

Articles
by
Siddik Keskin 
Total Records (
5 ) for
Siddik Keskin 





Galip Bakir
,
Siddik Keskin
and
Hamit Mirtagioglu


Milk yield is important in breeding studies because it is one of the economically important traits. Therefore, determining the relationship between milk yield and some other traits could provide some important easiness in animal breeding studies. In this study, the aim was to evaluate the relationship between mature age milk yield and 9 independent variables (cow age, first mating age, lactation order, lactation period, dry period, first calving age, calving season, birth type and sex of calf) using CHAID analysis. Seven hundred and seventy Brown Swiss animals’ records (from 19871997) taken from Mus State Production Farm (in Turkey) were utilized. CHAID analysis results showed that lactation period was primary, sex of calf and cow age were secondary and first mating age and dry period were the tertiary variables affecting mature age milk yield. 




Siddik Keskin
,
Askin Kor
,
Serhat Karaca
and
Hamit Mirtagio lu


The aim of this study was to determine relationships between some udder traits [Undder Bottom Height (UBH), Udder Depth (UD), Udder Circumference (UC), Left Teat Circumference (LTC), Right Teat Circumference (RTC) and Teat Angle (TA)] and Daily Milk Yields (DMY) of Akke?i goats. For this purpose, data were collected from 30 goats. Correlations and path analysis were executed for identify the significant contribution of the udder traits on daily milk yields. As a result, this study indicated that these traits especialy, udder circumference and udder bottom height could be used as selection criterias for milk yields in Akke?i goats. 





Ecevit Eyduran
,
Taner Ozdemir
,
M. Kazim Kara
,
Siddik Keskin
and
Bahattin Cak


The objective of this study was to examined ChiSquare and G test statistics in place of enough sample size, contingency coefficient and power of test for different four contingency tables (data set) regarding biology sciences. Besides, this study was to determine whether sample sizes of various four samples in biology sciences were sufficient. The reliability of two statistics related to Sample size, contingency coefficient and power of test. Power analysis for ChiSquare and G test statistics were performed using a special SAS macro According to results of power analysis, sample sizes of other sets of data except the third data set were determined to be sufficient because power values for both statistics were more than 88%. With respect to power analysis, G statistics for the initial two data sets were more advantageous than other as power value of G statistics were larger than that of other. In the last data set, as sample size were 1607 and power values for both statistics were 100%, both were asymptotically equivalent each other. As power values of the third data set for ChiSquare and G test statistics were approximately 46.77 and 58.16%, respectively, sample size with 20 for both were determined to be insufficient. When we artificially increased 30 to 200 by 10, sufficient sample size for third data should be 50 so as to provide power values of 80% with respect to results of SAS special macro. As a result, this study emphasized that researchers should have taken into sample sizes and power of test account except for probability of Type Error I in contingency tables in order to determine the best one of both statistics. 




Taner Ozdemir
,
Siddik Keskin
and
Bahattin Cak


The goal of this study was relatively analyzed as to power in ChiSquare and Likelihood Ratio ChiSquare Statistics by using SAS special macro which is presented in Appendix. For the aim, data sets regarding questionnaire responses of 107 refugees were utilized. Contrary to other data sets (had power values with highlevel), sample size for only data set 3 having power values with lowmoderate level for both statistics were artificially increased from backward to forward and optimum samples sizes for ChSquare and other were determined as 280 and 170, respectively. As a result, it was concluded that power of ChiSquare and Likelihood Ratio ChiSquare Statistics changed to some factors: the size of sample and combinations of all cells` frequencies of contingency table. Besides, it is possible that researchers can determine sample size which is suitable for each data set by means of special SAS macro in appendix. Moreover, ones should not forget that power concept in any statistic technique means reliability. 




Hakan Ulukan
,
Mustafa Guler
and
Siddik Keskin


The present study was carried out to investigate a path coefficient with one faba bean cultivar i.e. Filiz 99 and two advanced breeding lines i.e. H_{1}=PN 55 K.No 584066 Reine Blance and H_{2}=PN 54 K.No 7954 x 96492B. Relationships between yield and yield components were determined by using a correlation and a pathcoefficient analysis in 19992000. In the investigated characters positive and significant relationships were found statistically between grain number pod^{1}and pod number plant^{1}; between biological yield and plant height; between biological yield and grain number pod^{1}. Direct and indirect effects of plant height, pod length, first pod height and pod number
plant^{1} and grain number pod^{1} upon biological yield were calculated. The total determination coefficient was found as 0.636 (63.6%) in the model which we used. 





