Regression for categorical data /

"Categorical data play an important role in many statistical analyses. They appear whenever the outcomes of one or more categorical variables are observed. A categorical variable can be seen as a variable for which the possible values form a set of categories, which can be finite or, in the cas...

Πλήρης περιγραφή

Κύριος συγγραφέας: Tutz, Gerhard.
Μορφή: Βιβλίο
Γλώσσα: English
Στοιχεία έκδοσης: Cambridge ; New York : Cambridge University Press, 2012.
Σειρά: Cambridge series in statistical and probabilistic mathematics.
Ταξινομικός αριθμός: 519.5΄36 TUT
Θέματα:
Ετικέτες: Προσθήκη ετικέτας
Δεν υπάρχουν, Καταχωρήστε ετικέτα πρώτοι!
LEADER 02067cam a2200241 a 4500
001 1/44023
008 131106s2012 enka b 001 0 eng
020 |a 9781107009653 (hardback) 
035 |l 46957 
040 |a DLC  |c DLC  |d GR-PeUP 
082 0 0 |a 519.5΄36 TUT 
100 1 |a Tutz, Gerhard. 
245 1 0 |a Regression for categorical data /  |c Gerhard Tutz. 
260 |a Cambridge ;  |a New York :  |b Cambridge University Press,  |c 2012. 
300 |a x, 561 σ. :  |b εικ. ;  |c 26 εκ. 
490 1 |a Cambridge series on statistical and probabilistic mathematics ; 
504 |a Περιέχει βιβλιογραφία και ευρετήριο. 
520 |a "Categorical data play an important role in many statistical analyses. They appear whenever the outcomes of one or more categorical variables are observed. A categorical variable can be seen as a variable for which the possible values form a set of categories, which can be finite or, in the case of count data, infinite. These categories can be records of answers (yes/no) in a questionnaire, diagnoses like normal/abnormal resulting from a medical examination or choices of brands in consumer behaviour. Data of this type are common in all sciences that use quantitative research tools, for example social sciences, economics, biology, genetics and medicine, but also engineering and agriculture. In some applications all of the observed variables are categorical and the resulting data can be summarized in contingency tables which contain the counts for combinations of possible outcomes. In other applications categorical data are collected together with continuous variables and one wants to investigate the dependence of one or more categorical variables on continuous and/or categorical variables"-- 
650 4 |a Regression analysis. 
650 4 |a Categories (Mathematics) 
830 |a Cambridge series in statistical and probabilistic mathematics. 
852 |a INST  |b UNIPILB  |c MAIN  |e 20131106  |h 519.5΄36 TUT  |p 00169950  |q 00169950  |t STATIST  |y 0  |4 1 
856 4 |d /webopac/covers/03/46957_9781107009653.jpg  |z (hardback)