C 000 C ~A~B~C Today s outline. QCA and Fuzzy Sets Research Applications and Software Tools. Repitition I: Venn diagram.
|
|
|
- Sybil Cox
- 6 years ago
- Views:
Transcription
1 Institut für Politikwissenschaft Schwerpunkt qualitative empirische Sozialforschung Jonas uche Goethe-Universität Frankfurt Fachbereich 03 Q and Fuzzy Sets Research pplications and Software Tools Data alibration in fsq 15 May 2013 Today s outline Repetition (Venn diagram, calibration in csq) Get to know fsq 2.5? Rules on fuzzy set calibration Fuzzy set calibration in fsq 2.5 Set Relations in fsq 2.5 Task for the next week / Outlook alibration in fsq 2 Repitition I Work sheet on Venn diagrams alibration in fsq alibration in fsq ~~ ~ ~~ ~ ~ alibration in fsq 5 ~~ ~~~ alibrationin fsq 6 1
2 Repitition II: calibration with Tosmana omputer exercise Open FreitagSchlicht2009raw.csv alibrate outcome with Tosmanas thresholds setter alibrate outcome with qualitative anchor from the text alibration in fsq alibration in fsq 8 Repitition II: calibration with Tosmana FSQ alibration in fsq 9 fsq 2.5 dvantages csq and fsq (and even tq) Scatterplots for fuzzy set relations (Parameters of fit) Installation Disadvantages Only operates on Windows No Venn diagrams for csq (No case identification in truth tables) alibration in fsq alibration in fsq 12 2
3 Data matrix Data matrix reate/open data matrix Descriptive statistics alibration in fsq alibration in fsq 14 (Fuzzy) set calibration SET LIRTION alibration in fsq 15 5 steps of calibration areful definition of the relevant population of cases Precise definition of the meaning of all concept Decision on the point of maximum indifference about membership/non-membership (cs: threshold, fs: 0.5-anchor) Definition of full membership (1) and non-membership (0) For fsq: decision on graded memberships To repeat alibration criteria external to data ased on theoretical/ conceptual knowledge ased on case knowledge alibration in fsq 16 Fuzzy set calibration Freitag/Schlicht Ways for fuzzy set calibration Qualitative calibration Direct calibration Indirect calibration Most important are qualitative anchors Decision on the point of maximum indifference about membership/non-membership (cs: threshold, fs: 0.5-anchor) What is the text all about (outcome, conditions) Discipline? Level of nalysis? Number/selection of cases? Number/selection of conditions? ppropriate Q terminology? alibration in fsq alibration in fsq 18 3
4 alibration in fsq alibration in fsq 20 Qualitative anchors in Freitag/Schlicht alibration in fsq alibration in fsq 22 Qualitative anchors in Freitag/Schlicht 2009 alibration in fsq 2.5 (Freitag/Schlicht 2009) How to do this with the software? 1 0,67 0, alibration in fsq alibration in fsq 24 4
5 General calibration in fsq 2.5 Direct calibration [Variables] [ompute] Define Target Variable, i.e. nameofthenewset hoose[calibrate (x,n1,n2,n3)] from the list of [Functions] X = name of condition with raw data n1 = 1-anchor n2= 0.5 anchor n3= 0-anchor lick [Ok] N: interval scaled conditions! alibration in fsq alibration in fsq 26 Qualitative anchors in Freitag/Schlicht alibration in fsq alibration in fsq 28 Set operations in fsq 2.5 llen/ldred 2011 Intersection [Variables] [ompute] Define Target Variable, i.e. nameofthenewset hoose[fuzzyand(x 1,x 2,x n )] from the list of [Functions] X 1 = name of condition 1 with fuzzy data X 2 = name of condition 2 with fuzzy data X n = name of condition n with fuzzy data lick [Ok] What is the text all about (outcome, conditions) Discipline? Level of nalysis? Number/selection of cases? Number/selection of conditions? ppropriate Q terminology? N: usefuzzy dataonly! alibration in fsq alibration in fsq 30 5
