000 02427cam a2200349 i 4500
001 21402866
003 OSt
005 20221107113022.0
008 200127s2021 caua b 000 0 eng
010 _a 2019046882
020 _a1071807491
040 _aDLC
_beng
_cDLC
_erda
_dDLC
042 _apcc
050 0 0 _aHA31.35
_b.W37 2021
100 1 _aWarner, Rebecca M.,
245 1 0 _aApplied statistics I :
_bbasic bivariate techniques /
_cRebecca M. Warner
250 _a3rd ed.
264 1 _aLos Angeles :
_bSAGE Publications, Inc,
_c2021
300 _axxiii, 623 p :
_bill;
336 _atext
_btxt
_2rdacontent
337 _aunmediated
_bn
_2rdamedia
338 _avolume
_bnc
_2rdacarrier
500 _aRevised edition of the author's Applied statistics, c2013.
504 _aIncludes bibliographical references.
520 _a"Applied Statistics I: Basic Bivariate Techniques has been created from the first half of Rebecca M. Warner's popular Applied Statistics: From Bivariate Through Multivariate Techniques. The author's contemporary approach differs from some of the well-worn texts in the market, and reflects current thinking in the field. It spends less time on statistical significance testing, and moves in the direction of the "new statistics" by focusing more on confidence intervals and effect size. Instructors of upper undergraduate or beginning graduate level courses will find that the greater focus on basic concepts such as partition of variance and effect size is more useful to students, particularly as preparation for more advanced courses. Spending less time on statistical significance testing allows for more time to be devoted to more interesting and useful statistics that students will see in journal articles (such as correlation and regression). This introductory statistics text includes examples in SPSS, together with datasets on an accompanying website. A companion study guide reproducing the exercises and examples in R will also be available"--
_cProvided by publisher.
650 0 _aSocial sciences
_xStatistical methods.
650 0 _aPsychology
_xStatistical methods.
650 0 _aMultivariate analysis.
906 _a7
_bcbc
_corignew
_d1
_eecip
_f20
_gy-gencatlg
942 _2lcc
_cBK
999 _c19780
_d19779