From Business Statistics Made Easy in SAS. Full book available for purchase here. Chapter 1 Introduction to the Central Textbook Example...
|
|
- Clifford Lester
- 5 years ago
- Views:
Transcription
1 From Business Statistics Made Easy in SAS. Full book available for purchase here. Preface ix About the Author xv Acknowledgments xvii Chapter 1 Introduction to the Central Textbook Example Introduction The Company Current Research Needs of the Company Your Brief for the Case Example Extended Analytical Skills Needed in the Project Chapter 2 Introduction to the Statistics Process Introductory Case: Big Data in the Airline Industry Introduction to the Statistics Process Step 1: Your Needs & Requirements Step 2: Getting Data Step 3: Extracting Statistics from the Data Step 4: Understanding & Decision Making Summary: Challenges in the Statistics Process Advice to the Statistically Terrified Chapter 3 Introduction to Data Introductory Case: Royal FrieslandCampina Brief Introduction to Samples, Populations & Data Basic Characteristics of Variables Chapter 4 Data Collection & Capture Introduction Correct Sampling Choose Constructs and Variable Measurements Initial Data Capture: Which Package? Dealing with Data Once It Has Been Captured
2 iv Database & Data Analysis Software Some Complications in Datasets Chapter 5 Introduction to SAS Introductory Vignette: SAS On Top of the Analytics World Brief Introduction to SAS Introduction to the Textbook Materials Getting Started with SAS 9 or SAS Studio Chapter 6 Basics of SAS Programs, Data Manipulation, Analysis & Reporting Introduction The Running Data Example The Pre-Analysis Data Cleaning & Preparation Steps Overview of the Three Big Tasks in Business Statistics.. 73 Basic Introduction to SAS Programming Major Task #1: Data Manipulation in SAS Major Task #2: Data Analysis Major Task #3: SAS Reporting through Output Formats. 84 The Visual Programmer Mode in SAS Studio Conclusion Chapter 7 Descriptive Statistics: Understand your Data Introductory Case: 2007 AngloGold Ashanti Look Ahead Introduction End Outcome of a Descriptive Statistics Analysis Getting Descriptive Statistics in SAS Statistics Measuring Centrality Basic Statistics Assessing Variable Spread Assessing Shape of a Variable s Distribution Conclusion on Descriptive Statistics Appendix A to Chapter 7: Basic Normality Statistics Chapter 8 Basics of Associating Variables Introduction
3 v What is Statistical Association? Association Does Not Mean Causation Overview of Associations for Different Variable Types Relating Continuous or Ordinal Data: Correlation & Covariance Relating Categorical Variables Chapter 9 Using Basic Statistics to Check & Fix Data Introduction Inappropriate Data Points Dealing Practically with Missing Data Checking Centrality & Spread Strange Variable Distributions Dealing Practically with Multi-Item Scales Chapter 10 Introduction to Graphing in SAS Introduction Major Graphing Procedures in SAS The PROC SGPLOT Routine in SAS Multiple Plots Simultaneously through PROC SGPANEL Business Dashboards through PROC GKPI Geographical Mapping Using PROC GMAP PROC SGSCATTER for Multiple Scatterplots Conclusion on SAS Graphing Chapter 11 The Statistics Process: Fitting Models to Data Introduction Look for Patterns in the Data (Fit) Step 3: Interpret the Pattern Summary of the Statistics Process Chapter 12 Key Concepts: Size & Accuracy Illustrative Case: Pharmaceuticals I AstraZeneca s Crestor Introduction
4 vi Issue # 1: Size of a Statistic Issue # 2: Accuracy of Statistics The Aspects of Inaccuracy Putting Statistical Size and Accuracy Together Conclusion Appendix A to Chapter 12: More on Accuracy (optional) Chapter 13 Introduction to Linear Regression Illustrative Case: West Point Introduction The Core Textbook Case Example for Chapter Introduction to Linear Regression A Pictorial Walk through Regression Implementing Multiple Regression in SAS Step 1: Collect, Capture and Clean Data Step 2: Run an Initial Regression Analysis Step 3: Assess Fit and Apply Remedies If Necessary Step 4: Interpret the Regression Slopes Step 5: Reporting a Multiple Regression Result Other Statistical Forms Conclusion Chapter 14 Categories Explaining a Continuous Variable: Comparing Two Means Introduction to Comparison of Categories Features of the Continuous Variable to Compare Across Categories Two Types of Categories to Compare Numbers of Categories to Compare: Two vs. More than Two Data Assumptions and Alternatives when Comparing Categories Comparing Two Means: T-Tests