6 Set calibration in llan/ldred 2011 Set calibration in llan/ldred 2011 pp : alibration in fsq alibration in fsq 32 Outlook & Task for next week Truth table/ truth table analysis Readings: Your Q texts ND Kim/Lee; Krook 2010; Freitag/Schlicht 2009 ND Emmenegger, Patrick "Job Security Regulations in Western Democracies: Fuzzy Set nalysis." European Journal of Political Research50 (3): Questions: re they truth tables(with all information needed)? re theyin thetext? Whataboutcontradictory rows? j) ontradictory Truth Table Rows Should e Resolved prior to Minimizing the Truth Table (ourse ible: 7) alibration in fsq 33 6
Qualitative Comparative Analysis (QCA) and Fuzzy Sets. 24 June 2013: Code of Good Standards. Prof. Dr. Claudius Wagemann
Institut für Politikwissenschaft Schwerpunkt qualitative empirische Sozialforschung Goethe-Universität Frankfurt Fachbereich 03 Prof. Dr. Claudius Wagemann Qualitative Comparative Analysis (QCA) and 24
List of figures List of tables Acknowledgements
List of figures List of tables Acknowledgements page xii xiv xvi Introduction 1 Set-theoretic approaches in the social sciences 1 Qualitative as a set-theoretic approach and technique 8 Variants of QCA
11 Sets II Operations
11 Sets II Operations Tom Lewis Fall Term 2010 Tom Lewis () 11 Sets II Operations Fall Term 2010 1 / 12 Outline 1 Union and intersection 2 Set operations 3 The size of a union 4 Difference and symmetric
Software Reliability and Reusability CS614
Software Reliability and Reusability CS614 Assiut University Faculty of Computers & Information Quality Assurance Unit Software Reliability and Reusability Course Specifications2011-2012 Relevant program
WEEK 13: FSQCA IN R THOMAS ELLIOTT
WEEK 13: FSQCA IN R THOMAS ELLIOTT This week we ll see how to run qualitative comparative analysis (QCA) in R. While Charles Ragin provides a program on his website for running QCA, it is not able to do
Excel Conditional Formatting (Mac)
[Type here] Excel Conditional Formatting (Mac) Using colour to make data analysis easier Excel conditional formatting automatically formats cells in your worksheet if specified criteria are met, giving
Alignment matrix of unit standard
Alignment matrix of unit standard 116937 Cyberlab basic spreadsheet skills programme Use a Graphical User Interface (GUI)-based spreadsheet application to create and edit spreadsheets. Please note: The
How to design and print cards using a database connection with. emedia CS Software
How to design and print cards using a database connection with emedia CS Software For this exercise, we will use a Database that has been created in EXCEL. The example below shows the database fields populated
Quick Reference Card Capacity and Demand Planning via Resource Workbench
This document outlines the steps for resource managers to allocate their staff to projects. Allocations should be done on a quarterly basis and are reviewed by the portfolio manager and director. managers
Solving a Decision Making Problem Using Weighted Fuzzy Soft Matrix
12 Solving a Decision Making Problem Using Weighted Fuzzy Soft Matrix S. Senthilkumar Department of Mathematics,.V.C. College (utonomous), Mayiladuthurai-609305 BSTRCT The purpose of this paper is to use
USER S GUIDE TO. Fuzzy-Set / Qualitative Comparative Analysis
USER S GUIDE TO Fuzzy-Set / Qualitative Comparative Analysis Charles C. Ragin Department of Sociology University of California, Irvine Irvine, CA cragin@uci.edu Assisted by: Tyson Patros Sarah Ilene Strand
INSERT SUBTOTALS Database Exercise Sort the Data Department Department Data Tab Sort and Filter Group
INSERT SUBTOTALS Subtotals are used to summarize data in a range of data. This command offers many kinds of summary information, including counts, sums, averages, minimums, and maximums. When this feature
STUDENT USER GUIDE Vesna Gasovski
STUDENT USER GUIDE Vesna Gasovski 1/6/2016 Contents Introduction... 3 What is InPlace?... 3 How can I access InPlace?... 3 Desktop vs Mobile view... 3 Glossary of Terms... 4 Home Page... 5 My Details...
