Which Chart Or Graph Is Right for You?
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Chartmaking in England and Its Context, 1500–1660
58 • Chartmaking in England and Its Context, 1500 –1660 Sarah Tyacke Introduction was necessary to challenge the Dutch carrying trade. In this transitional period, charts were an additional tool for The introduction of chartmaking was part of the profes- the navigator, who continued to use his own experience, sionalization of English navigation in this period, but the written notes, rutters, and human pilots when he could making of charts did not emerge inevitably. Mariners dis- acquire them, sometimes by force. Where the navigators trusted them, and their reluctance to use charts at all, of could not obtain up-to-date or even basic chart informa- any sort, continued until at least the 1580s. Before the tion from foreign sources, they had to make charts them- 1530s, chartmaking in any sense does not seem to have selves. Consequently, by the 1590s, a number of ship- been practiced by the English, or indeed the Scots, Irish, masters and other practitioners had begun to make and or Welsh.1 At that time, however, coastal views and plans sell hand-drawn charts in London. in connection with the defense of the country began to be In this chapter the focus is on charts as artifacts and made and, at the same time, measured land surveys were not on navigational methods and instruments.4 We are introduced into England by the Italians and others.2 This lack of domestic production does not mean that charts I acknowledge the assistance of Catherine Delano-Smith, Francis Her- and other navigational aids were unknown, but that they bert, Tony Campbell, Andrew Cook, and Peter Barber, who have kindly commented on the text and provided references and corrections. -
3B – a Guide to Pictograms
3b – A Guide to Pictograms A pictogram involves the use of a symbol in place of a word or statistic. Why would we use a pictogram? Pictograms can be very useful when trying to interpret data. The use of pictures allows the reader to easily see the frequency of a geographical phenomenon without having to always read labels and annotations. They are best used when the aesthetic qualities of the data presentation are more important than the ability to read the data accurately. Pictogram bar charts A normal bar chart can be made using a set of pictures to make up the required bar height. These pictures should be related to the data in question and in some cases it may not be necessary to provide a key or explanation as the pictures themselves will demonstrate the nature of the data inherently. A key may be needed if large numbers are being displayed – this may also mean that ‘half’ sized symbols may need to be used too. This project was funded by the Nuffield Foundation, but the views expressed are those of the authors and not necessarily those of the Foundation. Proportional shapes and symbols Scaling the size of the picture to represent the amount or frequency of something within a data set can be an effective way of visually representing data. The symbol should be representative of the data in question, or if the data does not lend itself to a particular symbol, a simple shape like a circle or square can be equally effective. Proportional symbols can work well with GIS, where the symbols can be placed on different sites on the map to show a geospatial connection to the data. -
1) Key Words 2) Tally Charts 3) Pictograms 4) Block Graph 5) Bar
KS2 1) Key Words 2) Tally Charts 3) Pictograms 4) Block Graph 5) Bar Graphs 6) Pie Charts 7) Grouped Tally Charts (KS2/3 analysis) 8) Grouped Frequency Diagrams 9) Frequency Polygons 10) Line Graphs 11) Scatter Diagrams 12) Cumulative Frequency Diagrams 13) Box Plots 14) Histograms KS4 15) Grouped Tally Charts (KS4 analysis) 16) What Makes A Good Graph * Analysing Data Key words Axes Linear Continuous Median Correlation Origin Plot Data Discrete Scale Frequency x -axis Grouped y -axis Interquartile Title Labels Tally Types of data Discrete data can only take specific values, e.g. siblings, key stage 3 levels, numbers of objects Continuous data can take any value, e.g. height, weight, age, time, etc. Tally Chart A tally chart is used to organise data from a list into a table. The data shows the number of children in each of 30 families. 2, 1, 5, 0, 2, 1, 3, 0, 2, 3, 2, 4, 3, 1, 2, 3, 2, 1, 4, 0, 1, 3, 1, 2, 2, 6, 3, 2, 2, 3 Number of children in a Tally Frequency family 0 1 2 3 4 or more Year 3/4/5/6:- represent data using: lists, tally charts, tables and diagrams Tally Chart This data can now be represented in a Pictogram or a Bar Graph The data shows the number of children in each family. 30 families were studied. Add up the tally Number of children in a Tally Frequency family 0 III 3 1 IIII I 6 2 IIII IIII 10 3 IIII II 7 4 or more IIII 4 Total 30 Check the total is 30 IIII = 5 Year 3/4/5/6:- represent data using: lists, tally charts, tables and diagrams Pictogram This data could be represented by a Pictogram: Number of Tally Frequency -
