Statistics I
Informacje ogólne
Kod przedmiotu:  2500ENO21n  Kod Erasmus / ISCED:  14.4 / (0313) Psychologia 
Nazwa przedmiotu:  Statistics I  
Jednostka:  Wydział Psychologii  
Grupy: 
obligatory courses for 1 year 

Punkty ECTS i inne: 
8.00 zobacz reguły punktacji 

Język prowadzenia:  angielski  
Rodzaj przedmiotu:  obowiązkowe 

Skrócony opis: 
(tylko po angielsku) The aim of this course is to learn what kind of conclusions can be drawn from numerical data. The basics of statistics and statistical tests will be covered so that you will know how to make simple statistical analyses independently. This course will focus on two topics: One with general issues of statistical inference, and the other with specific statistical tests. The general topics refer to the basis of statistical inference, independent from the type of analysis you are performing, and is mainly theoretical. Understanding of these general issues gives you a better sense of what you are doing across a wide variety of statistical analyses. We will focus on this mainly in the beginning of the course. Later in the course we will look at specific statistical tests: When are they to be used, why, and how. 

Pełny opis: 
(tylko po angielsku) In this course you will learn about statistical methods and inference necessary to analyze data and test the relationships between variables. To get to this point you will need a basic understanding of the principles of statistical reasoning. These are not so much mathematical principles, but rather logical principles. As a consequence the emphasis in this course lies on the verbal understanding of this logic. You will also learn how to apply this knowledge in practice, in the form of different statistical tests. However, all these tests are expressions of the same underlying logic, applied in different situations. One of the main reasons to teach you all this is because it enables you to test your ideas, notions and theories. Any scientific theory has to be put to the test to see if its predictions are correct. An important part of this involves translating research questions into testable hypotheses which can be verified by applying the appropriate statistical techniques. Understanding of statistical inference makes it possible to make general conclusions about larger populations of people on the basis of research outcomes obtained from a relatively small number of tested participants. This course therefore helps you in forming a deeper understanding of the (empirical) scientific method, and complements knowledge of research methods. A major goal of this course is to prepare you to become an independent researcher of course. But you will benefit from having knowledge of statistics in other, more direct ways too. It will make it easier for you to read, understand and judge scientific writing for instance. Because of your increased skills in statistical reasoning it will become easier to avoid common cognitive biases and logical thinking errors, which greatly helps with drawing correct conclusions. You will be much better able to distinguish between common sense beliefs and scientific beliefs, which helps a lot with seeing the flaws in bogus or pseudo science and popscience often found in magazines. So this course in general also increases your critical thinking skills. Additional, forms of more professional skills you will acquire include an increased ability to communicate and explain research setups and findings, using numbers and graphs, and a better understanding of the construction, and use of psychological tests. 