5 vii Comparing Means for More than Two Categories: ANOVA Chapter 15 Categorical Data Distributions & Associations Introduction Repeat: One-Way Categorical Distributions Repeat: Linking Categorical Variables Together Further Statistical Questions about Categorical Data Assessing One-Way Frequencies Tests of Categorical Variable Association Conclusion on Categorical Data Analysis Chapter 16 Reporting Business Analytics Reminder - Your Brief for the Textbook Case Study Your Tasks in the Analytics and Reporting Stages Background Analyses Versus Displayed Reports for the CEO Conclusion on Business Statistics Reporting Chapter 17 Business Analysis from Statistics: Introduction Case Study: Oracle South Africa Introduction Overall Financial Extrapolation Process Step 1: Statistics Gives Level of or Change in Focal Variables Step 2: Financial Estimates of Revenue or Cost of One Unit Step 3: Combine Statistics with Per-Unit Financial Values Step 4: Include Scope Steps 5 and 6: Net Profitability Calculations Some Simple Examples of Business Extrapolation Conclusion of Statistical Business Extrapolation Chapter 18 Miscellaneous Business Statistics Topics Introduction
6 viii Big Data Data Warehousing Machine Learning & Algorithms Simulation in Business Situations Bayesian Statistics Conclusion Chapter 19 Bibliography Books and Articles Index From Business Statistics Made Easy in SAS, by Gregory John Lee. Copyright 2015, SAS Institute Inc., Cary, North Carolina, USA. ALL RIGHTS RESERVED.
Probability and Statistics Curriculum Pacing Guide
Unit 1 Terms PS.SPMJ.3 PS.SPMJ.5 Plan and conduct a survey to answer a statistical question. Recognize how the plan addresses sampling technique, randomization, measurement of experimental error and methods
More informationKnowledge management styles and performance: a knowledge space model from both theoretical and empirical perspectives
University of Wollongong Research Online University of Wollongong Thesis Collection University of Wollongong Thesis Collections 2004 Knowledge management styles and performance: a knowledge space model
More informationA Model to Predict 24-Hour Urinary Creatinine Level Using Repeated Measurements
Virginia Commonwealth University VCU Scholars Compass Theses and Dissertations Graduate School 2006 A Model to Predict 24-Hour Urinary Creatinine Level Using Repeated Measurements Donna S. Kroos Virginia
More informationInstructor: Mario D. Garrett, Ph.D. Phone: Office: Hepner Hall (HH) 100
San Diego State University School of Social Work 610 COMPUTER APPLICATIONS FOR SOCIAL WORK PRACTICE Statistical Package for the Social Sciences Office: Hepner Hall (HH) 100 Instructor: Mario D. Garrett,
More informationPython Machine Learning
Python Machine Learning Unlock deeper insights into machine learning with this vital guide to cuttingedge predictive analytics Sebastian Raschka [ PUBLISHING 1 open source I community experience distilled
More informationSociology 521: Social Statistics and Quantitative Methods I Spring 2013 Mondays 2 5pm Kap 305 Computer Lab. Course Website
Sociology 521: Social Statistics and Quantitative Methods I Spring 2013 Mondays 2 5pm Kap 305 Computer Lab Instructor: Tim Biblarz Office: Hazel Stanley Hall (HSH) Room 210 Office hours: Mon, 5 6pm, F,
More informationPurdue Data Summit Communication of Big Data Analytics. New SAT Predictive Validity Case Study
Purdue Data Summit 2017 Communication of Big Data Analytics New SAT Predictive Validity Case Study Paul M. Johnson, Ed.D. Associate Vice President for Enrollment Management, Research & Enrollment Information
More informationCS Machine Learning
CS 478 - Machine Learning Projects Data Representation Basic testing and evaluation schemes CS 478 Data and Testing 1 Programming Issues l Program in any platform you want l Realize that you will be doing
More informationBHA 4053, Financial Management in Health Care Organizations Course Syllabus. Course Description. Course Textbook. Course Learning Outcomes.
