Fuzzy Traffic Light Method A Presentation by William Silvert, Ph. D. Lisbon, Portugal.

Slides:



Advertisements
Similar presentations
Data Display: Tables and Graphs
Advertisements

Microsoft ® Office Excel ® 2003 Training How to create a chart.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved. Lecture Slides Elementary Statistics Eleventh Edition and the Triola.
Note 3 of 5E Statistics with Economics and Business Applications Chapter 2 Describing Sets of Data Descriptive Statistics - Tables and Graphs.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved.Copyright © 2010 Pearson Education Section 2-3 Histograms.
Reading Graphs and Charts are more attractive and easy to understand than tables enable the reader to ‘see’ patterns in the data are easy to use for comparisons.
FUZZY SET THEORY ABBY YINGER. DEFINITIONS WHAT IS A FUZZY SET? Definition: A fuzzy set is any set that allows its members to have different grades of.
Handling Data Pie Charts Data (numbers) can be shown much more clearly using charts and graphs.
Traffic Light Thinking G.A.T.E. Thinking Strategy.
Statistics-MAT 150 Chapter 2 Descriptive Statistics
Fuzzy Traffic Light Methods by W. Silvert, IPIMAR, Portugal and P. Fanning, R. Halliday, and R. Mohn DFO, Canada.
Section 3.2 ~ Picturing Distributions of Data
MAL-001 – BAR GRAPHS AND PIE CHARTS.
CHAPTER 1: Picturing Distributions with Graphs
Intro to Graphs Vocab and Categorical Data. Distributions What is a distribution? The distribution of a variable tells us what values the variable takes.
OCR Functional Skills Charts Presenting data – Good data presentation skills are important. – Poor graphs and tables lead to the wrong conclusions being.
Are the results valid? Was the validity of the included studies appraised?
Copyright © 2010 SAS Institute Inc. All rights reserved. Effective Data Visualization Design for Dashboards Lisa Whitman TriUPA May 25, 2011.
NSW Curriculum and Learning Innovation Centre Tinker with Tinker Plots Elaine Watkins, Senior Curriculum Officer, Numeracy.
3. Data Presentation Graphs & Charts.
© Copyright McGraw-Hill CHAPTER 2 Frequency Distributions and Graphs.
Data Presentation.
Understanding and Interpreting maps
The Diminishing Rhinoceros & the Crescive Cow Exploring, Organizing, and Describing, Qualitative Data.
1 12/3/03 Math warm-up Draw an example of each a line graph, bar graph, and a circle graph. (without exact numbers) Label it. When would you use a line.
Graphs Graphs are used to display data. They visually represent relationships between data. All graphs should have a title that identifies the variables.
Copyright © Cengage Learning. All rights reserved. 2 Descriptive Analysis and Presentation of Single-Variable Data.
Dr. Asawer A. Alwasiti.  Chapter one: Introduction  Chapter two: Frequency Distribution  Chapter Three: Measures of Central Tendency  Chapter Four:
1 MATB344 Applied Statistics Chapter 1 Describing Data with Graphs.
1 Chapter 3 Looking at Data: Distributions Introduction 3.1 Displaying Distributions with Graphs Chapter Three Looking At Data: Distributions.
Chapter 3 Data Visualization 1. Introduction Data visualization involves: Creating a summary table for the data. Generating charts to help interpret,
Chapter 2 Graphs, Charts, and Tables - Describing Your Data ©
Ch 4 Graphs Main topic-How can you appropriately display data.
Line Graphs A line graph is a way to summarize how two pieces of information are related and how they vary depending on one another. The numbers along.
Copyright © 2014 Pearson Education. All rights reserved Picturing Distributions of Data LEARNING GOAL Be able to create and interpret basic.
Ministry of Education and Science of the Republic of Kazakhstan Bologna Process and Academic Mobility Center Astana, 2013 Seidakhmetova R. Director of.
Career planning Key ideas to help you with advice and guidance for pupils.
Lecture 03 Dr. MUMTAZ AHMED MTH 161: Introduction To Statistics.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. Section 2-2 Frequency Distributions.
Dr. Serhat Eren Other Uses for Bar Charts Bar charts are used to display data for different categories where the data are some kind of quantitative.
11 To call into question Questioning of a statement or fact Demand for justification or explanation Challenge.
Lecture PowerPoint Slides Basic Practice of Statistics 7 th Edition.
Tables and Graphing Chapter 2 Section 3. Tables Tables- these display information in rows and columns so that it is easier to read and understand. Many.
Hmmmmm..Pie!. WALT understand and interpret pie charts.
© Copyright McGraw-Hill CHAPTER 2 Frequency Distributions and Graphs.
Scientific Investigation. Terms Problem – The question Materials – A list of everything you need Hypothesis – Your guess at the answer to the problem.
CONFIDENTIAL Data Visualization Katelina Boykova 15 October 2015.
Presenting Data.
Class 11, October 8, 2015 Lessons 2.4 & 2.5.  By the end of this lesson, you should understand: ◦ The scale on graphs can change the perception of the.
Presenting Data in Charts, Graphs and Tables #1-8-1.
April 6,  Refine our understanding of ELA  Engage with student exemplars and rubrics and designing constructive feedback  Plan – put knowledge.
MIS 420: Data Visualization, Representation, and Presentation Content adapted from Chapter 2 and 3 of
1-2 Scientific Inquiry How do scientists investigate the natural world? What role do models, theories, and laws play in science?
PowerPoint Etiquette What works in the world of presentations…color, fonts, and transitions.
Copyright © 2009 Pearson Education, Inc. 3.2 Picturing Distributions of Data LEARNING GOAL Be able to create and interpret basic bar graphs, dotplots,
 Line Graphs: are used to show something changing over time.  Bar Graphs: are used to show a comparison between two or more variables.  Pie Chart:
Survey Training Pack Session 20 – Presentation of Findings.
The Diminishing Rhinoceros & the Crescive Cow
Level of Representation
Elementary Applied Statistics
© T Madas.
Descriptive Statistics
Chapter Two Organizing and Summarizing Data
GRAPHING Notes for Review.
Introduction to Probability and Statistics Thirteenth Edition
Which graph should I use?
Presenting Data in Tables
Collecting, Presenting, and Interpreting Data.
GCSE Statistics Misleading Diagrams.
Standard Grade Graphic Communication KI Q1
Presentation transcript:

