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Lecture 2: Descriptive Statistics and Exploratory Data ...

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Lecture 2: DescriptiveStatistics and ExploratoryData AnalysisFurther Thoughts on Experimental DesignPop 1Pop 2Repeat 2 times processing 16 samples in totalRepeat entire process producing 2 technicalreplicates for all 16 samplesRandomly sample 4 individuals from each popTissue culture and RNA extractionLabeling and array hybridizationSlide scanning and data acquisition 16 Individuals (8 each from two populations) with replicatesOther Business Course web-site: Homework due on Thursday not Tuesday Make sure you look at HW1 soon and seeeither Shameek or myself with questionsToday What is Descriptive Statistics and exploratorydata analysis? Basic numerical summaries of data Basic graphical summaries of data How to use R for calculating Descriptive statisticsand making graphsPopulationSampleInferential StatisticsDescriptiveStatisticsProbabili ty Central Dogma of StatisticsEDABefore making inferences from data it is essential toexamine all your listen to the data :- to catch mistakes- to see patterns in the data - to find violations of statistical assumptions- to generate because if you don t, you will have trouble laterTypes of DataCategoricalQuantitativeco

Multivariate Data •Organize units into clusters •Descriptive, not inferential •Many approaches •“Clusters” always produced Clustering Data Reduction Approaches (PCA) •Reduce n-dimensional dataset into much smaller number •Finds a new (smaller) set of variables that retains most of the information in the total sample

  Data, Multivariate, Multivariate data

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