BHA 4053, Financial Management in Health Care Organizations Course Syllabus Course Description Introduces key aspects of financial management for today's healthcare organizations, addressing diverse factors
More informationGRADUATE STUDENT HANDBOOK Master of Science Programs in Biostatistics
2017-2018 GRADUATE STUDENT HANDBOOK Master of Science Programs in Biostatistics Entrance requirements, program descriptions, degree requirements and other program policies for Biostatistics Master s Programs
More informationGuide to Teaching Computer Science
Guide to Teaching Computer Science Orit Hazzan Tami Lapidot Noa Ragonis Guide to Teaching Computer Science An Activity-Based Approach Dr. Orit Hazzan Associate Professor Technion - Israel Institute of
More informationRadius STEM Readiness TM
Curriculum Guide Radius STEM Readiness TM While today s teens are surrounded by technology, we face a stark and imminent shortage of graduates pursuing careers in Science, Technology, Engineering, and
More informationEconomics 201 Principles of Microeconomics Fall 2010 MWF 10:00 10:50am 160 Bryan Building
Economics 201 Principles of Microeconomics Fall 2010 MWF 10:00 10:50am 160 Bryan Building Professor: Dr. Michelle Sheran Office: 445 Bryan Building Phone: 256-1192 E-mail: mesheran@uncg.edu Office Hours:
More informationTABLE OF CONTENTS TABLE OF CONTENTS COVER PAGE HALAMAN PENGESAHAN PERNYATAAN NASKAH SOAL TUGAS AKHIR ACKNOWLEDGEMENT FOREWORD
TABLE OF CONTENTS TABLE OF CONTENTS COVER PAGE HALAMAN PENGESAHAN PERNYATAAN NASKAH SOAL TUGAS AKHIR ACKNOWLEDGEMENT FOREWORD TABLE OF CONTENTS LIST OF FIGURES LIST OF TABLES LIST OF APPENDICES LIST OF
More informationCHALLENGES FACING DEVELOPMENT OF STRATEGIC PLANS IN PUBLIC SECONDARY SCHOOLS IN MWINGI CENTRAL DISTRICT, KENYA
CHALLENGES FACING DEVELOPMENT OF STRATEGIC PLANS IN PUBLIC SECONDARY SCHOOLS IN MWINGI CENTRAL DISTRICT, KENYA By Koma Timothy Mutua Reg. No. GMB/M/0870/08/11 A Research Project Submitted In Partial Fulfilment
More informationBittinger, M. L., Ellenbogen, D. J., & Johnson, B. L. (2012). Prealgebra (6th ed.). Boston, MA: Addison-Wesley.
Course Syllabus Course Description Explores the basic fundamentals of college-level mathematics. (Note: This course is for institutional credit only and will not be used in meeting degree requirements.
More informationResearch Design & Analysis Made Easy! Brainstorming Worksheet
Brainstorming Worksheet 1) Choose a Topic a) What are you passionate about? b) What are your library s strengths? c) What are your library s weaknesses? d) What is a hot topic in the field right now that
More informationTIMSS ADVANCED 2015 USER GUIDE FOR THE INTERNATIONAL DATABASE. Pierre Foy
TIMSS ADVANCED 2015 USER GUIDE FOR THE INTERNATIONAL DATABASE Pierre Foy TIMSS Advanced 2015 orks User Guide for the International Database Pierre Foy Contributors: Victoria A.S. Centurino, Kerry E. Cotter,
More informationLecture 1: Machine Learning Basics
1/69 Lecture 1: Machine Learning Basics Ali Harakeh University of Waterloo WAVE Lab ali.harakeh@uwaterloo.ca May 1, 2017 2/69 Overview 1 Learning Algorithms 2 Capacity, Overfitting, and Underfitting 3
More informationInstrumentation, Control & Automation Staffing. Maintenance Benchmarking Study
Electronic Document Instrumentation, Control & Automation Staffing Prepared by ITA Technical Committee, Maintenance Subcommittee, Task Force on IC&A Staffing John Petito, Chair Richard Haugh, Vice-Chair
More informationSchool Size and the Quality of Teaching and Learning
School Size and the Quality of Teaching and Learning An Analysis of Relationships between School Size and Assessments of Factors Related to the Quality of Teaching and Learning in Primary Schools Undertaken
More informationThe 9 th International Scientific Conference elearning and software for Education Bucharest, April 25-26, / X
The 9 th International Scientific Conference elearning and software for Education Bucharest, April 25-26, 2013 10.12753/2066-026X-13-154 DATA MINING SOLUTIONS FOR DETERMINING STUDENT'S PROFILE Adela BÂRA,
More informationSTA 225: Introductory Statistics (CT)
Marshall University College of Science Mathematics Department STA 225: Introductory Statistics (CT) Course catalog description A critical thinking course in applied statistical reasoning covering basic
More informationRyerson University Sociology SOC 483: Advanced Research and Statistics
