Treatment of data
[IEPR1003]
[15h + 15h] 4 credits
Teacher(s): Philippe Gérard(coord.)
Language: French
Level: First
Aims
Specifically, it correctly interpret graphical representations of data and key indicators of descriptive statistics. It may also have access to sources of scientific information (consultations of databases, references ...)
Main themes
- Construction and interpretation of graphs
- Descriptive analysis of data (concept of sample, indicators of average and dispersion, interpretation of level of service ...)
- Search for library materials, database consultation and construction of a thematic bibliography.
This introduction to the processing and analysis of scientific data will be made from specific materials to EDPH or KINE.
Content and teaching methods
Theoretical:
o Different types of data,
o Concepts of population and sample
o absolute frequency tables, cumulative frequency of relative frequencies and cumulative relative frequencies,
o Representation of data in tables and graphs,
o Key indicators of central tendency,
o Key indicators of dispersion,
o Concept of probability,
o normality distribution
o Hypothesis homoscédasticité,
o parametric tests and nonparametric tests,
o Comparisons of 2 and several medium and 2 or more rows means (for dependent or independent samples) (concept of post-hoc)
o Comparisons of proportions (and conditions of use of different tests),
o Relations between continuous variables, calculation of correlation and interpretation of correlation coefficients,
o Coefficient of determination
o Relationship between variables.
Practical:
o Discover the Excel software
- Mathematical functions, logical, dates - hours, statistics and text,
- Representation of data in tables or graphs.
o Discovery of statistical software SPSS
- Links between SPSS and Excel (import data)
- Documentation files * sav,
- Descriptive analysis (variables [frequency] and continuous variables [central tendency and dispersion]),
- Graphical representations as SPSS,
- Splitsing file
- Selection of topics (select cases)
- Verification of normal distribution of variables
- Comparison of two independent samples
? Parametric Comparisons
? Comparisons nonparametric
- Comparison of more than two independent samples
? Parametric Comparisons
? Comparisons nonparametric
- Comparing two dependent samples
? Parametric Comparisons
? Comparisons nonparametric
- Analysis of correlations (parametric and nonparametric)
Methods:
lectures by audience
exercises supervision in computer classes or independently.
Other information (prerequisite, evaluation (assessment methods), course materials recommended readings, ...)
Evaluation Review written or oral and / or elements of continuous assessment
Syllabus support and / or book (s)
Encadrement Holder (s) and / or assistant (s), help (s) by any student (s) monitor (s)
Other Content to articulate with the Master's course: "Statistical and Research Methodology motricity"