Face-to-face , second term, 30 hours of theory and 22,5 hours of exercises.

Second term
Thursday from 11:00 to 13:00 at 109 Marais 100

French

The course aims to study the main graphical and numerical methods of univariate and bivariate descriptive statistics, to introduce to the calculation of probability, and to present the first elements of inferential statistics: sampling distributions, point estimation, confidence interval, hypothesis testing, chi-square tests.

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For the Bachelor in Information and Communication :

For the Bachelor in Political Sciences: General :

For the Bachelor in Sociology and Anthropology :

The course outline is as follows:

1. Introduction: concepts of population and sample, sampling plan, sample selection, the sampling bias and errors, the concept of statistical variable...

2. Descriptive statistics: description of a qualitative variable (frequency table, bar chart, pie chart...), description of a quantitative variable (rank tables, histogram, cumulative curve, cumulative frequency curve, measures of centrality, measures of dispersion, the skewness and kurtosis coefficients...), joint description of two qualitative or quantitative variables, contingency table, marginal and conditional distributions, correlation coefficient, analysis of simple linear regression...

3. Probability: we will discuss the basic elements of calculation of probability and concepts needed for inferential statistics: random experiment, event and probability, conditional probability, independence of two events, random variable, main discrete and continuous distributions (binomial, normal, Student, chi-square, Fisher), distribution function, mean, variance, quantiles, percentiles...

4. Inferential statistics: sampling distribution of the sample mean, the principle of statistical estimation, central limit theorem, confidence intervals for the mean of a normal distribution, proportion confidence interval, general theory of hypothesis testing, test the mean parameter of a normal distribution, test of a proportion, chi-square statistic, Goodness of fit chi-square test, chi-square test of independence...

5. Analysis of statistical graphs from the Belgian and international press: highlighting good and bad statistical representations, intentionally or unintentionally biased or misleading graphs...

The course (30 hours) will introduce the main theoretical concepts. A prime example will be used as common thread: the analysis of answers to a survey carried out on 158 households in a neighbourhood of a big city. Many other examples will illustrate the subject matter.

Exercise sessions (22.5 hours) accompany the course. In addition to complete model exercises commented by the probationary lecturer, the students' personal research and work will be encouraged.

The final assessment is a written examination. It consists, on the one hand, of one or two questions of theory designed to verify the understanding of statistical concepts and ideas, as well as the analytical mind of the student, but also, on the other hand, of four or five practical exercises that will enable to assess the practical skills of the student, his ability to comprehend a problem, to analyse a set of statistical data, to choose the most appropriate statistical method and to correctly interpret the results obtained. These exercises will be of the same level of difficulty as those solved in class or during tutorials.

The following documents are made available to students: a course syllabus, complete and detailed, a copy of the slides used in the lecture, a workbook and a list of references works on which the courses and exercises are based, and in which the student will find information, clarifications or additional illustrations of the subject matter.

The references books of the course and tutorials are available at the library of the University.

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