THE 2-POINT CORRELATION-FUNCTION AND MORPHOLOGICAL SEGREGATION IN THEOPTICAL REDSHIFT SURVEY

We study the clustering of galaxies in real and redshift space using t he Optical Redshift Survey (ORS). We estimate the two-point correlatio n function in redshift space, xi(s), for several subsamples of ORS, sp anning nearly a factor of 30 in volume. We detect significant variatio ns in xi(s) among the subsamples covering small volumes. For volumes < greater than or greater than or similar to(75h(-1)Mpc)(3), however the ORS subsamples present very similar clustering patterns. Fits of the form xi(s)=(s/s(0))- give best-fitting values in the range 1.5 less th an or equal to y(s) less than or equal to 1.7 and 6.5 less than or equ al to s(0) 8.8 h(-1) Mpc for several samples extending to redshifts of 8000 km S-1. However, in several cases xi(s) is not well described by a single power-law, rendering the best-fitting values quite sensitive to the interval in s adopted. We find significant differences in clus tering between the diameter-limited and magnitude-limited ORS samples within a radius of 4000 km s(-1) centred on the Local Group; xi(s) is larger for the magnitude-limited sample than for the diameter-limited one, We interpret this as an indirect result of the morphological segr egation coupled with differences in morphological mix, We split ORS in to different morphological subsamples and confirm the existence of mor phological segregation of galaxies out to scales of s similar to 10 h( -1) Mpc, Our results indicate that the relative bias factor between ea rly- and late-type galaxies may be weakly dependent on scale, If real, this would suggest non-linear biasing. We also compute correlations a s a function of radial and projected separations, xi(r(p), pi), from w hich we derive the real-space correlation function, xi(r). We obtain v alues 4.9 less than or equal to r(0) 7.3 h(-1) Mpc and 1.5 less than o r equal to y(r) less than or equal to 1.7 for various ORS samples. As before, these values depend strongly on the range in r adopted for the fit. The results obtained in real space confirm those found using xi( s),i.e in small volumes magnitude-limited samples show larger clusteri ng than do diameter-limited ones. There is no difference when large vo lumes are considered. Our results prove to be robust to adoption of di fferent estimators of xi(s) and to alternative methods of compensating for sampling selection effects.