BOOST Weekly Reporting Excel Steps: How to Obtain Your Data
BOOST Weekly Reporting Excel Steps: How to Obtain Your Data These steps provide an overview of how to identify, and obtain counts for the number of clients at your primary opiate agonist therapy (OAT)
CS 450 Exam 2 Mon. 4/11/2016
CS 450 Exam 2 Mon. 4/11/2016 Name: Rules and Hints You may use one handwritten 8.5 11 cheat sheet (front and back). This is the only additional resource you may consult during this exam. No calculators.
Multivariate Data More Overview
Multivariate Data More Overview CS 4460 - Information Visualization Jim Foley Last Revision August 2016 Some Key Concepts Quick Review Data Types Data Marks Basic Data Types N-Nominal (categorical) Equal
Pivot Tables, Lookup Tables and Scenarios
Introduction Format and manipulate data using pivot tables. Using a grading sheet as and example you will be shown how to set up and use lookup tables and scenarios. Contents Introduction Contents Pivot
CONTENTS 1) GENERAL. 1.1 About this guide About the CPD Scheme System Compatibility. 3 2) SYSTEM SET-UP
CONTENTS 1) GENERAL 1.1 About this guide. 1 1.2 About the CPD Scheme 2 1.3 System Compatibility. 3 2) SYSTEM SET-UP 2.1 Setting up your CPD year. 5 2.2 Requesting a date change for your CPD year. 9 2.3
The following illustrates what you will see when you log in to Home Access Center (HAC).
Instructions for Home Access Center The following illustrates what you will see when you log in to Home Access Center (HAC). Login Screen Here is where you will login using the username and password that
1. Data Analysis Yields Numbers & Visualizations. 2. Why Visualize Data? 3. What do Visualizations do? 4. Research on Visualizations
Data Analysis & Business Intelligence Made Easy with Excel Power Tools Excel Data Analysis Basics = E-DAB Notes for Video: E-DAB-05- Visualizations: Table, Charts, Conditional Formatting & Dashboards Outcomes
Transfer Student Records
Transfer Student Records Students transfer in and out of school districts on a regular basis. This exciting new feature provides districts the ability to transfer student records from one district to another,
IA Digital Electronics - Supervision I
IA Digital Electronics - Supervision I Nandor Licker Due noon two days before the supervision 1 Overview The goal of this exercise is to design an 8-digit calculator capable of adding
Database Design. 2-3 Entity Relationship Modeling and ERDs. Copyright 2015, Oracle and/or its affiliates. All rights reserved.
Database Design 2-3 Objectives This lesson covers the following objectives: Define the meaning of implementation-free as it relates to data models and database design implementation List the four goals
BASIC NAVIGATION & VIEWS...
Content Overview VISUAL TOUR... 5 NEW FEATURES IN OUTLOOK 2010... 6 BASIC NAVIGATION & VIEWS... 7 SETTING PREFERENCES... 7 Creating an Outlook Shortcut... 7 Choosing a Startup View... 7 CUSTOMIZING INBOX
Compulsory course in Computer Science
Compulsory course in Computer Science University of Macau Faculty of Science and Technology Department of Computer and Information Science SFTW241 Programming Languages Architecture I Syllabus 2 nd Semester
Fuzzy Set Theory and Its Applications. Second, Revised Edition. H.-J. Zimmermann. Kluwer Academic Publishers Boston / Dordrecht/ London
Fuzzy Set Theory and Its Applications Second, Revised Edition H.-J. Zimmermann KM ff Kluwer Academic Publishers Boston / Dordrecht/ London Contents List of Figures List of Tables Foreword Preface Preface
2.1 Sets 2.2 Set Operations
CSC2510 Theoretical Foundations of Computer Science 2.1 Sets 2.2 Set Operations Introduction to Set Theory A set is a structure, representing an unordered collection (group, plurality) of zero or more
[If you have been ed the Add-In save the attachment in the and proceed as below.]
