Преподавател(и):

проф. Стефан Матеев  д.н.
гл. ас. Кирил Костов  д-р

Описание на курса:

Компетенции:

The students will know

- the logical basis of the statements and inferences from psychological data

- the meaning of the most common terminology in the analysis of psychological data

The students will be able

- to carry out the most relevant analyzes of data from psychological studies

- to present data and conclusions according to the world standards

- to better understand and critically to evaluate texts that contain data from psychological studies.

Предварителни изисквания:
Good knowledge of the high-school mathematics. Knowledge in statistics is welcome!

Форми на провеждане:
Редовен

Учебни форми:
Лекция

Език, на който се води курса:
Английски

Теми, които се разглеждат в курса:

1. Introduction: the problems with treating data from groups of individuals. Variables and their measurement. Operations with variables. From the scale of measurement to the statement and vice versa. Illustrating of empirical data with figures

2. The problem with the list of data. Describing the data by tables and figures. Distributions and percentiles. Comparisons between data on the basis of percentiles

3. Description of data “on average”. Meaningful, meaningless, and wrong statements based on mean values. The shape of the distribution and its role in the description.

4. Description of data "with three words only". Normally distributed data and their properties. Standardization of data: z-values, Т-values, and their use in psychology.

5. The difference between groups of measurements. Effect size.

6. Exercises and Test 1

7. Association between variables. Graphical and analytical consideration of the association. The Pearson’s correlation index. Use and misuse of the index.

8. Correlation between variables measured in an ordinal scale. The role of the correlation on the effect size.

9. Correlation between variables measured in nominal scale. Meaningful, meaningless and wrong statements on the basis of the correlation between dichotomic variables. The Simpson paradox. Odds ratios, log-odds ratios, and their use in psychology

10. Correlation and causality. Use and misuse of correlation in inferring causality. Mediator and moderator variables

11. Belief, chance, risk and probability. Probability vs. relative frequency. Sampling. Measurement of population parameters. The confidence interval.

12. What is a statistical test. The concept of “significance” and its role in the psychological inference. Displaying results in tables and figures. Reading pictures of data. Determining sample size.

13. Psychological inferences when “significance” is established and when it is not established. The role of the effect size.

14. “Significance” of association between variables. Psychological inferences in cases of presence and lack of significance. Determining sample sizes.

15. Exercises and Test 2

Литература по темите:

1. Abelson, R. (1995) Statistics as principled argument. Lawrence Erlbaum Ass., Hillsdale, NJ

2. Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Lawrence Erlbaum Ass., Hilldale, New Jersey

3. Cumming G., Finch, S. (2005). Inference by eye. Confidence intervals and how to read pictures of data. American Psychologist, vol 60, 170-180

4. Glenberg, A.M. (1996) Learning from data: An introduction to statistical reasoning. Mahwah: Lawrence Erlbaum Ass.

5. Huck, S.W. (2009) Statistical misconseptions. New York, Taylor and Francis

6. Stout, W.F., Marden, J., Travers, K.J. (2000) Statistics: Making sense of data. Moebius, Rantoul

Средства за оценяване:

Two tests during the semester