Training and Research

PhD school courses/classes - 2023/2024

Please note: Additional information will be added during the year. Currently missing information is labelled as “TBD” (i.e. To Be Determined).

PhD students must obtain a specified number of CFUs each year by attending teaching activities offered by the PhD School.
First and second year students must obtain 8 CFUs. Teaching activities ex DM 226/2021 provide 5 CFUs; free choice activities provide 3 CFUs.
Third year students must obtain 4 CFUs. Teaching activities ex DM 226/2021 provide 2 CFUs; free choice activities provide 2 CFUs.

Registering for the courses is not required unless explicitly indicated; please consult the course information to verify whether registration is required or not. When registration is actually required, no confirmation e-mail will be sent after signing up.

Teaching Activities ex DM 226/2021: Linguistic Activities

Teaching Activities ex DM 226/2021: Research management and Enhancement

Teaching Activities ex DM 226/2021: Statistics and Computer Sciences

Teaching Activities: Free choice

Credits

1

Language

English

Class attendance

Free Choice

Learning objectives

The course will provide an overview on the methods to compute sample size necessary to achieve an adequate precision in estimating proportions or an adequate statistical power to compare the means of two independent or dependent samples, or the proportions of two independent samples. The concepts of statistical power, statistical precision, sample size and effect size will be reviewed. Statistical power computations will be illustrated by Excel files and Stata software. Participants will be encouraged to bring power calculation problems, to be used as examples in the class.

Prerequisites and basic notions

Students should have basic knowledge of Mathematics and Statistics.

Program

Confidence interval and precision of the estimate. Methods to compute sample size necessary to achieve an adequate precision in estimating proportions.
Probability of type II error and power of a statistical test. Methods to compute sample size necessary to achieve an adequate statistical power to compare the means of two independent or dependent samples, or the proportions of two independent samples.

When and where

Lessons will take place in the computer room. Statistical power computations will be illustrated by Excel files and Stata software (Stata and R-commander). Participants will be encouraged to bring power calculation problems, to be used as examples in the class.

Learning assessment procedures

A written exam will be administered. Students will have to compute sample size in a given problem.

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE

Assessment

The exam will evaluate not only the acquisition of statistical knowledge, but also the ability to adopt it critically to solve health problems.

Criteria for the composition of the final grade

The final mark will be expressed on a scale ranging from 0 to 30. A minimum mark of 18 will be required in order to pass the exam.

Scheduled Lessons

When Classroom Teacher topics
Thursday 02 May 2024
14:00 - 18:00
Duration: 4:00 AM
https://univr.zoom.us/j/92638650019 Giuseppe Verlato DETERMINATION OF SAMPLE SIZE TO ACHIEVE A PREDEFINED PRECISION OR POWER

Faculty

B C F G K L M R S T V Z

Battaglia Yuri

symbol email yuri.battaglia@univr.it

Bertoldo Francesco

symbol email francesco.bertoldo@univr.it symbol phone-number +39 045 812 6485

Carrara Elena

symbol email elena.carrara@univr.it

Ciccocioppo Rachele

symbol email rachele.ciccocioppo@univr.it symbol phone-number 045 8124466

Crisafulli Ernesto

symbol email ernesto.crisafulli@univr.it symbol phone-number +39 045 812 8146

Fantin Francesco

symbol email francesco.fantin@univr.it symbol phone-number +39 045 812 3577

Fava Cristiano

symbol email cristiano.fava@univr.it symbol phone-number +39 045 8124732

Fratta Pasini Anna Maria

symbol email annamaria.frattapasini@univr.it symbol phone-number +39 045 8124749

Frulloni Luca

symbol email luca.frulloni@univr.it symbol phone-number 045 8124466

Gatti Davide

symbol email davide.gatti@univr.it

Girolomoni Giampiero

symbol email giampiero.girolomoni@univr.it symbol phone-number +39 045 812 2547

Gisondi Paolo

symbol email paolo.gisondi@univr.it symbol phone-number +39 045 812 2547

Krampera Mauro

symbol email mauro.krampera@univr.it symbol phone-number 0458124034

Lanza Massimo

symbol email massimo.lanza@univr.it symbol phone-number +39 0458425118

Mantovani Alessandro

symbol email alessandro.mantovani@univr.it symbol phone-number 0458127672

Mazzali Gloria

symbol email gloria.mazzali@aovr.veneto.it symbol phone-number +39 045 807 3577

Minuz Pietro

symbol email pietro.minuz@univr.it symbol phone-number +39 045 812 4414

Romano Simone

symbol email simone.romano@univr.it symbol phone-number 0458124414

Rossini Maurizio

symbol email maurizio.rossini@libero.it symbol phone-number +39 045 8126338

Sacerdoti David

symbol email DAVID.SACERDOTI@UNIVR.IT symbol phone-number 0458128159

Targher Giovanni

symbol email giovanni.targher@univr.it symbol phone-number +39 045 6014530

Trifirò Gianluca

symbol email gianluca.trifiro@univr.it symbol phone-number 0458027612

Viapiana Ombretta

symbol email ombretta.viapiana@univr.it symbol phone-number +39 045 812 4049

Zamboni Mauro

symbol email mauro.zamboni@univr.it symbol phone-number +39 045 812 2537

Zoico Elena

symbol email elena.zoico@univr.it symbol phone-number +39 045 812-2537

Zoppini Giacomo

symbol email giacomo.zoppini@univr.it symbol phone-number +39 045 8123115

PhD students

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Course lessons
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Guidelines for PhD students

Below you will find the files that contain the Guidelines for PhD students and rules for the acquisition of ECTS credits (in Italian: "CFU") for the Academic Year 2023/2024.