Ryerson University Sociology SOC 483: Advanced Research and Statistics Prerequisites: SOC 481 Instructor: Paul S. Moore E-mail: psmoore@ryerson.ca Office: Sociology Department Jorgenson JOR 306 Phone:
More informationWord Segmentation of Off-line Handwritten Documents
Word Segmentation of Off-line Handwritten Documents Chen Huang and Sargur N. Srihari {chuang5, srihari}@cedar.buffalo.edu Center of Excellence for Document Analysis and Recognition (CEDAR), Department
More informationIep Data Collection Templates
Iep Templates Free PDF ebook Download: Iep Templates Download or Read Online ebook iep data collection templates in PDF Format From The Best User Guide Database Data analysis process. Data collection and
More informationEDCI 699 Statistics: Content, Process, Application COURSE SYLLABUS: SPRING 2016
EDCI 699 Statistics: Content, Process, Application COURSE SYLLABUS: SPRING 2016 Instructor: Dr. Katy Denson, Ph.D. Office Hours: Because I live in Albuquerque, New Mexico, I won t have office hours. But
More informationCourse Content Concepts
CS 1371 SYLLABUS, Fall, 2017 Revised 8/6/17 Computing for Engineers Course Content Concepts The students will be expected to be familiar with the following concepts, either by writing code to solve problems,
More informationPROFESSIONAL TREATMENT OF TEACHERS AND STUDENT ACADEMIC ACHIEVEMENT. James B. Chapman. Dissertation submitted to the Faculty of the Virginia
PROFESSIONAL TREATMENT OF TEACHERS AND STUDENT ACADEMIC ACHIEVEMENT by James B. Chapman Dissertation submitted to the Faculty of the Virginia Polytechnic Institute and State University in partial fulfillment
More informationCriterion Met? Primary Supporting Y N Reading Street Comprehensive. Publisher Citations
Program 2: / Arts English Development Basic Program, K-8 Grade Level(s): K 3 SECTIO 1: PROGRAM DESCRIPTIO All instructional material submissions must meet the requirements of this program description section,
More informationOFFICE SUPPORT SPECIALIST Technical Diploma
OFFICE SUPPORT SPECIALIST Technical Diploma Program Code: 31-106-8 our graduates INDEMAND 2017/2018 mstc.edu administrative professional career pathway OFFICE SUPPORT SPECIALIST CUSTOMER RELATIONSHIP PROFESSIONAL
More informationACTL5103 Stochastic Modelling For Actuaries. Course Outline Semester 2, 2014
UNSW Australia Business School School of Risk and Actuarial Studies ACTL5103 Stochastic Modelling For Actuaries Course Outline Semester 2, 2014 Part A: Course-Specific Information Please consult Part B
More informationVOL. 3, NO. 5, May 2012 ISSN Journal of Emerging Trends in Computing and Information Sciences CIS Journal. All rights reserved.
Exploratory Study on Factors that Impact / Influence Success and failure of Students in the Foundation Computer Studies Course at the National University of Samoa 1 2 Elisapeta Mauai, Edna Temese 1 Computing
More informationStatistics and Data Analytics Minor
October 28, 2014 Page 1 of 6 PROGRAM IDENTIFICATION NAME OF THE MINOR Statistics and Data Analytics ACADEMIC PROGRAM PROPOSING THE MINOR Mathematics PROGRAM DESCRIPTION DESCRIPTION OF THE MINOR AND STUDENT
More informationMMOG Subscription Business Models: Table of Contents
DFC Intelligence DFC Intelligence Phone 858-780-9680 9320 Carmel Mountain Rd Fax 858-780-9671 Suite C www.dfcint.com San Diego, CA 92129 MMOG Subscription Business Models: Table of Contents November 2007
More informationSociology 521: Social Statistics and Quantitative Methods I Spring Wed. 2 5, Kap 305 Computer Lab. Course Website
Sociology 521: Social Statistics and Quantitative Methods I Spring 2012 Wed. 2 5, Kap 305 Computer Lab Instructor: Tim Biblarz Office hours (Kap 352): W, 5 6pm, F, 10 11, and by appointment (213) 740 3547;
More informationAlgebra 1, Quarter 3, Unit 3.1. Line of Best Fit. Overview
Algebra 1, Quarter 3, Unit 3.1 Line of Best Fit Overview Number of instructional days 6 (1 day assessment) (1 day = 45 minutes) Content to be learned Analyze scatter plots and construct the line of best
More informationEducation for an Information Age
Education for an Information Age Teaching in the Computerized Classroom 7th Edition by Bernard John Poole, MSIS University of Pittsburgh at Johnstown Johnstown, PA, USA and Elizabeth Sky-McIlvain, MLS
More informationlearning collegiate assessment]
[ collegiate learning assessment] INSTITUTIONAL REPORT 2005 2006 Kalamazoo College council for aid to education 215 lexington avenue floor 21 new york new york 10016-6023 p 212.217.0700 f 212.661.9766
More informationUser education in libraries