Fuzzy Traffic Light Method A Presentation by William Silvert, Ph. D. Lisbon, Portugal

Standard Traffic Lights n Each Indicator is represented by a single traffic light, red, yellow or green. n There is no smooth transition, just two sharp lines separating red-yellow and yellow-green. n The meaning of the lights can be very sensitive to the location of these cuts.

Criteria for Improvement The objective is to develop a more general approach with the following characteristics: n Resolution n Uncertainty n Weighting

Resolution n The most serious problem with the standard traffic light method is the way that the lights change discontinuously when the Indicators change smoothly. n There is general agreement that there must be a more gradual representation of the significance of changing indicators.

Uncertainty n A less obvious point, but one which is clearly relevant to fisheries management, is the need to represent the degree of uncertainty in the interpretation of Indicators, and to provide a mechanism for expressing conflicting evidence or interpretation.

Weighting It is also clear that not all Indicators are equally significant. They can be: n Of varying accuracy n Of different relevance n Of dubious value n New and untested

Alternative Approaches n Most alternatives to the standard traffic light method use some sort of averaging to show that an Indicator is on the border between red and yellow or between yellow and green. n One example is using intermediate colours, such as orange between red and yellow.

Fuzzy Traffic Lights n Fuzzy Sets offer one way to improve the standard traffic light method. n With fuzzy traffic lights an Indicator can correspond to more than one light. n For example, instead of using orange to show that an Indicator is on the red- yellow boundary, we can simply show both red and yellow lights.

Advantages of Fuzzy n Fuzzy traffic lights are continuous, we can switch between colours gradually to achieve higher resolution. n Fuzzy traffic lights show uncertainty if we illuminate several lights at once. n Fuzzy traffic lights can be weighted to show relative importance of indicators.

Memberships n The key idea behind Fuzzy Set Theory is that something can belong to more than one set at a time. n When we say that a light is red, that means that it belongs to the set “red”. n With fuzzy sets we can have a light be 50% in set red and 50% in yellow.

Displaying Fuzzy Lights n There are several ways to show a fuzzy traffic light: n Bubble charts, which look a lot like real traffic lights n Pie charts, which display information more quantitatively n Stacked bar graphs, which are less familiar but very effective

Bubble Charts n A Bubble Chart looks like a regular traffic light, but the sizes of the ”lights” are proportional to the membership in each of the three sets, red yellow & green.

Pie Charts n A pie chart looks less like a traffic light, but it gives a more quantitative picture of how much of each light is lit, n The area of each slice represents the fuzzy membership.

Stacked Bar Graphs n A stacked bar graph is somewhat like a traffic light with rectangular bulbs. n The area of each part of the bar represents the membership in the corresponding set.

Choosing the Display n The bubble chart resembles traffic lights most, but it does not give a good sense of the quantitative information about memberships. n The pie chart and the stacked bar graph both represent the relative memberships clearly.

Displaying Weighting n The bubble graph does not give a good idea of the relative weights of the different Indicators. n By varying the diameter of the pie charts or the width of the bar graphs we can show the relative importance of different indicators.

Comparison of Pie Charts

Comparison of Bar Graphs