This course presents the basic concepts of probability and statistics useful in the field of psychology. By the end of the course, the students will be able to :
- understand and explain the concepts covered in class
- recognize the kind of method to use for a given problem
- use each tool and apply it in various situations
- follow a systematic procedure to resolve an open problem, from the choice of method, its application and validation to the interpretation of the results obtained
- have a good understanding of the fields of application of statistics in psychology and of the situations they will encounter
Main themes
Descriptive statistics :
- graphic and numeric tools to summarize the available information about one or two qualitative and/or quantitative variables: frequency tables, bar charts, distribution functions, histograms, box-plots, means, variances, standard deviations, correlation coefficients (Pearson, Kendall and Spearman), X-Y graphs, etc.
Probability :
- definition of probability, basic combinatory calculation, formulas for basic probability calculation, independence, conditional probability, Bayes' theorem, discrete and continuous random variables, uniform, binomial and normal distribution, central limit theorem
Statistical inference :
- notions of estimation, confidence interval and hypothesis tests. Inference on the means and variances of one or two normal populations and one or two proportions.
Content and teaching methods
Content
The course has three parts.
First, the basic techniques of descriptive statistics are covered. This relates particularly to graphic and numerical tools to summarize the available information in terms of one or two qualitative and/or quantitative variables.
Second, the basic concepts of probability theory are introduced e.g. formulas for probability calculation, concepts of independence and conditional probability, Bayes' theorem, discrete and continuous random variables, central limit theorem etc.
Third, the final part will present the basic concepts of statistical inference: notions of estimation, confidence interval and hypothesis tests are explained and applied to the inference on the means and variances of one or two normal populations and on one or two proportions.
Methods
Lectures and exercises. The exercises are in small groups and are supervised by assistants.
Other information (prerequisite, evaluation (assessment methods), course materials recommended readings, ...)
Prerequisites : none
Assessment : written examination.
Support : theory manual, exercise manual and transparencies from lectures