![[If you have been ed the Add-In save the attachment in the and proceed as below.]](/thumbs/95/126110174.jpg "[If you have been ed the Add-In save the attachment in the and proceed as below.]")
XL-excellence spreadsheet Add-In Overview The XL-excellence Add-In provides tools to help develop high-quality spreadsheets. Examples of these tools include reports that highlight cells containing errors,
How To Analyze Nodularity Using PAX-it Version 5.1 or Higher
How To nalyze Nodularity Using PX-it Version 5.1 or Higher LEO orporation; Saint Joseph, Michigan US Goal of This Document The goal of this document is to demonstrate how to configure the Nodularity feature
Queries with Multiple Criteria (OR)
Queries with Multiple Criteria (OR) When a query has multiple criteria, logical operators such as AND or OR combine the criteria together. This exercise has two example questions to illustrate, in two
Introduction to Minitab 1
Introduction to Minitab 1 We begin by first starting Minitab. You may choose to either 1. click on the Minitab icon in the corner of your screen 2. go to the lower left and hit Start, then from All Programs,
Geography 281 Map Making with GIS Project Three: Viewing Data Spatially
Geography 281 Map Making with GIS Project Three: Viewing Data Spatially This activity introduces three of the most common thematic maps: Choropleth maps Dot density maps Graduated symbol maps You will
Word counts and match values
integrated translation environment Word counts and match values 2004-2014 Kilgray Translation Technologies. All rights reserved. 2004-2014 ZAAC. All rights reserved. Contents Contents... 2 1 General...
CS 177. Lists and Matrices. Week 8
CS 177 Lists and Matrices Week 8 1 Announcements Project 2 due on 7 th March, 2015 at 11.59 pm Table of Contents Lists Matrices Traversing a Matrix Construction of Matrices 3 Just a list of numbers 1D
Eric Roberts Handout #39 CS 106B February 20, 2015 Sets
Eric Roberts Handout #39 S 106 February 20, 2015 Sets Sets Eric Roberts S 106 February 20, 2015 Outline 1. Midcourse correction 2. Sets in mathematics 3. Venn diagrams 4. High-level set operations 5. Implementing
Introduction II. Sets. Terminology III. Definition. Definition. Definition. Example
Sets Slides by Christopher M. ourke Instructor: erthe Y. Choueiry Spring 2006 Computer Science & Engineering 235 Introduction to Discrete Mathematics Sections 1.6 1.7 of Rosen cse235@cse.unl.edu Introduction
Applied Regression Modeling: A Business Approach
i Applied Regression Modeling: A Business Approach Computer software help: SAS SAS (originally Statistical Analysis Software ) is a commercial statistical software package based on a powerful programming
c) the set of students at your school who either are sophomores or are taking discrete mathematics
Exercises Exercises Page 136 1. Let A be the set of students who live within one mile of school and let B be the set of students who walk to classes. Describe the students in each of these sets. a) A B
Financial Reporting and Analysis
Financial Reporting and Analysis Study guidance for the 15 th Edition of the recommended text The information below indicates which parts of the recommended text, Financial Accounting and Reporting 15
Package SetMethods. April 25, 2018
Type Package Package SetMethods April 25, 2018 Title Functions for Set-Theoretic Multi-Method Research and Advanced QCA Version 2.3.1 Date 2018-04-24 Author Juraj Medzihorsky [aut], Ioana-Elena Oana [aut,
Implementation of a reporting workflow to maintain data lineage for major water resource modelling projects
18 th World IMACS / MODSIM Congress, Cairns, Australia 13-17 July 2009 http://mssanz.org.au/modsim09 Implementation of a reporting workflow to maintain data lineage for major water Merrin, L.E. 1 and S.M.