2021 Garmin & Navionics Cartography Catalog
2021 CARTOGRAPHY CATALOG CONTENTS BlueChart® Coastal Charts �� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 04 LakeVü Inland Maps �� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 06 Canada LakeVü G3 �� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 08 ActiveCaptain® App �� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 09 New Chart Guarantee� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 10 How to Read Your Product ID Code �� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 10 Inland Maps ��������������������������������������������������� 12 Coastal Charts ������������������������������������������������� 16 United States� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 18 Canada ���������������������������������������������������� 24 Caribbean �������������������������������������������������� 26 South America� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 27 Europe����������������������������������������������������� 28 Africa ����������������������������������������������������� 39 Asia ������������������������������������������������������ 40 Australia/New Zealand �� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 42 Pacific Islands �� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � -
1. What Is a Pictogram? 2
Canonbury Home Learning Year 2/3 Maths Steppingstone activity Lesson 5 – 26.06.2020 LO: To interpret and construct simple pictograms Success Criteria: 1. Read the information about pictograms 2. Use the information in the Total column to complete the pictogram 3. Find some containers around your house and experiment with their capacity – talk through the questions with someone you live with 1. What is a pictogram? 2. Complete the pictogram: A pictogram is a chart or graph which uses pictures to represent data. They are set out the same way as a bar chart but use pictures instead of bars. Each picture could represent one item or more than one. Today we will be drawing pictograms where each picture represents one item. 2. Use the tally chart to help you complete the pictogram: Canonbury Home Learning Year 2/3 Maths Lesson 5 – 26.06.2020 LO: To interpret and construct simple pictograms Task: You are going to be drawing pictograms 1-1 Success Criteria: 1. Read the information about pictograms 2. Task 1: Use the information in the table to complete the pictogram 3. Task 2: Use the information in the tally chart and pictogram to complete the missing sections of each Model: 2. 3. 1. What is a pictogram? A pictogram is a chart or graph which uses pictures to represent data. They are set out the same way as a bar chart but use pictures instead of bars. Each picture could represent one item or more than one. Today we will be drawing pictograms where each picture represents one item. -
2. Graphing Distributions
2. Graphing Distributions A. Qualitative Variables B. Quantitative Variables 1. Stem and Leaf Displays 2. Histograms 3. Frequency Polygons 4. Box Plots 5. Bar Charts 6. Line Graphs 7. Dot Plots C. Exercises Graphing data is the first and often most important step in data analysis. In this day of computers, researchers all too often see only the results of complex computer analyses without ever taking a close look at the data themselves. This is all the more unfortunate because computers can create many types of graphs quickly and easily. This chapter covers some classic types of graphs such bar charts that were invented by William Playfair in the 18th century as well as graphs such as box plots invented by John Tukey in the 20th century. 65 by David M. Lane Prerequisites • Chapter 1: Variables Learning Objectives 1. Create a frequency table 2. Determine when pie charts are valuable and when they are not 3. Create and interpret bar charts 4. Identify common graphical mistakes When Apple Computer introduced the iMac computer in August 1998, the company wanted to learn whether the iMac was expanding Apple’s market share. Was the iMac just attracting previous Macintosh owners? Or was it purchased by newcomers to the computer market and by previous Windows users who were switching over? To find out, 500 iMac customers were interviewed. Each customer was categorized as a previous Macintosh owner, a previous Windows owner, or a new computer purchaser. This section examines graphical methods for displaying the results of the interviews. We’ll learn some general lessons about how to graph data that fall into a small number of categories. -
Chapter 16.Tst
