PPT-Xuhua Xia Slide 1 Multivariate statistics

PCA principal component analysis Correspondence analysis Canonical correlation Discriminant function analysis Cluster analysis MANOVA PCA Given a set of variables x 1 x 2 x. Fitting Several Regression Lines. Many applications of statistical analysis involves a continuous variable as dependent variable (DV) but both continuous and categorical variables as independent variables (IV). . Gerry Quinn. Deakin University. Data sets in community ecology. Multivariate abundance data. Sampling or experimental units. p. lots, cores, panels, quadrats ……. u. sually in hierarchical spatial or temporal structure. Slide . 1. Correlation. Simple correlation. between two variables. Multiple and Partial correlations. between one variable and a set of other variables. Canonical Correlation. between two sets of variables each containing more than one variable.. and decoding. Kay H. Brodersen. Computational Neuroeconomics Group. Institute of Empirical Research in Economics. University of Zurich. Machine Learning and Pattern Recognition Group. Department of Computer Science. models for fMRI . data. Klaas Enno Stephan. (with 90% of slides kindly contributed by . Kay H. Brodersen. ). Translational . Neuromodeling. Unit (TNU). Institute for Biomedical Engineering. University . Stepwise Regression. Y may depend on many independent variables. How to find a subset of X’s that best predict Y?. There are several criteria (e.g., adjusted R. 2. , AIC, BIC, likelihood ratio test, etc.) for model selection and many algorithms for including or excluding X’s in the model: forward selection, backward elimination, stepwise regression, etc.. Xuhua Xia. xxia@uottawa.ca. http://dambe.bio.uottawa.ca. Xuhua Xia. Slide . 2. Lecture Outline. Objectives in this lecture. Grasp the basic concepts distance-based tree-building algorithms. Learn the least-squares criterion and the minimum evolution criterion and how to use them to construct a tree. Stevan. J. Arnold. Department of Integrative Biology. Oregon State University. Thesis. The statistical approach that we used for a single trait can be extended to multiple traits.. The key statistical parameter that emerges is the G-matrix.. Many applications of statistical analysis involves a continuous variable as dependent variable (DV) but both continuous and categorical variables as independent variables (IV). . Relationship between DV and continuous IVs is linear and the slope remains the same in different groups: ANCOVA.. 1/09 今天的学习目标 ( Today’s Learning Objectives ) I can speak, read and understand Lesson 18 Dialogue 1. I can understand the Section I Listening Comprehension No. 1-5 on the Chinese Writing Assessment Handouts. EstimationofDimensionReductionSpacethat,foranyconstantvector;:::;b,thereareconstants;:::;cdependingonsuchthat,forthedirectionsinmodel(1.1),AspointedoutbyCookandWeisbergintheirdiscussionofLi(1991),them http://dambe.bio.uottawa.ca. Slide . 2. Causes of genomic evolution. Variation in genome size and gene content. sequence duplication (genome, segmental, gene). horizontal gene transfer. transposition (Barbara McClintock). xxia@uottawa.ca. http://dambe.bio.uottawa.ca. Definitions. Genome: the . entire complement of genetic material carried by an individual. Transcriptome with two definitions:. the . entire set of . transcribable sequences from the genome (operationally all RNA sequences from annotated productive genes in a genome). Previous work [1] studied the use of PTP and Synchronous Ethernet (. SyncE. ) for synchronization of detector data from multiple Pixie-Net modules, an earlier and smaller version of the digitizing and pulse processing electronics described here. The time resolution for coincident events reached ~10ns FWHM with PTP synchronization and 200-800ps FWHM with .