Február - 2019
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Tantárgy adatlap

Statistics II.

Tantárgy adatlap letöltése: Letöltés

A tantárgy kódja: 4ST14NAK28B
A tantárgy megnevezése (magyarul): Statistics II.
A tantárgy neve (angolul): Statistics II.
A tanóra száma (Előadás + szeminárium + gyakorlat + egyéb): 14 lectures + 14 seminars
Kreditérték: 6
A tantárgy meghirdetésének gyakorisága: once every fall semester
Az oktatás nyelve: English
Előtanulmányi kötelezettségek: Statistics I.
A tantárgy típusa: core
Tantárgyfelelős tanszék: Statisztika Tanszék
A tantárgyfelelős neve: Szemerédi Katalin Ágnes

A tantárgy szakmai tartalma: The course presents the core concepts and tools of statistical inference. The primary objective is to learn how to make, based on a finite sample, statistically valid statements on the distribution of and the relationship among multiple variables characterizing some population of interest. Statistical software (SPSS) will be used for performing various types of data analyses.

Évközi tanulmányi követelmények: Regular attendance of lectures and seminars is strongly recommended.

Vizsgakövetelmény: final exam for 50 points

Az értékelés módszere: End-term grade is based on the total score obtained on (1) the final exam, and either (2/a) two mid-term computer exams; or (2/b) a research paper which is optional and can be substituted for the two computer exams.

Tananyag leírása: The course, covering the main topics of statistical inference, is composed of five parts. Part 1 provides a brief overview of statistical sampling and introduces the concept and the basic properties of sampling distributions. Part 2 presents in detail the techniques of interval estimation for various unknown population parameters (means, proportions and variances). Part 3 presents the theory of hypothesis testing in general, as well as a number of standard statistical procedures for testing hypotheses about the values of and the relation between unknown population characteristics. Part 4 presents two particular types of statistical procedures (chi-square tests, ANOVA and its non-parametric equivalents), designed to test a wider scope of hypotheses about the population distribution of one or more variables of interest. Part 5 gives a detailed treatment of multiple regression models, including topics such as how to incorporate qualitative information to the model, how to model interaction effects and curvilinear relationships, and how to test for a significant relationship between the variable of interest and one or more explanatory variables.

Órarendi beosztás: 

Kompetencia leírása: By the end of the course, students will have gained competence in providing interval estimates for unknown population parameters; testing hypotheses about population characteristics; analyzing and testing the statistical relationship among multiple variables; building regression models and using them for predicting the variable(s) of interest.

Félévközi ellenőrzések: 2 mid-term computer exams for 25 points each

A hallgató egyéni munkával megoldandó feladatai: empirical research paper for 50 points (optional, substituting the two computer exams)

Szak neve: Applied Economics

Kötelező irodalom:

  • Detailed lecture notes will be provided on-line.

Ajánlott irodalom:

  • IBM SPSS Statistics 22 Brief Guide
  • IBM SPSS Statistics Base 22
Ajánlott irodalmak:
Kötelező irodalmak:

A tantárgy oktatói:

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