Computational Intelligence Winter Term 2017/18
Computational Intelligence Winter Term 2017/18 Prof. Dr. Günter Rudolph Lehrstuhl für Algorithm Engineering (LS 11) Fakultät für Informatik TU Dortmund Plan for Today Fuzzy Clustering 2 Cluster Formation
Elementary Statistics. Chapter 2 Review: Summarizing & Graphing Data
Name Elementary Statistics Date Period Chapter 2 Review: Summarizing & Graphing Data Quick Quiz p.74 #1-10 Use the following information to answer questions 1-3: When one is constructing a table representing
Nearest Neighbor Classification
Nearest Neighbor Classification Professor Ameet Talwalkar Professor Ameet Talwalkar CS260 Machine Learning Algorithms January 11, 2017 1 / 48 Outline 1 Administration 2 First learning algorithm: Nearest
rading Periods can be deleted by selecting the Delete checkbox and Saving the document.
Goals Tab Goals added to this IEP will be available in the student s Progress Report once this IEP is finalized. Add the Grading Periods dates for Progress Reports. Enter the Date for the Grading Periods
Introduction to Mplus
Introduction to Mplus May 12, 2010 SPONSORED BY: Research Data Centre Population and Life Course Studies PLCS Interdisciplinary Development Initiative Piotr Wilk piotr.wilk@schulich.uwo.ca OVERVIEW Mplus
Quality and Six Sigma Tools using MINITAB Statistical Software: A complete Guide to Six Sigma DMAIC Tools using MINITAB
Samples from MINITAB Book Quality and Six Sigma Tools using MINITAB Statistical Software A complete Guide to Six Sigma DMAIC Tools using MINITAB Prof. Amar Sahay, Ph.D. One of the major objectives of this
DATIX. Risk Management Information System. Risk Register Module. User Guide
DATIX Risk Management Information System Risk Register Module User Guide Contents Using Datix Web Manager Risk Register 2 Access Requirements 2 Accessing Datix 2 Adding Datix as Favorite 2 Creating a shortcut
USER GUIDE. SAP EHSM-RA-Job Safety Analysis of GAIL (India) Limited
SAP EHSM-RA-Job Safety Analysis of GAIL (India) Limited 1 TABLE OF CONTENTS 1. Create JSA... 3 2. Risk Identification... 6 3. Review and Analyze the Risk... 11 4. Assign Job Location with similar Risk...
Granular Computing: A Paradigm in Information Processing Saroj K. Meher Center for Soft Computing Research Indian Statistical Institute, Kolkata
Granular Computing: A Paradigm in Information Processing Saroj K. Meher Center for Soft Computing Research Indian Statistical Institute, Kolkata Granular computing (GrC): Outline Introduction Definitions
Bézier Surface Modeling for Neutrosophic Data Problems
Neutrosophic Sets and Systems, Vol. 19, 2018 19 University of New Mexico Bézier Surface Modeling for Neutrosophic Data Problems Selçuk Topal 1 * and Ferhat Taş 2 1 Department of Mathematics, Faculty of
eschoolplus+ Cognos Query Studio Training Guide Version 2.4
+ Training Guide Version 2.4 May 2015 Arkansas Public School Computer Network This page was intentionally left blank Page 2 of 68 Table of Contents... 5 Accessing... 5 Working in Query Studio... 8 Query
IT 1033: Fundamentals of Programming Loops
IT 1033: Fundamentals of Programming Loops Budditha Hettige Department of Computer Science Repetitions: Loops A loop is a sequence of instruction s that is continually repeated until a certain condition
Data Migration Plan (40) Fingrid Oyj
1 (40) Fingrid Oyj FI10728943, VAT reg. 2 (40) Table of Contents Definitions... 5 1 Summary... 6 2 Introduction... 7 2.1 Datahub... 7 2.2 Members of the data migration plan... 8 2.3 Datahub's data migration
Excel VLOOKUP. An EMIS Coordinator s Friend
Excel VLOOKUP An EMIS Coordinator s Friend Vlookup, a function in excel, stands for Vertical Lookup. This function allows you to search a specific table of data, look for a match within the table of data