Chapter 16 Statistical Quality Control- Prof. Dr. Samir Safi TRUE/FALSE. Write 'T' if the statement is true and 'F' if the statement is false. 1) Statistical process control uses regression and other forecasting tools to help control processes. 1) 2) It is impossible to develop a process that has zero variability. 2) 3) If all of the control points on a control chart lie between the UCL and the LCL, the process is always 3) in control. 4) An x-bar chart would be appropriate to monitor the number of defects in a production lot. 4) 5) The central limit theorem provides the statistical foundation for control charts. 5) 6) If we are tracking quality of performance for a class of students, we should plot the individual 6) grades on an x-bar chart, and the pass/fail result on a p-chart. 7) A p-chart could be used to monitor the average weight of cereal boxes. 7) 8) If we are attempting to control the diameter of bowling bowls, we will find a p-chart to be quite 8) helpful. 9) A c-chart would be appropriate to monitor the number of weld defects on the steel plates of a 9) ship's hull. MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. 1) Which of the following is not a popular definition of quality? 1) A) Quality is fitness for use. B) Quality is the totality of features and characteristics of a product or service that bears on its ability to satisfy stated or implied needs. -
Section 2.2: Bar Charts and Pie Charts
Section 2.2: Bar Charts and Pie Charts 1 Raw Data is Ugly Graphical representations of data always look pretty in newspapers, magazines and books. What you haven’tseen is the blood, sweat and tears that it some- times takes to get those results. http://seatgeek.com/blog/mlb/5-useful-charts-for-baseball-fans-mlb-ticket-prices- by-day-time 1 Google listing for Ru San’sKennesaw location 2 The previous examples are informative graphical displays of data. They all started life as bland data sets. 2 Bar Charts Bar charts are a visual way to organize data. The height or length of a bar rep- resents the number of points of data (frequency distribution) in a particular category. One can also let the bar represent the percentage of data (relative frequency distribution) in a category. Example 1 From (http://vgsales.wikia.com/wiki/Halo) consider the sales …g- ures for Microsoft’s videogame franchise, Halo. Here is the raw data. Year Game Units Sold (in millions) 2001 Halo: Combat Evolved 5.5 2004 Halo 2 8 2007 Halo 3 12.06 2009 Halo Wars 2.54 2009 Halo 3: ODST 6.32 2010 Halo: Reach 9.76 2011 Halo: Combat Evolved Anniversary 2.37 2012 Halo 4 9.52 2014 Halo: The Master Chief Collection 2.61 2015 Halo 5 5 Let’s construct a bar chart based on units sold. Translating frequencies into relative frequencies is an easy process. A rela- tive frequency is the frequency divided by total number of data points. Example 2 Create a relative frequency chart for Halo games. -
Bar Charts and Box Plots Normal Poisson Exponential Creating a Simple Yet Effective Plot Requires an 02468 C 1.0 Exponential Uniform Understanding of Data and Tasks
THIS MONTH a Uniform POINTS OF VIEW Normal Poisson Exponential 02468 b Uniform Bar charts and box plots Normal Poisson Exponential Creating a simple yet effective plot requires an 02468 c 1.0 Exponential Uniform understanding of data and tasks. λ = 1 Min = 5.5 Normal Max = 6.5 0.5 Poisson σμ= 1, = 5 μ = 2 Bar charts and box plots are omnipresent in the scientific literature. 0 02468 They are typically used to visualize quantities associated with a set of Figure 2 | Representation of four distributions with bar charts and box plots. items. Representing the data accurately, however, requires choosing (a) Bar chart showing sample means (n = 1,000) with standard-deviation the appropriate plot according to the nature of the data and the task at error bars. (b) Box plot (n = 1,000) with whiskers extending to ±1.5 × IQR. hand. Bar charts are appropriate for counts, whereas box plots should (c) Probability density functions of the distributions in a and b. λ, rate; be used to represent the characteristics of a distribution. µ, mean; σ, standard deviation. Bar charts encode quantities by length, which is a highly accurate visual encoding and preferred over the angle-based strategy used in to represent such uncertainty. However, because the bars always start pie charts (Fig. 1a). Often the counts that we want to represent are at zero, they can be misleading: for example, part of the range covered sums over multiple categories. There are several options to visualize by the bar might have never been observed in the sample. -
Measurement & Transformations