International Journal of Library and Information Science Vol. 1(1) pp. 001-005 June, 2009 Available online http://www.academicjournals.org/ijlis 2009 Academic Journals Review User education in libraries
More informationIndividual Differences & Item Effects: How to test them, & how to test them well
Individual Differences & Item Effects: How to test them, & how to test them well Individual Differences & Item Effects Properties of subjects Cognitive abilities (WM task scores, inhibition) Gender Age
More informationcontent First Introductory book to cover CAPM First to differentiate expected and required returns First to discuss the intrinsic value of stocks
content First Introductory book to cover CAPM First to differentiate expected and required returns First to discuss the intrinsic value of stocks presentation First timelines to explain TVM First financial
More informationMODULE 4 Data Collection and Hypothesis Development. Trainer Outline
MODULE 4 Data Collection and Hypothesis Development Trainer Outline The following trainer guide includes estimated times for each section of the module, an overview of the information to be presented,
More informationAnalysis of Enzyme Kinetic Data
Analysis of Enzyme Kinetic Data To Marilú Analysis of Enzyme Kinetic Data ATHEL CORNISH-BOWDEN Directeur de Recherche Émérite, Centre National de la Recherche Scientifique, Marseilles OXFORD UNIVERSITY
More informationMAHATMA GANDHI KASHI VIDYAPITH Deptt. of Library and Information Science B.Lib. I.Sc. Syllabus
MAHATMA GANDHI KASHI VIDYAPITH Deptt. of Library and Information Science B.Lib. I.Sc. Syllabus The Library and Information Science has the attributes of being a discipline of disciplines. The subject commenced
More informationLesson Plan Art: Painting Techniques
Lesson Plan Art: Painting Techniques Subject Area: Art Grade Level: K-1, Special Education Student Objectives: Students will know the terms texture plates, sponges and salt, and that they add detail to
More informationA Case Study: News Classification Based on Term Frequency
A Case Study: News Classification Based on Term Frequency Petr Kroha Faculty of Computer Science University of Technology 09107 Chemnitz Germany kroha@informatik.tu-chemnitz.de Ricardo Baeza-Yates Center
More informationPSY 1010, General Psychology Course Syllabus. Course Description. Course etextbook. Course Learning Outcomes. Credits.
Course Syllabus Course Description This course is an introductory survey of the principles, theories, and methods of psychology as a basis for the understanding of human behavior and mental processes.
More informationEdexcel GCSE. Statistics 1389 Paper 1H. June Mark Scheme. Statistics Edexcel GCSE
Edexcel GCSE Statistics 1389 Paper 1H June 2007 Mark Scheme Edexcel GCSE Statistics 1389 NOTES ON MARKING PRINCIPLES 1 Types of mark M marks: method marks A marks: accuracy marks B marks: unconditional
More informationCitrine Informatics. The Latest from Citrine. Citrine Informatics. The data analytics platform for the physical world
Citrine Informatics The data analytics platform for the physical world The Latest from Citrine Summit on Data and Analytics for Materials Research 31 October 2016 Our Mission is Simple Add as much value
More informationEDPS 859: Statistical Methods A Peer Review of Teaching Project Benchmark Portfolio
University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln UNL Faculty Course Portfolios Peer Review of Teaching Project 2015 EDPS 859: Statistical Methods A Peer Review of Teaching
More informationHierarchical Linear Modeling with Maximum Likelihood, Restricted Maximum Likelihood, and Fully Bayesian Estimation
A peer-reviewed electronic journal. Copyright is retained by the first or sole author, who grants right of first publication to Practical Assessment, Research & Evaluation. Permission is granted to distribute
More informationModule 12. Machine Learning. Version 2 CSE IIT, Kharagpur
Module 12 Machine Learning 12.1 Instructional Objective The students should understand the concept of learning systems Students should learn about different aspects of a learning system Students should
More informationTHE INFLUENCE OF COOPERATIVE WRITING TECHNIQUE TO TEACH WRITING SKILL VIEWED FROM STUDENTS CREATIVITY
THE INFLUENCE OF COOPERATIVE WRITING TECHNIQUE TO TEACH WRITING SKILL VIEWED FROM STUDENTS CREATIVITY (An Experimental Research at the Fourth Semester of English Department of Slamet Riyadi University,