Introduction to R Programming
Course Overview Over the past few years, R has been steadily gaining popularity with business analysts, statisticians and data scientists as a tool of choice for conducting statistical analysis of data
System of Systems Complexity Identification and Control
System of Systems Identification and ontrol Joseph J. Simpson Systems oncepts nd ve NW # Seattle, W jjs-sbw@eskimo.com Mary J. Simpson Systems oncepts nd ve NW # Seattle, W mjs-sbw@eskimo.com bstract System
Course Syllabus MECHANICAL ENGINEERING LABORATORY I Spring 2006
Course Syllabus 22.302 - MECHANICAL ENGINEERING LABORATORY I Spring 2006 Classes: Instructors: Teaching Assistants: Textbook: Tuesday at 12:30 2:30 PM Majid Charmchi, B224, 934-2969; Majid_Charmchi@uml.edu
NEW NAPA PROLink Smart Search
NEW NP PROLink Smart Search The new PROLink Smart-Search makes it faster and easier than ever before to locate hard to find items by part description! Smart-Search allows you to begin entering the first
1.2 Venn Diagrams and Partitions
1.2 Venn Diagrams and Partitions Mark R. Woodard Furman U 2010 Mark R. Woodard (Furman U) 1.2 Venn Diagrams and Partitions 2010 1 / 9 Outline 1 Venn Diagrams 2 Partitions 3 Fundamentals of Counting Mark
Evolutionary Algorithms Introduction
Evolutionary Algorithms Introduction Prof. Dr. Rudolf Kruse Pascal Held {kruse,pheld}@iws.cs.uni-magdeburg.de Otto-von-Guericke-Universität Magdeburg Fakultät für Informatik Institut für Wissens- und Sprachverarbeitung
Beginning Excel. Revised 4/19/16
Beginning Excel Objectives: The Learner will: Become familiar with terminology used in Microsoft Excel Create a simple workbook Write a simple formula Formatting Cells Adding Columns Borders Table of Contents:
Manual for creating prioritization schemes (using the Profiling Scheme Editor)
Manual for creating prioritization schemes (using the Profiling Scheme Editor) Manual for creating prioritization schemes (using the Profiling Scheme Editor) Page 1 Contents 1. Features of the editor...
A Soft Computing-Based Method for the Identification of Best Practices, with Application in the Petroleum Industry
CIMSA 2005 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications Giardini Naxos, Italy, 20-22 July 2005 A Soft Computing-Based Method for the Identification
PDS Detailed User Guide
PDS Detailed User Guide The Planwell PDS login page can be accessed from a link provided on your Reprographer s website. Enter in the username and password created for your account. The PDS homepage will
School of Computer Science
Course Title: Date: 10/30/03 Course Number: COP-340 Number of Credits: 3 Subject Area: Computer Systems Subject Area Coordinator: Masoud Sadjadi email: sadjadi@cis.fiu.edu Catalog Description: Overview
CS 1110, LAB 2: ASSIGNMENTS AND STRINGS
CS 1110, LAB 2: ASSIGNMENTS AND STRINGS http://www.cs.cornell.edu/courses/cs1110/2014fa/labs/lab02.pdf First Name: Last Name: NetID: The purpose of this lab is to get you comfortable with using assignment
Southwest Power Pool Portal Market Participant General User s Guide
Southwest Power Pool Portal Market Participant General User s Guide 1. Overview... 4 1.1 User Roles... 4 1.1.1 Market Participant Level Roles... 4 1.1.2. Asset Owner Level Roles... 4 1.1.3. Market Operations
Rubrics. Creating a Rubric
Rubrics A rubric is a set of specific evaluation criteria used to assess an assignment. Instructors use rubrics to carefully outline their assignment requirements and expectations for students. Students
CS Introduction to Data Mining Instructor: Abdullah Mueen
CS 591.03 Introduction to Data Mining Instructor: Abdullah Mueen LECTURE 8: ADVANCED CLUSTERING (FUZZY AND CO -CLUSTERING) Review: Basic Cluster Analysis Methods (Chap. 10) Cluster Analysis: Basic Concepts
What is Advisor Center?
