OTHER CHARTS AVAILABLE FROM GOOGLE CHARTS Traditional Graphs Diagrams Area Charts (Traditional and Stepped) Bubble Charts Bar Charts Box and Whisker Plots (Candlestick Charts) Column Charts Calendar Charts Combo Charts Gauge Charts Histograms Geographic Charts Intervals Organizational Charts Line Charts Tables Pie Charts Timelines Scatter Charts Tree Map Charts Time Series (Annotated) Word Trees Trend lines **User created community charts are also available**
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Woodland Paper Company Example 6.4 In the Woodland Paper Company’s final step in their paper production process, the paper passes through a machine that measures various product quality characteristics. When the paper production process is in control, it averages 20 defects per roll. a) Set up a control chart for the number of defects per roll. Use twosigma control limits. b) Five rolls had the following number of defects: 16, 21, 17, 22, and 24, respectively. The sixth roll, using pulp from a different supplier, had 5 defects. Is the paper production process in control? c = 20 z=3 © 2007 Pearson Education UCLc = c+3 c = 20 + 3 20 = 33.42 LCLc = c−3 c = 20 - 3 20 = 6.58
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Control Charts Process Parameter Sample Statistic Process average  Sample average Process variability σ Sample range or R, or sample standard deviation S R-chart S-chart Process proportion defective p Sample proportion defectives (P) P-chart Process defects per unit (c) Sample defects per unit (C) C-chart 03/22/2019 rd Name of Chart X X -chart 8
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XP Create 3-D charts • To create a 3-D chart, you may choose to do so during the first step of the Chart Wizard, as three-dimensional charts are sub-types of most other charts, such as the pie chart. • To change a chart to a 3-D chart, select the chart, click Chart on the menu bar, and then click Chart Type. • Choose the 3-D option sub-type of whichever chart type you prefer. • There are also several 3-D charts on the Custom Types tab of the Chart Type dialog box. ‫ﴀ‬New Perspectives on Microsoft Office 2003, Premium Edition Excel Tutorial 4 26
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Samples for the Proteomics Experiment Tissue 1 2 3 4 Treatment Group 1. Before Senescence A 2. After Senescence B 1. Before Senescence C 2. After Senescence D 1. Before Senescence E 2. After Senescence F 1. Before Senescence G 2. After Senescence H Switchgrass Clone # 5 (Early Senescence) Switchgrass Clone # 4 (Late Senescence) Prairie Cordgrass-ND (Early Senescence) Prairie Cordgrass-SD (Late Senescence) Sample# Sample# 1 Sample# 2 Sample# 3 Sample# 4 Sample# 5 Sample# 6 Sample# 7 Sample# 8 Sample# 9 Sample# 10 Sample# 11 Sample# 12 Sample# 13 Sample# 14 Sample# 15 Sample# 16 Sample# 17 Sample# 18 Sample# 19 Sample# 20 Sample# 21 Sample# 22 Sample# 23 Sample# 24
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What Really Happened in May of 2006?  Wednesday, May 10th: Larry Hoyle posts the PROC SQL Sudoku solver on SAS-L, gets a flurry of responses. –  Several responses, and new Sudokuoriented threads, followed – David Cassell (again!): “I think you and Larry have a paper for SUGI 32/SGF 1 !” 5 posts on Wednesday, more later Constraint programming, no optimization necessary  Seeing Larry’s solver inspired me to try to learn PROC CLP to write a Sudoku solver. – One variable per square, with actual range of possible values {1,…,9} – One constraint for each of the 27 conditions, e.g.: ALLDIFF (value1 – value9); – Initial configuration strung together by commas in a LINCON statement. Wednesday, April 18th, 2007 Thursday, May 11th: I post the PROC CLP Sudoku solver on SAS-L. – Around the same time, I found out about PROC CLP. –    I tested the PROC CLP solver on a few puzzles, one took more than a half hour to solve; only then did I decide to bite the bullet and produce the LP solution. Friday, May 12th: I post a cleaner version of the PROC CLP Sudoku solver, and a first version of the PROC LP Sudoku solver on SAS-L. – Same day, John Gerlach announces his solver. – One week later, DeVenezia joins the fray. Applications Development Section 011-2007 Katz: SAS/OR 67
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Woodland Paper Company Using a c-Chart to monitor a process Example 6.4 Number of Defects Solver - c-Charts Sample Number © 2007 Pearson Education
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Chart Types • • • • • • • • • Column and Bar Charts Stacked Column or Bar Chart Clustered column or Bar Chart Line Charts X-Y Scatter Charts Bubble Charts Heat Map Graphical Information Systems Textbook & Authors finally reflect the truth: • Pie charts are not as effective as column/bar charts • 3-D charts (not bubble charts) are “Chart Junk” 22
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Estimating Defects 3 Developer Example Three developers in an inspection identified 10 unique defects (# from 1 to 10). Harry found defects 1, 2, 3, 4 & 5 Chapin found defects 1, 2, 4, 6 & 7 Sue found defects 4, 6, 7, 8, 9 & 10 Estimate total # of defects in product prior to inspection. Estimate total inspection yield. Sue identified the most unique defects (3) = 6 identified Combine Harry’s & Chapin’s defects = 7 identified, 3 in common w/ Sue Total Product Defects = 6 * 7 / 3 = 14 Yield % = 100 * 10/14 = 71% 6/19/2007 SE 652- 2007_06_19_Overview_Inspections.ppt 21