More informationInternational Series in Operations Research & Management Science
International Series in Operations Research & Management Science Volume 240 Series Editor Camille C. Price Stephen F. Austin State University, TX, USA Associate Series Editor Joe Zhu Worcester Polytechnic
More informationTHE PROMOTION OF SOCIAL AWARENESS
THE PROMOTION OF SOCIAL AWARENESS Powerful Lessons from the Partnership of Developmental Theory and Classroom Practice Robert L. Selman Russell Sage Foundation New York The Russell Sage Foundation The
More informationGreen Belt Curriculum (This workshop can also be conducted on-site, subject to price change and number of participants)
Green Belt Curriculum (This workshop can also be conducted on-site, subject to price change and number of participants) Notes: 1. We use Mini-Tab in this workshop. Mini-tab is available for free trail
More informationHow the Guppy Got its Spots:
This fall I reviewed the Evobeaker labs from Simbiotic Software and considered their potential use for future Evolution 4974 courses. Simbiotic had seven labs available for review. I chose to review the
More informationBPS Information and Digital Literacy Goals
BPS Literacy BPS Literacy Inspiration BPS Literacy goals should lead to Active, Infused, Collaborative, Authentic, Goal Directed, Transformative Learning Experiences Critical Thinking Problem Solving Students
More informationSpring 2014 SYLLABUS Michigan State University STT 430: Probability and Statistics for Engineering
Spring 2014 SYLLABUS Michigan State University STT 430: Probability and Statistics for Engineering Time and Place: MW 3:00-4:20pm, A126 Wells Hall Instructor: Dr. Marianne Huebner Office: A-432 Wells Hall
More informationPractical Research. Planning and Design. Paul D. Leedy. Jeanne Ellis Ormrod. Upper Saddle River, New Jersey Columbus, Ohio
SUB Gfittingen 213 789 981 2001 B 865 Practical Research Planning and Design Paul D. Leedy The American University, Emeritus Jeanne Ellis Ormrod University of New Hampshire Upper Saddle River, New Jersey
More informationGACE Computer Science Assessment Test at a Glance
GACE Computer Science Assessment Test at a Glance Updated May 2017 See the GACE Computer Science Assessment Study Companion for practice questions and preparation resources. Assessment Name Computer Science
More informationBSM 2801, Sport Marketing Course Syllabus. Course Description. Course Textbook. Course Learning Outcomes. Credits.
BSM 2801, Sport Marketing Course Syllabus Course Description Examines the theoretical and practical implications of marketing in the sports industry by presenting a framework to help explain and organize
More informationBusiness 712 Managerial Negotiations Fall 2011 Course Outline. Human Resources and Management Area DeGroote School of Business McMaster University
B712 - Fall 2011-1 of 10 COURSE OBJECTIVE Business 712 Managerial Negotiations Fall 2011 Course Outline Human Resources and Management Area DeGroote School of Business McMaster University The purpose of
More informationDOCTORAL SCHOOL TRAINING AND DEVELOPMENT PROGRAMME
The following resources are currently available: DOCTORAL SCHOOL TRAINING AND DEVELOPMENT PROGRAMME 2016-17 What is the Doctoral School? The main purpose of the Doctoral School is to enhance your experience
More informationKristin Moser. Sherry Woosley, Ph.D. University of Northern Iowa EBI
Kristin Moser University of Northern Iowa Sherry Woosley, Ph.D. EBI "More studies end up filed under "I" for 'Interesting' or gather dust on someone's shelf because we fail to package the results in ways
More informationDiploma in Library and Information Science (Part-Time) - SH220
Diploma in Library and Information Science (Part-Time) - SH220 1. Objectives The Diploma in Library and Information Science programme aims to prepare students for professional work in librarianship. The
More informationAP Statistics Summer Assignment 17-18
AP Statistics Summer Assignment 17-18 Welcome to AP Statistics. This course will be unlike any other math class you have ever taken before! Before taking this course you will need to be competent in basic
More informationShockwheat. Statistics 1, Activity 1
Statistics 1, Activity 1 Shockwheat Students require real experiences with situations involving data and with situations involving chance. They will best learn about these concepts on an intuitive or informal
More informationProbabilistic Latent Semantic Analysis
