## PSYE112 Reasoning Skills

### Annotation:

The aim of the course is to develop the logical and numerical reasoning skills of students. The students will be trained to recognize arguments and analyze their validity and soundness, and to draw valid conclusions from given premises. The course also will provide the basic skills needed to understand, analyze, and present numerical information related to empirical research in psychology.

### Lecturers:

**Prof. Lilia Gurova, PhD**

**Prof. Maurice Grinberg, PhD**

### Course Description:

**Competencies:**

Students who complete this course:

1) will know:

• what arguments are (and what they are not), what makes a valid argument and when a valid argument is also a sound one;

• the basic types of argument; the main logical fallacies;

• how to interpret and analyze numerical data expressed as real numbers, ratios, percentages, ratios as well as graphically represented;

• frequent errors in numerical reasoning.

2) will be able to:

• recognize arguments and analyzing them in terms of validity and soundness;

• draw logically valid conclusions from given premises;

• perform numerical calculations and evaluations and assessment of the obtained results in typical cases of empirical data analysis in psychology.

**Prerequisites:**

Students are required to have the following knowledge and/or skills:

• Proficiency in English at level B2

• High school background knowledge

**Types:**

Full-time Programmes

**Types of Courses:**

Lecture

**Language of teaching:**

English

### Topics:

- Introduction: Why psychologists need good reasoning skills. Examples. The aim and the structure of the course.
- Arguments. What arguments are and what they are not. Deductive and inductive arguments. Valid and sound arguments.
- Analysis of arguments (1).
- Analysis of arguments (2).
- Reasoning fallacies (1).
- Reasoning fallacies (2).
- Drawing conclusions from given premises.
- TEST 1
- Basic operations with numerical information and related frequent problems. Qualitative evaluation of numerical data.
- Presentation of numerical information - ratios, percentage, average. Comparison and inference.
- Understanding and analysis of plots, tables, and diagrams used in psychology research.
- Simpson's paradox. Implication for research in psychology.
- Probability and probability reasoning. Bayesian inference.
- Frequent errors in probability judgments and methods to avoid them.
- TEST 2

### Bibliography:

Baron, J. (2008). Thinking and Deciding. New York: Cambridge University Press.

Bowell, J., Kemp, G. (2002). Critical Thinking. A Concise Guide. London: Routledge.

Copi, I. M., Cohen, C., McMahon, K. (2014). Introduction to Logic, 14th edition. London: Pearson.

Cottrell, S. (2005). Critical Thinking Skills. New York: Palgrave Macmillan.

Kahneman, D. (2011). Thinking, fast and slow. Macmillan.

Novella, S. (2012). Your Deceptive Mind: A Scientific Guide to Critical Thinking Skills. Chantilly, Virginia: The Great Courses.

Smith, H. (2011). How to Pass Numerical Reasoning Tests: A Step-by-Step Guide to Learning Key Numeracy Skills (2nd ed). Philadelphia: Kogan Page Limited.

Weston, A. (2009). A Rulebook for Arguments, 4th edition. Cambridge, MA: Hackett.

### Assessment:

Test 1 (50%)

Test 2 (50%)