Literatura: 
(tylko po angielsku) 1. Introduction / measures of center • Pages 116 of chapter 1 of Spatz, C. (2005). Basic statistics: Tales of distributions, 8th ed. Wadsworth, Belmont, CA. • Pages 1614 of chapter 2 of Howell, D. C. (2002). Statistical methods for Psychology, 5th ed. Duxbury, Pacific Grove, CA. 2. Measures of variability • Pages 5361 of chapter 3 of Spatz, C. (2005). Basic statistics: Tales of distributions, 8th ed. Wadsworth, Belmont, CA. 3. Z > standardizing scores & the normal distribution • Pages 7171 of chapter 4 of Spatz, C. (2005). Basic statistics: Tales of distributions, 8th ed. Wadsworth, Belmont, CA. • Chapter 6 of Spatz, C. (2005). Basic statistics: Tales of distributions, 8th ed. Wadsworth, Belmont, CA. 4. Sampling, sampling distribution and probability • Pages 142156 from chapter 7 of Spatz, C. (2005). Basic statistics: Tales of distributions, 8th ed. Wadsworth, Belmont, CA. 5. Confidence intervals • Pages 434442 of chapter 6 of Moore, D. D., McCabe, G. P., & Craig, B. (2014). Introduction to the Practice of Statistics, 8th ed. W. H. Freeman, NY. 6. Effect size and the tdistribution • Sullivan, G. M., & Feinn, R. (2012). Using effect sizeor why the P value is not enough. Journal of graduate medical education, 4(3), 279282. • Remainder of chapter 8 of Spatz, C. (2005). Basic statistics: Tales of distributions, 8th ed. Wadsworth, Belmont, CA. 7. Testing a hypothesis • Pages 453468, 476481 of chapter 6 from Moore, D. D., McCabe, G. P., & Craig, B. (2014). Introduction to the Practice of Statistics, 8th ed. W. H. Freeman, New York, NY. 8. Significance, Type I & II errors, and power • Pages 168172, 176181 of chapter 8 of Spatz, C. (2005). Basic statistics: Tales of distributions, 8th ed. Wadsworth, Belmont, CA. 9. Twosample ttests • Pages 324336 of chapter 9 of Field, A. (2013). Discovering statistics using IBM SPSS statistics. Sage. 10. ANOVA • Chapter 10 of Spatz, C. (2005). Basic statistics: Tales of distributions, 8th ed. Wadsworth, Belmont, CA. 11. Factorial ANOVA • Chapter 12 of Spatz, C. (2005). Basic statistics: Tales of distributions, 8th ed. Wadsworth, Belmont, CA. 12. Correlation • Pages 85107 of chapter 5 of Spatz, C. (2005). Basic statistics: Tales of distributions, 8th ed. Wadsworth, Belmont, CA. • Pages 248254 of chapter 9 of Howell, D. C. (2002). Statistical methods for Psychology, 5th ed. Duxbury, Pacific Grove, CA. • Pages 166179 of chapter 6 of Field, A. (2013). Discovering statistics using IBM SPSS statistics. Sage. 13. Regression • Pages 108115 of chapter 5 of Spatz, C. (2005). Basic statistics: Tales of distributions, 8th ed. Wadsworth, Belmont, CA. • Pages 197205 of chapter 7 of Field, A. (2013). Discovering statistics using IBM SPSS statistics. Sage 14. Chisquare • Chapter 13 of Spatz, C. (2005). Basic statistics: Tales of distributions, 8th ed. Wadsworth, Belmont, CA. 15. Nonparametric alternatives to parametric tests • Chapter 14 of Spatz, C. (2005). Basic statistics: Tales of distributions, 8th ed. Wadsworth, Belmont, CA. 

Efekty uczenia się: 
(tylko po angielsku)  Knowledge how to use different statistical methods to describe, investigate and test relationships between variables  The ability to solve research questions by translating them into testable hypotheses, applying the appropriate tests, and making the correct inferences to come to the most appropriate conclusions  Understanding of statistical inference  Understanding of the logic and reasoning underlying statistical principles, such as probability theory  Understanding of the use of statistical methods in the broader context of the empirical scientific methods 

Metody i kryteria oceniania: 
(tylko po angielsku) a) Fourteen short inclass tests, worth 2 points each. b) Midterm exam, 36 points. c) Final exam, 36 points. 97 or more = 5! 9296 = 5 8491 = 4.5 7683 = 4 6875 = 3.5 6067 = 3 below 60 = 2 (fail) Attendance is obligatory for both lectures and exercise classes. No more than 2 of each can be missed without valid excuse. For the exercises, missing more than 4 classes overall leads to course failure. For the lectures missing more than 50% leads to course failure. Students must respect the principles of academic integrity. Cheating and plagiarism (including copying work from other students, internet or other sources) are serious violations that are punishable and instructors are required to report all cases to the administration. This also applies to the exercises: do not copy solutions to exercises from a colleague. Students being caught copying work will be immediately excluded from the course (=fail) and referred to the University’s disciplinary commission. 
Zajęcia w cyklu "Semestr letni 2019/20" (zakończony)
Okres:  20200217  20200802 
zobacz plan zajęć 
Typ zajęć: 
Ćwiczenia, 30 godzin więcej informacji Wykład, 30 godzin więcej informacji 

Koordynatorzy:  (brak danych)  
Prowadzący grup:  Wouter De Raad  
Lista studentów:  (nie masz dostępu)  
Zaliczenie: 
Przedmiot 
Egzamin
Ćwiczenia  Brak protokołu Wykład  Zaliczenie na ocenę 
Właścicielem praw autorskich jest Uniwersytet Warszawski.