What is Advisor Center? The Advisor Center is a portal within HUB that provides you a modified view of what students see when they log into HUB. It serves as an online one step shop to access a student
RISKMAN QUICK REFERENCE GUIDE TO MANAGING & CREATING ALERTS
Introduction This reference guide is aimed at Administrators/Managers who will be responsible for creating and managing Alerts within RiskMan. Alerts can be created for all Registers that are activated
CHAPTER 4 FUZZY LOGIC, K-MEANS, FUZZY C-MEANS AND BAYESIAN METHODS
CHAPTER 4 FUZZY LOGIC, K-MEANS, FUZZY C-MEANS AND BAYESIAN METHODS 4.1. INTRODUCTION This chapter includes implementation and testing of the student s academic performance evaluation to achieve the objective(s)
Static Program Analysis
Static Program Analysis Lecture 1: Introduction to Program Analysis Thomas Noll Lehrstuhl für Informatik 2 (Software Modeling and Verification) noll@cs.rwth-aachen.de http://moves.rwth-aachen.de/teaching/ws-1415/spa/
Inserting cell content with the fill handle
2 Creating and editing useful spreadsheets Creating lists automatically D EXCEL 2016 5 minutes Inserting cell content with the fill handle Fill options Fill options-r 1. Open the Fill options exercise
Setting up an IT Network
Unit 16: Setting up an IT Network Unit code: M/601/3274 QCF Level 2: BTEC Specialist Credit value: 10 Guided learning hours: 60 Aim and purpose This unit enables learners to understand the role of IT networks
Introduction to CS databases and statistics in Excel Jacek Wiślicki, Laurent Babout,
One of the applications of MS Excel is data processing and statistical analysis. The following exercises will demonstrate some of these functions. The base files for the exercises is included in http://lbabout.iis.p.lodz.pl/teaching_and_student_projects_files/files/us/lab_04b.zip.
Take Technology Into Your Own Hands. Joann Denby, Oakland University Ken Harris, Wayne State University
Take Technology Into Your Own Hands Joann Denby, Oakland University Ken Harris, Wayne State University Returning Student Project At Wayne State University an initiative was started by the Registrar s office
CAPACITY PLANNING FOR THE DATA WAREHOUSE BY W. H. Inmon
CAPACITY PLANNING FOR THE DATA WAREHOUSE BY W. H. Inmon The data warehouse environment - like all other computer environments - requires hardware resources. Given the volume of data and the type of processing
Hot Events - Events of interest to the community, such as Admissions, theater, and open-house events.
MCC Events Calendar/Room Request Procedure CONTENTS: Click on a topic link below to go directly to that section of the document. Webviewer: Overview of MCC Events Calender Webviewer Event Details: Explanation
Customer Progress s Enhancement
Dealer Business Management Software for Contract Furniture Dealers Customer Progress Emails Enhancement Version 2.0 / January 2014 17.05.00 or higher This module and all associated changes throughout the
Data Management Lecture Outline 2 Part 2. Instructor: Trevor Nadeau
Data Management Lecture Outline 2 Part 2 Instructor: Trevor Nadeau Data Entities, Attributes, and Items Entity: Things we store information about. (i.e. persons, places, objects, events, etc.) Have relationships
Managing the Burn Down Agent
Managing the Burn Down Agent Agile Studio 7.4 May 2018 Introduction Agile Studio 7.4 has several burn down charts that teams and managers can use to view the overall progress of a sprint, team, or release.
Modeling and computer simulation of real process solution of Mastermind board game
Modeling and computer simulation of real process solution of Mastermind board game Stepan Hubalovsky Abstract One of the most important methods in current scientific and technological research as well
Introduction to digital image classification
Introduction to digital image classification Dr. Norman Kerle, Wan Bakx MSc a.o. INTERNATIONAL INSTITUTE FOR GEO-INFORMATION SCIENCE AND EARTH OBSERVATION Purpose of lecture Main lecture topics Review
STATE COLLEGE OF NEW YORK COLLEGE OF TECHNOLOGY CANTON, NEW YORK COURSE OUTLINE MFGT INSTRUMENTATION AND CONTROLS
STATE COLLEGE OF NEW YORK COLLEGE OF TECHNOLOGY CANTON, NEW YORK COURSE OUTLINE MFGT 220 - INSTRUMENTATION AND CONTROLS Prepared By: Daniel Miller Revised By: Daniel Miller 4/5/12 CANINO SCHOOL OF ENGINEERING
2015 Arkansas Department of Education Data & Reporting Conference. Cognos Query Studio
2015 Arkansas Department of Education Data & Reporting Conference Cognos Query Studio SMS Workshop August 7, 2015 Arkansas Public School Computer Network CREATING REPORTS USED TO GENERATE DATA FILES 1.
