PPT-Numerical Data

Uses data and statistical measures for a v ariety of purposes Essential Question How can you summarize and display numerical data is the process of collecting organizing and interpreting data . et al et al et al brPage 2br i ii 2 GEOMETRY AND PARAMETERS Main Features Symbol Value brPage 3br 3 EXPERIMENTAL MEASUREMENTS pp pp brPage 4br RR F Fr Fr Fr Fr 4 NUMERICAL RESULTS brPage 5br Fr Fr 5 CONCLUSIONS Fr ACKNOWLEDGEMENTS REFERENCES brPage Summarizing the Sample. WARNING: Today’s lecture may bore some of you…. It’s . (sort of) not . my fault…I’m required to teach you about what we’re going to cover today.. I’ll try to make it as exciting as possible…. 2 Abstract The numerical knowledge of children from low-income backgrounds trails behind that of peers from middle-income backgrounds even before the children enter school. This gap may reflect differ Pietro Ferrara. Chair of Programming . Methodology. ETH Zürich. pietro.ferrara@gmail.com. Who I am. Former student @ . Ca. ’ . Foscari. Bachelor: July 2003. Master: February 2005. PhD student @. Ecole. ES 84 Numerical Methods for Engineers, Mindanao State University- . Iligan. Institute of Technology. Prof. . Gevelyn. B. . Itao. Techniques by which mathematical problems are formulated so that they can be solved with arithmetic operations {+,-,*,/} that can then be performed by a computer. . Unit-3. Linear . Algebric. Equation. 2140706 – Numerical & Statistical Methods. Matrix Equation. The matrix notation for following linear system of equation is as follow:. . . The above linear system is expressed in the matrix form . Introduction. This chapter focuses on using some numerical methods to solve problems. We will look at finding the region where a root lies. We will learn what iteration is and how it solves equations. Unit-1. Computer Arithmetic. 2140706 . – Numerical & Statistical Methods. Errors. An error is defined as the . difference. between the . actual value . and the . approximate value . obtained from the experimental . Martyn. Clark. Short course on. “. Model building, inference and hypothesis testing in hydrology. ”. 21-25 May, 2012. Approach. Stick to very simple (yet robust) numerical methods. Simpler than those presented in “Numerical Recipes”. WARNING: Today’s lecture may bore some of you…. It’s . (sort of) not . my fault…I’m required to teach you about what we’re going to cover today.. I’ll try to make it as exciting as possible…. Distinguish between:. - A statistic and a parameter. - A categorical and a quantitative variable. - A response and an explanatory . variable. Identify:. - When a categorical variable is ordinal. - When a quantitative variable is continuous. Chapter 2 Topics. . Visualizing variation in numerical and categorical data. Summarizing important features in numerical and categorical distributions. Visualizing variation in numerical data. Section 2.1. Statistical Questions. Statistical Questions. : ones that can be answered by collecting and analyzing . data. (pieces of information, can be numerical or categorical). Ex’s:. (a) What is the height of each . NUMERICAL RESULTS . VS EXPERIMENTAL DATA. Tatiana . Dobroserdova. (INM RAS, Moscow, Russia. ) . A. . . Akulov. (Institute of Cytology and Genetics, SB RAS). A. . Cherevko. . (. Lavrentyev. Institute of Hydrodynamics SB RAS.