Szeptember - 2018
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Tantárgy adatlap

Multivariate Data Analysis

Tantárgy adatlap letöltése: Letöltés

A tantárgy kódja: PCXXNOKC02M
A tantárgy megnevezése (magyarul): Multivariate Data Analysis
A tantárgy neve (angolul): Multivariate Data Analysis
A tanóra száma (Előadás + szeminárium + gyakorlat + egyéb): 2*90 minutes weekly (lecture+seminar)
Kreditérték: 6
A tantárgy meghirdetésének gyakorisága: Spring semester
Az oktatás nyelve: English
Előtanulmányi kötelezettségek: Probability Theory, Statistics
A tantárgy típusa: Elective
Tantárgyfelelős tanszék: Operációkutatás és Aktuáriustudományok Tanszék
A tantárgyfelelős neve: Dr. Szüle Borbála

A tantárgy szakmai tartalma: This course will present statistical techniques that can be used to test the impact of social, political and economical decisions and to turn numbers into information. In treating the various statistical procedures, equal attention will be paid to their statistical background and the computational details. The course will build confidence to treat numbers and analyze data to use the techniques covered by statistical computer packages. This course of statistics combines an overview of hypothesis testing and regression with an opportunity to practice, including the use of SPSS statistical software and the interpretation of results obtained from real data.

Évközi tanulmányi követelmények: In case of "offered grade": individual homework analysis (based on own data collection), project work analysis (written in groups consisting of maximum 3 students), test and literature review.
Otherwise: an individual homework analysis that should be based on own data collection.

Vizsgakövetelmény: In case of "offered grade": the grade will be based on the results of the individual homework analysis and the project work analysis. Each of these will contribute 50-50 % to the grade, if the result of the test (before the exam period) is at least 50% and the quality of the literature review is adequate. Students can indicate until a given deadline whether the "offered grade" is accepted, without the indication about the acceptance of the offered grade (until the given deadline) the grade can only be achieved with the writing of the final exam (and the individual homework analysis, each of these contributing 50-50% to the grade).
Otherwise: the grade will be based on the results of the individual homework analysis and the final exam. Each of these will contribute 50-50 % to the grade.
The individual homework analysis should be based on own data collection.
The project work analysis should be related to selected research questions (that are analyzed with data analysis methods discussed during classes). The project work analysis should be written with a proportionate work distribution among the students (it is also necessary to hand in a report that describes the details of the work distribution).
The students may write a test before the exam period.
The literature review (2-3 pages) can not be handed in during the exam period.
The final exam (written in the exam period) contains questions related to the theoretical background of multivariate statistical methods and questions that should be solved with statistical computer program.

Az értékelés módszere: In case of "offered grade": the grade will be based on the results of the individual homework analysis and the project work analysis. Each of these will contribute 50-50 % to the grade, if the result of the test (before the exam period) is at least 50% and the quality of the literature review is adequate. Students can indicate until a given deadline whether the "offered grade" is accepted, without the indication about the acceptance of the offered grade (until the given deadline) the grade can only be achieved with the writing of the final exam (and the individual homework analysis, each of these contributing 50-50% to the grade).
Otherwise: the grade will be based on the results of the individual homework analysis and the final exam. Each of these will contribute 50-50 % to the grade.
The individual homework analysis should be based on own data collection.
The project work analysis should be related to selected research questions (that are analyzed with data analysis methods discussed during classes). The project work analysis should be written with a proportionate work distribution among the students (it is also necessary to hand in a report that describes the details of the work distribution).
The students may write a test before the exam period.
The literature review (2-3 pages) can not be handed in during the exam period.
The final exam (written in the exam period) contains questions related to the theoretical background of multivariate statistical methods and questions that should be solved with statistical computer program.

Tananyag leírása: - Data analysis, review of basic terms, Explorative Statistics
(Qualitative and quantitative Data, Frequency distributions, Stem and Leaf displays, Descriptive statistics: Measures of central tendency: mean, median, mode, Measures of variability: range, variance, standard deviation, Box plot for detecting outliers, Scales of measurements, Shape of a distribution, Normal distribution, Skewness, Kurtosis)
- The MEANS Procedure
(Inferences about the population mean and about the difference between two means, Rejection region and acceptance region of a hypothesis, One-Sample t-Test for the mean, t-Test for the difference between two means, Paired t-Test, Pooled variance, Empirical significance level)
- Simple linear regression and correlation
(Covariance and correlation coefficients, Covariance matrix, correlation matrix, Estimation of regression model, Ordinary least squares, Slope and intercept, ANOVA Table, F-test of the model, Plots, Interpretation of the results)
- Multivariate regression
(Residuals, Testing the Hypothesis that some coefficients are zero, Model building, Multicollinearity, Stepwise regression, Outliers, Qualitative variables, Dummy variables, Non-linear models, Goodness-of-fit tests in multivariate regression)
- Aggregating Variables
(The principal component approach, Principal Component Analysis, The eigenvalue problem, Generalization to r principal component, Communality or variance explained)
- The exploratory factor analysis model
(Estimation of the factor model using principal components, Determination of the number of factors, Factor structure matrix, Factor rotation, Varimax method, Factor scores)
- Cluster analysis
(Hierarchical and non-hierarchical clustering. Methods of aggregation. Interpretation of dendrograms. Interpretation of characteristics of clusters.)
- Discriminant Analysis
(Predicting Group Membership, Assumptions Underlying Discriminant Analysis, Coefficients for the Discriminant Functions)

Órarendi beosztás: According to the NEPTUN information

Kompetencia leírása: This course will present statistical techniques that can be used to test the impact of social, political and economical decisions and to turn numbers into information.

Félévközi ellenőrzések: deadline for individual homework analysis: 8th April, 2018.
deadline for project work analysis: 29th April, 2018.
deadline for literature review: 6th May, 2018.

A hallgató egyéni munkával megoldandó feladatai: individual homework analysis, and it is possible to write the project work analysis individually (and the test and the literature review should also be written individually, if the student writes the test and the literature review)

Szak neve: 

Irodalomjegyzék:
Kötelező irodalom:

  • Reading materials: Darren George – Paul Mallery: SPSS for Windows Step by Step, 8th Edition, Pearson, 2008

Ajánlott irodalom:

Ajánlott irodalmak:
Kötelező irodalmak:
Darren George - Paul Mallery: SPSS for Windows Step by Step, 8th Edition, Pearson, 2008
Megtalálható a Központi Könyvtárban

 
A tantárgy oktatói:

Utolsó módosítás: 2018-02-03 11:45:19

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