ASSIUT UNIVERSITY. Faculty of Computers and Information Department of Information Technology. on Technology. IT PH.D. Program.
ASSIUT UNIVERSITY Faculty of Computers and Information Department of Information Technology Informatiio on Technology PhD Program IT PH.D. Program Page 0 Assiut University Faculty of Computers & Informationn
IJISET - International Journal of Innovative Science, Engineering & Technology, Vol. 1 Issue 3, May
Optimization of fuzzy assignment model with triangular fuzzy numbers using Robust Ranking technique Dr. K. Kalaiarasi 1,Prof. S.Sindhu 2, Dr. M. Arunadevi 3 1 Associate Professor Dept. of Mathematics 2
INDE499B: Information Systems Course Review Autumn 2000
INDE499B: Information Systems Course Review Autumn 2000 WHAT did we cover? HOW did we cover it? WHY did we cover it? And the exam, what s on it INDE499B: Information Systems Course Review Autumn 2000 WHAT
Textbook(s) and other required material: Raghu Ramakrishnan & Johannes Gehrke, Database Management Systems, Third edition, McGraw Hill, 2003.
Elective course in Computer Science University of Macau Faculty of Science and Technology Department of Computer and Information Science SFTW371 Database Systems II Syllabus 1 st Semester 2013/2014 Part
E0005E - Industrial Image Analysis
E0005E - Industrial Image Analysis The Hough Transform Matthew Thurley slides by Johan Carlson 1 This Lecture The Hough transform Detection of lines Detection of other shapes (the generalized Hough transform)
RISKMAN REFERENCE GUIDE TO CREATING & MANAGING ALERTS
Introduction This reference guide is aimed at Administrators/Managers who will be responsible for creating and managing alerts within RiskMan Step : Details What is an Alert? User Defined Alerts are a
Introduction to Statistics lab 1
Introduction to Statistics lab 1 Johan A. Elkink jos.elkink@ucd.ie 7 September 2015 The main purpose of today s class is to get a feel for how to open, access and view data, and to get some familiarity
Opera 3 Nominal Ledger Training Manual
Opera 3 Nominal Ledger Training Manual Contents Overview... 3 Open Period Accounting... 3 Period End... 4 Journals... 5 Posting a Journal... 5 Creating a Journal... 6 Basic Journal... 6 Recurring Journal...
Using the HP IP/IPX Printer Gateway
Using the HP IP/IPX Printer Gateway Notice The information contained in this document is subject to change without notice. HEWLETT-PACKARD COMPANY MAKES NO WARRANTY OF ANY KIND WITH REGARD TO THIS MATERIAL,
Creating Individual Student Account(s)
TASK: TIME FRAME: 6 weeks prior to first test administration These processes will allow you to create individual student accounts, or upload multiple student accounts. The Site Administrator should use
CS473: Course Review CS-473. Luo Si Department of Computer Science Purdue University
CS473: CS-473 Course Review Luo Si Department of Computer Science Purdue University Basic Concepts of IR: Outline Basic Concepts of Information Retrieval: Task definition of Ad-hoc IR Terminologies and
1) Give a set-theoretic description of the given points as a subset W of R 3. a) The points on the plane x + y 2z = 0.
) Give a set-theoretic description of the given points as a subset W of R. a) The points on the plane x + y z =. x Solution: W = {x: x = [ x ], x + x x = }. x b) The points in the yz-plane. Solution: W
Excel. Spreadsheet functions
Excel Spreadsheet functions Objectives Week 1 By the end of this session you will be able to :- Move around workbooks and worksheets Insert and delete rows and columns Calculate with the Auto Sum function