Chapter 3 Measurement & Transformations 3.1 Measurement Scales: Traditional Classifica- tion Statisticians call an attribute on which observations differ a variable. The type of unit on which a variable is measured is called a scale.Traditionally,statisticians talk of four types of measurement scales: (1) nominal,(2)ordinal,(3)interval, and (4) ratio. 3.1.1 Nominal Scales The word nominal is derived from nomen,theLatinwordforname.Nominal scales merely name differences and are used most often for qualitative variables in which observations are classified into discrete groups. The key attribute for anominalscaleisthatthereisnoinherentquantitativedifferenceamongthe categories. Sex, religion, and race are three classic nominal scales used in the behavioral sciences. Taxonomic categories (rodent, primate, canine) are nomi- nal scales in biology. Variables on a nominal scale are often called categorical variables. For the neuroscientist, the best criterion for determining whether a variable is on a nominal scale is the “plotting” criteria. If you plot a bar chart of, say, means for the groups and order the groups in any way possible without making the graph “stupid,” then the variable is nominal or categorical. For example, were the variable strains of mice, then the order of the means is not material. Hence, “strain” is nominal or categorical. On the other hand, if the groups were 0 mgs, 10mgs, and 15 mgs of active drug, then having a bar chart with 15 mgs first, then 0 mgs, and finally 10 mgs is stupid. Here “milligrams of drug” is not anominalorcategoricalvariable. 1 CHAPTER 3. MEASUREMENT & TRANSFORMATIONS 2 3.1.2 Ordinal Scales Ordinal scales rank-order observations. -
Chapter 6 Presenting Your Data in Graphic Form Political Orientations
UNIVARIATE ANALYSIS Chapter 6 Presenting Your Data in Graphic Form Political Orientations Now let’s turn our attention from religion to politics. Some people feel so strongly about politics that they joke about it being a religion. The General Social Survey distribute(GSS) data set has several items that reflect political issues. Two are key political items: POLVIEWS and PARTYID. These items will be the primary focus in this chapter. In the process of examining these variables, we are going to learn not only more about the politicalor orientations of respon- dents to the 2012 GSS but also how to use SPSS Statistics to produce and interpret data in graphic form. You will recall that in the previous chapter, we focused on a variety of ways of displaying univariate distributions (frequency tables) and summarizing them (measures of central ten- dency and dispersion). In this chapter, we are going to build on that discussion by focusing on several ways of presenting your data graphically. We will begin by focusing on two charts thatpost, are useful for variables at the nominal and ordinal levels: bar charts and pie charts. We will then consider two graphs appropriate for interval/ratio variables: histograms and line charts. Graphing Data With Direct “Legacy” Dialogs SPSS Statistics gives us acopy, variety of ways to present data graphically. Clicking the Graphs option on the menu bar will give you three options for building charts: Chart Builder, Interactive, and Legacy Dialogs. These take you to two chart-building methods developed by SPSS over the past 20 years. Chart Builder is the most recent. -
Visualization
Visualization Computer Graphics II University of Missouri at Columbia Visualization •• “a“a picturepicture sayssays moremore thanthan aa thousandthousand words”words” Computer Graphics II University of Missouri at Columbia Visualization •• “a“a picturepicture sayssays moremore thanthan aa thousandthousand numbers”numbers” Computer Graphics II University of Missouri at Columbia Visualization •• VVisualizationisualization cancan facilitatefacilitate peoplepeople toto betterbetter understandunderstand thethe informationinformation embeddedembedded inin thethe givengiven dataset.dataset. •• TThehe mergemerge ofof datadata withwith thethe displaydisplay geometricgeometric objectsobjects throughthrough computercomputer graphics.graphics. Computer Graphics II University of Missouri at Columbia Data •2•2DD ddaattaasseett –– BBarar chart,chart, piepie chart,chart, graph,graph, stocks.stocks. –– IInformationnformation visualizationvisualization •3•3DD ddaattaasseett –– SScalarcalar datadata –V–Veeccttoorr ddaattaa –T–Teennssoorr ddaattaa Computer Graphics II University of Missouri at Columbia Data •2•2DD ddaattaasseett –– BBarar chart,chart, piepie chart,chart, graph,graph, stocks.stocks. –– IInformationnformation visualizationvisualization •3•3DD ddaattaasseett –– SScalarcalar datadata –V–Veeccttoorr ddaattaa –T–Teennssoorr ddaattaa Computer Graphics II University of Missouri at Columbia Data •2•2DD ddaattaasseett –– BBarar chart,chart, piepie chart,chart, graph,graph, stocks.stocks. –– IInformationnformation visualizationvisualization •3•3DD