Probabilistic Latent Semantic Analysis Thomas Hofmann Presentation by Ioannis Pavlopoulos & Andreas Damianou for the course of Data Mining & Exploration 1 Outline Latent Semantic Analysis o Need o Overview
More informationLearning Microsoft Office Excel
A Correlation and Narrative Brief of Learning Microsoft Office Excel 2010 2012 To the Tennessee for Tennessee for TEXTBOOK NARRATIVE FOR THE STATE OF TENNESEE Student Edition with CD-ROM (ISBN: 9780135112106)
More informationIntroduction to Simulation
Introduction to Simulation Spring 2010 Dr. Louis Luangkesorn University of Pittsburgh January 19, 2010 Dr. Louis Luangkesorn ( University of Pittsburgh ) Introduction to Simulation January 19, 2010 1 /
More informationTeaching a Laboratory Section
Chapter 3 Teaching a Laboratory Section Page I. Cooperative Problem Solving Labs in Operation 57 II. Grading the Labs 75 III. Overview of Teaching a Lab Session 79 IV. Outline for Teaching a Lab Session
More informationStatewide Framework Document for:
Statewide Framework Document for: 270301 Standards may be added to this document prior to submission, but may not be removed from the framework to meet state credit equivalency requirements. Performance
More informationMinitab Tutorial (Version 17+)
Minitab Tutorial (Version 17+) Basic Commands and Data Entry Graphical Tools Descriptive Statistics Outline Minitab Basics Basic Commands, Data Entry, and Organization Minitab Project Files (*.MPJ) vs.
More informationAnalyzing sentiments in tweets for Tesla Model 3 using SAS Enterprise Miner and SAS Sentiment Analysis Studio
SCSUG Student Symposium 2016 Analyzing sentiments in tweets for Tesla Model 3 using SAS Enterprise Miner and SAS Sentiment Analysis Studio Praneth Guggilla, Tejaswi Jha, Goutam Chakraborty, Oklahoma State
More informationWHEN THERE IS A mismatch between the acoustic
808 IEEE TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING, VOL. 14, NO. 3, MAY 2006 Optimization of Temporal Filters for Constructing Robust Features in Speech Recognition Jeih-Weih Hung, Member,
More information1 Use complex features of a word processing application to a given brief. 2 Create a complex document. 3 Collaborate on a complex document.
National Unit specification General information Unit code: HA6M 46 Superclass: CD Publication date: May 2016 Source: Scottish Qualifications Authority Version: 02 Unit purpose This Unit is designed to
More informationUsing Calculators for Students in Grades 9-12: Geometry. Re-published with permission from American Institutes for Research
Using Calculators for Students in Grades 9-12: Geometry Re-published with permission from American Institutes for Research Using Calculators for Students in Grades 9-12: Geometry By: Center for Implementing
More informationIntroduction to the Practice of Statistics
Chapter 1: Looking at Data Distributions Introduction to the Practice of Statistics Sixth Edition David S. Moore George P. McCabe Bruce A. Craig Statistics is the science of collecting, organizing and
More informationSoftware Development: Programming Paradigms (SCQF level 8)
Higher National Unit Specification General information Unit code: HL9V 35 Superclass: CB Publication date: May 2017 Source: Scottish Qualifications Authority Version: 01 Unit purpose This unit is intended
More informationWHY SOLVE PROBLEMS? INTERVIEWING COLLEGE FACULTY ABOUT THE LEARNING AND TEACHING OF PROBLEM SOLVING
From Proceedings of Physics Teacher Education Beyond 2000 International Conference, Barcelona, Spain, August 27 to September 1, 2000 WHY SOLVE PROBLEMS? INTERVIEWING COLLEGE FACULTY ABOUT THE LEARNING
More informationMachine Learning and Development Policy
Machine Learning and Development Policy Sendhil Mullainathan (joint papers with Jon Kleinberg, Himabindu Lakkaraju, Jure Leskovec, Jens Ludwig, Ziad Obermeyer) Magic? Hard not to be wowed But what makes
More informationModeling function word errors in DNN-HMM based LVCSR systems
Modeling function word errors in DNN-HMM based LVCSR systems Melvin Jose Johnson Premkumar, Ankur Bapna and Sree Avinash Parchuri Department of Computer Science Department of Electrical Engineering Stanford
More informationMining Association Rules in Student s Assessment Data
www.ijcsi.org 211 Mining Association Rules in Student s Assessment Data Dr. Varun Kumar 1, Anupama Chadha 2 1 Department of Computer Science and Engineering, MVN University Palwal, Haryana, India 2 Anupama
