PPT-Outliers

The Story of Success By Malcolm Gladwell What is an Outlier outli er n 1 something that is situated away from or classed differently from a main or related body 2 a statistical observation that is markedly different in value from the others of the sample . regression models, the outliers can affect the estimated correlation coefficient [10]. Presence of outliers in training and testing data can bring about several difficulties for methods of decision- k. -center clustering. Ilya Razenshteyn (MIT). Silvio . Lattanzi. (Google), Stefano . Leonardi. (. Sapienza. University of Rome) and . Vahab. . Mirrokni. (Google). k. -Center clustering. Given:. 21. , 1, 1, 0, 3, 1, 2, 2. Which measure of central tendency will best convey how often the students typically eat out?. Possible Answers: Mean, Median, or Mode. The Scenario. Mean. : The arithmetic average. Add up all of the values and divide by the number of scores.. OUTLIER FORMULAS. BOX PLOTS. HISTOGRAMS. DESCRIBING A DISTRIBUTION (C.U.S.S.). STANDARD DEVIATION AND VARIANCE. Create a Box Plot of this data.. We need the 5# summary, which consists of the min,Q1,Med,Q3, max. Data Analysis & Computers II. Slide . 1. Detecting Outliers. Detecting univariate outliers. Detecting multivariate outliers. SW388R7. Data Analysis & Computers II. Slide . 2. Outliers. Outliers are cases that have data values that are very different from the data values for the majority of cases in the data set.. Identifying Outliers: More about this interpolation stuff..... Whenever the depth of a median or a fourth is a decimal (??.5), then you must interpolate. That is, you must find thevalue of the Jobs using . Mantri. Ganesh Ananthanarayanan. †. , Srikanth Kandula*, Albert Greenberg*, Ion Stoica. †. , Yi Lu*, Bikas Saha*, Ed Harris*. . †. UC Berkeley * . Microsoft. 1. MapReduce Jobs. Jimmy Johansson, Patric Ljung, Mikael Jern, Matthew Cooper . NVIS- Norrkoping Visualization and Interaction Studio, Linkoping University, Sweden . Presented by . Xinyu. . Chang. Kent State University. Validating and Preparing your data. Lyytinen & Gaskin . Data Screening. Data screening . (also known for us as “data screaming”) ensures . your data is . “clean” . and ready to go before you conduct . Claim & Purpose. Prologue & Chapter 1 - 2. ~ Claim ~. People . are considered successful when they . express . particular traits and characteristics: . diligence. , . self-sacrifice. , . intelligence. The Practice of Statistics in the Life Sciences. Third Edition. © . 2014 . W.H. Freeman and Company. Objectives (PSLS . Chapter . 2). Describing distributions with numbers. Measure of center: mean and median. Olivier . Dupriez. World Bank, Development Data Group. odupriez@worldbank.org. 6 June 2013. Initial objective. Calculate poverty PPPs. Had price data at basic heading level from the ICP ; needed consumption shares “at the poverty line” for the same breakdown to be used as weights.. Jobs using . Mantri. Ganesh Ananthanarayanan. †. , Srikanth Kandula*, Albert Greenberg*, Ion Stoica. †. , Yi Lu*, Bikas Saha*, Ed Harris*. . †. UC Berkeley * . Microsoft. 1. MapReduce Jobs. Section 1.2. Displaying Quantitative Data with Graphs. After this section, you should be able to…. CONSTRUCT and INTERPRET dotplots, stemplots, and histograms. DESCRIBE the shape of a distribution.