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Section 1. Course description.
Advanced Statistical Methods
Course type: Corso per dottorandi
Value in ECTS: 1.5
Registrazione online/ Online Registration: http://www.phdsubscription.lu.usi.ch
14 February 2012: 13:30-17:00, Aula 402
16 February 2012: 13:30-17:00, Aula 402
21 February 2012: 13:30-17:00, Aula 251
23 February 2012: 13:30-17:00, Aula 402
The class will prepare graduate students for quantitative research. The class is designed to increase knowledge about commonly used statistical tests including their purpose, how they relate to hypotheses, how to interpret and explain them, their limitations and how to perform them using SPSS (and to a lesser extent MS Excel). The class will primarily consist of applied hands-on activities and interaction with other students. Other topics will be covered as suggested by students. The class will be structured around the specific research needs of students.
Upon successful completion of the class, students will be able to:
- understand the meaning and use of statistical significance in inferential statistics and Type I/Type II errors.
- understand different types of data and the consequences for statistical tests.
- comprehend and interpret statics reported in research and reports especially bivariate and multivariate statistics such as x2 , T tests, F tests, correlation coefficients, regression coefficients along with model goodness of fit measures such as R2 .
- understand the appropriate use of various statistical tests, with an emphasis on the underlying assumptions associated with each statistical method.
- create database for use in statistical analyses (create new data set, download data from online sources such WHO, ICPSR, open data files in SPSS and MS Excel, use SPSS set up files).
- perform data management tasks, cleaning data files, handling missing data, labels.
- translate hypotheses into operationalized variables through management procedures such as recoding, transforming and constructing variables.
- conduct various statistical tests, including contingency tables, difference of means, correlation, analysis of variance, ordinary least squares regression, in SPSS and R.
- manage and comprehend SPSS output as well as the ability to edit tables, graphs, figures, and export output to other documents.
- 1design and construct appropriate presentation format for statistical tests.
- explain statistical results (written and oral).
Section 2. Orientation info.
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