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MORE CHARTS TYPES Stacked Column Chart 100% Stacked Column Chart 3-D Column Chart Bar Chart Line Chart Area Chart X Y (Scatter) Chart Stock Chart Surface Chart Doughnut Chart Bubble Chart Radar Chart 8
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Code Reviews While there are many aspects to software quality, one particularly important emphasis is on the eliminationIfof defects. Rationale: the software doesn’t work right, other quality issues are irrelevant. How can defects be effectively eliminated? Since low defect content is best achieved where the defects are injected,• remove software engineers should: their own defects • determine the causes of their defects • learn to prevent those When should the defects be defects eliminated? Rather than waiting until late in the development process (i.e., during testing, when locating and correcting defects is difficult and expensive), modern processes advocate CS 325 eliminating defects during Lesson Fifteen code review (and possibly even Modeling and Design of Rule-Based Systems
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s l o o T . V . D D3 Data-Driven-Documents Library Chart Types Interactivity Events Customization Expressivity Rendering Method D3.js DataDrivenDocuments No charts out-ofthe box Defined by developer on selected elements using JS event handling functions All aspects are customizable by developer using library methods, CSS, and pure JavaScript JavaScript, CSS & HTM5/SVG Google Charts API 12 core chart types plus 16 more Out-of-box tooltips with additional event handling through JS event handling functions Ready to use out-ofthe-box. Customizations available through an options object. Some specific to each chart, others generic JavaScript, HTML5/SVG, VML for older IE browsers such as IE8 Google Charts Charts.js Charts.js 9 core chart types out-of-the-box tooltips and standard JS events passed into an options object as a string[] Customization available on major chart components such as colors, fonts, layout, legend, and ToolTips JavaScript HTML5/ Canvas HTML 5 / SVG cto e V ble a l a Sc hics p Gra HTML5 Ra s te r r
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Creating Charts XP • A chart, or graph, is a visual representation of a set of data • Select the data source with the range of data you want to chart • In the Charts group on the Insert tab, click a chart type, and then click a chart subtype in the Chart gallery • In the Location group on the Chart Tools Design tab, click the Move Chart button to place the chart in a chart sheet or embed it into a worksheet New Perspectives on Microsoft Office Excel 2007 4
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XP Modify 3-D chart options • A 3-D chart has several options for modifying the 3-D effect. – Perspective is the illusion that parts of the 3-D chart that are farther away from you decrease in size – Elevation is the illusion that you are looking at the 3-D chart from some particular height—either above or below the chart – You may also rotate the 3-D chart to bring different parts of the chart to the forefront • • • Elevation and rotation are options that you can change with the 3-D View dialog box, available from the Chart menu. Excel creates each 3-D chart with a default elevation, rotation and height. To change the appearance of a 3-D chart once you have created one, make sure it is an active chart then click Chart on the menu bar and then click 3-D View. ‫ﴀ‬New Perspectives on Microsoft Office 2003, Premium Edition Excel Tutorial 4 27
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Measurement Data & Metrics Base Metrics # & Type of Defects found (major, minor) For each defect, who found # of pages inspected, preparation time (per inspector), inspection time Measures Preparation rate = # pages / average preparation time Inspection rate = # pages / inspection time Inspection defect rate = # major defects / inspection time Defect density = # estimated defects / # of pages Inspection yield = # defects / # estimated defects (individual & team) SRS Phase Defect Containment (%) = 100% * # Defects removed @ step / ( Incoming defects + Injected defects) 6/12/2007 2007_06_12_Rqmts.ppt 28
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Measurement Data & Metrics Base Metrics # & Type of Defects found (major, minor) For each defect, who found # of pages inspected, preparation time (per inspector), inspection time Measures Preparation rate = # pages / average preparation time Inspection rate = # pages / inspection time Inspection defect rate = # major defects / inspection time Defect density = # estimated defects / # of pages Inspection yield = # defects / # estimated defects (individual & team) SRS Phase Defect Containment (%) = 100% * # Defects removed @ step / ( Incoming defects + Injected defects) 6/19/2007 SE 652- 2007_06_19_Overview_Inspections.ppt 17
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