LEADER 04208nam 22007215 450 001 9910299963003321 005 20220324204032.0 010 $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$b[electronic resource] /$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 $aSpringer Series in Statistics,$x0172-7397 300 $aDescription based upon print version of record. 311 $a1-322-13255-0 311 $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,$x0172-7397 606 $aStatistics  606 $aNeurosciences 606 $aNeuropsychology 606 $aStatistics for Life Sciences, Medicine, Health Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/S17030 606 $aNeurosciences$3https://scigraph.springernature.com/ontologies/product-market-codes/B18006 606 $aNeuropsychology$3https://scigraph.springernature.com/ontologies/product-market-codes/Y12030 606 $aStatistical Theory and Methods$3https://scigraph.springernature.com/ontologies/product-market-codes/S11001 615 0$aStatistics . 615 0$aNeurosciences. 615 0$aNeuropsychology. 615 14$aStatistics for Life Sciences, Medicine, Health Sciences. 615 24$aNeurosciences. 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 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