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Courses in foreign languages Academic year Area subject code 2016-2017 - Title of course Statistics – data analysis Level I (undergraduate – B.A.) √ II (graduate – M.A.) √ III postgraduate (please check √) Time of implementation Number of hours ECTS Lecture(s) (name and last name) Title/position Affiliation (Institute, division) Course description Aim of the course Topics Required readings 1st semester √ 2nd semester√ 30 6 Magdalena Rowicka √ 1st +2nd semester (please check √) Ph.D. Academy of Special Education, Institute of Applied Psychology The course provided an extensive knowledge related to an application of statistics to psychology – starting from an overviews of basics of methodology and descriptive statistics (incl. random sampling and measurement scales), through the elements of probability, up to inferential statistics (factorial and linear). The course aims at enabling students to: understand that a great part of information has a statistical base; acquire an understanding of the concepts of statistics and probability which are useful and relevant for planning research and carrying out analysis; draw appropriate conclusions from the results of an application of statistical methods; interpret the conclusions of statistical analysis; be aware of the limitations and levels of accuracy of interpretations and conclusions; Part A. Descriptive statistics and basic probability. 1. Basic concepts, Mean, Median, Mode, Errors, Absolute and squared error of the Mean; Sd and variance, Skewness and Kurtosis; 2. Presentation of data – plots (incl. plots for two variables); 3. Normal distribution and it’s properties 4. Basics of probability 5. Hypothesis testing – introduction 6. Categorical data and chi-square (formulas and statistical tables) Part B. Statistical inference and tests 7. Correlation (parametric and nonparametric) 8. Psychometrics - Exploratory Factor Analysis 9. Simple regression 10. Confidence intervals 11. t-Student tests 12. Simple Analysis of Variance 13. Factorial Analysis of Variance 14. Repeated Measured Design 15. Multiple Regression, mediation and moderation models 16. Analyses of Variance and Covariance as General Linear Models Howell, D. (2010). Statistical methods for psychology. Wadsworth Cengage learning. McKinnon, D. (2008). Introduction to Statistical Mediation Analysis. Lawrence Erlbaum Associates Taylor & Francis Group. Teaching methods Workshop including: slide presentation, video presentation, calculations, Excel and SPSS exercises (SPSS will be provided on APS licence) Prerequisites Basic knowledge of mathematics; intermediate knowledge of methodology of scientific research (in psychology) 30% - Quizzes (short closed questions, problem questions, calculation questions); 20% - Homework (All open questions with calculations); 20% - Test A (first part of the material – descriptive statistics plus basic inferential statistics) 30% - Test B (from descriptive to inferential incl. factorial and linear tests) Assessment English Teaching language [email protected] Contact person for further information (name, e-mail, phone)