More informationAccounting 380K.6 Accounting and Control in Nonprofit Organizations (#02705) Spring 2013 Professors Michael H. Granof and Gretchen Charrier
Accounting 380K.6 Accounting and Control in Nonprofit Organizations (#02705) Spring 2013 Professors Michael H. Granof and Gretchen Charrier 1. Office: Prof Granof: CBA 4M.246; Prof Charrier: GSB 5.126D
More informationUniversity of Groningen. Systemen, planning, netwerken Bosman, Aart
University of Groningen Systemen, planning, netwerken Bosman, Aart IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document
More informationKentucky s Standards for Teaching and Learning. Kentucky s Learning Goals and Academic Expectations
Kentucky s Standards for Teaching and Learning Included in this section are the: Kentucky s Learning Goals and Academic Expectations Kentucky New Teacher Standards (Note: For your reference, the KDE website
More informationBusiness Analytics and Information Tech COURSE NUMBER: 33:136:494 COURSE TITLE: Data Mining and Business Intelligence
Business Analytics and Information Tech COURSE NUMBER: 33:136:494 COURSE TITLE: Data Mining and Business Intelligence COURSE DESCRIPTION This course presents computing tools and concepts for all stages
More informationMandarin Lexical Tone Recognition: The Gating Paradigm
Kansas Working Papers in Linguistics, Vol. 0 (008), p. 8 Abstract Mandarin Lexical Tone Recognition: The Gating Paradigm Yuwen Lai and Jie Zhang University of Kansas Research on spoken word recognition
More informationUnraveling symbolic number processing and the implications for its association with mathematics. Delphine Sasanguie
Unraveling symbolic number processing and the implications for its association with mathematics Delphine Sasanguie 1. Introduction Mapping hypothesis Innate approximate representation of number (ANS) Symbols
More informationDoctor of Public Health (DrPH) Degree Program Curriculum for the 60 Hour DrPH Behavioral Science and Health Education
College of Pharmacy and Pharmaceutical Sciences Institute of Public Health Doctor of Public Health (DrPH) Degree Program Curriculum for the 60 Hour DrPH Behavioral Science and Health Education Behavioral
More informationCertified Six Sigma Professionals International Certification Courses in Six Sigma Green Belt
Certification Singapore Institute Certified Six Sigma Professionals Certification Courses in Six Sigma Green Belt ly Licensed Course for Process Improvement/ Assurance Managers and Engineers Leading the
More informationFifth Grade Science Inquiry Questions
Fifth Inquiry Free PDF ebook Download: Fifth Inquiry Download or Read Online ebook fifth grade science inquiry questions in PDF Format From The Best User Guide Database Science. Grade-Level Expectations:
More informationFAQ (Frequently Asked Questions)
FAQ (Frequently Asked Questions) Q. How can we contact the DIGITAL EDUCATION PROJECT and the NATIONAL DIGITAL SCHOOLBOOK LIBRARY PROGRAM for additional information and questions? A. VISIT OUR WEBSITE at
More informationApplication of Virtual Instruments (VIs) for an enhanced learning environment
Application of Virtual Instruments (VIs) for an enhanced learning environment Philip Smyth, Dermot Brabazon, Eilish McLoughlin Schools of Mechanical and Physical Sciences Dublin City University Ireland
More informationTHE EFFECTS OF TEACHING THE 7 KEYS OF COMPREHENSION ON COMPREHENSION DEBRA HENGGELER. Submitted to. The Educational Leadership Faculty
7 Keys to Comprehension 1 RUNNING HEAD: 7 Keys to Comprehension THE EFFECTS OF TEACHING THE 7 KEYS OF COMPREHENSION ON COMPREHENSION By DEBRA HENGGELER Submitted to The Educational Leadership Faculty Northwest
More informationDegree Qualification Profiles Intellectual Skills
Degree Qualification Profiles Intellectual Skills Intellectual Skills: These are cross-cutting skills that should transcend disciplinary boundaries. Students need all of these Intellectual Skills to acquire
More informationHuman Emotion Recognition From Speech
RESEARCH ARTICLE OPEN ACCESS Human Emotion Recognition From Speech Miss. Aparna P. Wanare*, Prof. Shankar N. Dandare *(Department of Electronics & Telecommunication Engineering, Sant Gadge Baba Amravati
More informationTesting A Moving Target: How Do We Test Machine Learning Systems? Peter Varhol Technology Strategy Research, USA
Testing A Moving Target: How Do We Test Machine Learning Systems? Peter Varhol Technology Strategy Research, USA Testing a Moving Target How Do We Test Machine Learning Systems? Peter Varhol, Technology
More information