LEADER 03850nam 22007455 450 001 9910299963003321 005 20250505002904.0 010 $a1-4614-9602-0 024 7 $a10.1007/978-1-4614-9602-1 035 $a(CKB)3710000000092561 035 $a(EBL)1781994 035 $a(SSID)ssj0001186984 035 $a(PQKBManifestationID)11651473 035 $a(PQKBTitleCode)TC0001186984 035 $a(PQKBWorkID)11243174 035 $a(PQKB)11214211 035 $a(MiAaPQ)EBC1781994 035 $a(DE-He213)978-1-4614-9602-1 035 $a(PPN)177825081 035 $a(EXLCZ)993710000000092561 100 $a20140303d2014 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aAnalysis of Neural Data /$fby Robert E. Kass, Uri T. Eden, Emery N. Brown 205 $a1st ed. 2014. 210 1$aNew York, NY :$cSpringer New York :$cImprint: Springer,$d2014. 215 $a1 online resource (663 p.) 225 1 $aSpringer Series in Statistics,$x2197-568X 300 $aDescription based upon print version of record. 311 08$a1-322-13255-0 311 08$a1-4614-9601-2 320 $aIncludes bibliographical references at the end of each chapters and indexes. 327 $aIntroduction -- Exploring Data -- Probability and Random Variables -- Random Vectors -- Important Probability Distributions -- Sequences of Random Variables -- Estimation and Uncertainty -- Estimation in Theory and Practice -- Uncertainty and the Bootstrap -- Statistical Significance -- General Methods for Testing Hypotheses -- Linear Regression -- Analysis of Variance -- Generalized Regression -- Nonparametric Regression -- Bayesian Methods -- Multivariate Analysis -- Time Series -- Point Processes -- Appendix: Mathematical Background -- Example Index -- Index -- Bibliography. 330 $aContinual improvements in data collection and processing have had a huge impact on brain research, producing data sets that are often large and complicated. By emphasizing a few fundamental principles, and a handful of ubiquitous techniques, Analysis of Neural Data provides a unified treatment of analytical methods that have become essential for contemporary researchers. Throughout the book ideas are illustrated with more than 100 examples drawn from the literature, ranging from electrophysiology, to neuroimaging, to behavior. By demonstrating the commonality among various statistical approaches the authors provide the crucial tools for gaining knowledge from diverse types of data. Aimed at experimentalists with only high-school level mathematics, as well as computationally-oriented neuroscientists who have limited familiarity with statistics, Analysis of Neural Data serves as both a self-contained introduction and a reference work. 410 0$aSpringer Series in Statistics,$x2197-568X 606 $aBiometry 606 $aNeurosciences 606 $aNeuropsychology 606 $aStatistics 606 $aBiostatistics 606 $aNeuroscience 606 $aNeuropsychology 606 $aStatistical Theory and Methods 615 0$aBiometry. 615 0$aNeurosciences. 615 0$aNeuropsychology. 615 0$aStatistics. 615 14$aBiostatistics. 615 24$aNeuroscience. 615 24$aNeuropsychology. 615 24$aStatistical Theory and Methods. 676 $a612.8 700 $aKass$b Robert E.$4aut$4http://id.loc.gov/vocabulary/relators/aut$0423354 702 $aEden$b Uri T.$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aBrown$b E. N$g(Emery N.),$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910299963003321 996 $aAnalysis of Neural Data$92528825 997 $aUNINA