Program MS Access: Creation/opening a MS Access database. Update the structure of a table in MS Access database. Sorting and filtering in MS Access. Applications. Program MS Access: SQL language. Database interrogations using SQL queries. Applications. Program MS Access: Relationships between tables belonging to a MS Access database. Applications using different MS Access databases. Program MS Access: Design and usage of the reports in MS Access. Applications. Practical exam Colloquium Multiple choice test 8.2. Seminar / Practical lessons (2 nd semester) Teaching Methods Observations Introduction. Presentation of statistical date. Classification. Exemples Excel template for information processing calculation of average, sorting, filtering Calculation of descriptive statistical parameters in MS-Excel (I) Calculation of descriptive statistical parameters in MS-Excel (II) Events and probabilities

5 Formula of total probability and the Bayes theorem Calculation of probabilities Calculation of probabilities based on PDF and CDF functions Confidence intervals (I) Confidence intervals (II) Statistical hypotheses testing (I) Statistical hypotheses testing (II) Linear regression analysis Practical exam Multiple choice test Bibliography 1. Wayne D. Biostatistics Basic Concepts and Methodology for the Health Sciences. John Wiley&Sons, van Bemmel JH, Musen MA (editors). Handbook of Medical Informatics. Springer, Bland M. An Introduction to Medical Statistics. Oxford University Press, Boiculese L, Dascălu C, Dimitriu G, Moscalu M, Doloca A. Metode descriptive și elemente de analiză statistică a datelor medicale. Iași: Ed. Performantica, Boiculese L, Dimitriu G, Moscalu M. Elemente de Biostatistică. Iaşi: Ed. PIM, Dimitriu G, Doloca A. Introducere în informatică. Iaşi: Ed. CERMI, *** Biostatistics. 8. *** Microsoft Excel. 9. The agreement between the course contents and the expectations of the representatives of the epistemic communities, professional associations and employers in the field related to the program The knowledge acquired in the field of informatics and biostatistics is a goal in scientific training of future pharmacists. The statistical analysis and interpretation of the pharmaceutical data improves the pharmaceutical expertise. 10. Assessment Activity Course Assessment criteria Colloquium (1 st sem) / Exam (2 nd sem) Assessment methods Percentage of the final grade Multiple choice test 50% Seminar / Practical exam Multiple choice test 35%

6 Practical lessons Knowledge testing during the Multiple choice test 15% semester Minimal standard of proficiency To achieve the minimum score 5 Date: Signature of Coordinator for Teaching Activities Prof. Gabriel Dimitriu, PhD Date of indorsement in the Council of the Department Signature of The Department Director Assoc. Prof. Georgeta Zanoschi, PhD