The Vintage of Reports
The interpretation of data changes the outcome.

source: Mr. KABC, talk show host, Los Angeles, February 19, 1999
"You will admire the table and diagram extremely. They have been made out with extreme care, and all the indices most minutely and scrupulously attended to."

--Letter to Charles Babbage from Ada Augusta Lovelace (daughter of Lord Byron and first female programmer) (Scientific American, May, 1999, p. 81)


I am indebted to former and current students for many of the ideas for this web site.

William Playfair Starts the Effort

You start thinking about charts and graphs by realizing how far we have come in our development of the subject. Charts and graphs are not new; they don't go back to their origin after World War II. It is true these visuals received a tremendous impetus after the War. What we need to consider is the debt we owe the Scots.

We already owe the Scots the debt of Adam Smith, the famous economist. We also owe a debt to the physicians and doctors who pushed the boundaries of medicine. We owe a debt to Robert Burns, the famous Scottish poet. Still, we probably little consider William Playfair. Consider this: William Playfair worked as a draftsman and clerk for James Watt, inventor of the steam engine. In 1822-23 Playfair wrote "the king (Louis XVI)understood the charts and was highly pleased." The King liked geographic atlases, and Playfair's book was among his treasures. You have to remember that William Playfair was also a rogue and a possible embezzler. He dabbled in what we call today insider trading in France. Regardless, King Louis recognized his contributions as Playfair phrased in his writings: "He said they spoke all languages and were very clear and easily understood (Playfair, 1822-23)." (William Playfair, Howard Wainer, Ian Spence, The Commercial and Political Atlas and Statistical Breviary, Cambridge University Press, 2005, p. 1)

Our purpose in spending so much time with Playfair is to recognize his contributions to the development of graphics. Without Playfair we wouldn't have the idea of line charts, bar charts, and pie charts. In the days before copiers and printouts William Playfair constructed graphics that stand the test of time.

In the last few months I was privileged to find original works of Playfair called The Commercial and Political Atlas and Statistical Breviary. Statistical data, until Playfair, had never been presented in pictorial form (Playfair, Wainer, Spence, p. 2). Sure, we have hieroglypics from the ancient Egyptians and Roman arches, but those are not bar and pie charts. Playfair believed that graphs convey comparative information. The American historian of statistics, H. G. Funkhouser, believed that graphic method represents a universal language (Playfair, Wainer, Spence, p. 2). That was what Playfair was doing, conveying a universal language of graphics. Remember William came from an illustrious family in Scorland. His father was a Presbyterian minister, and his brother John, a physicist, mathematician, and geologist, became one of the most distinguished professors at the University of Edinburgh (Playfair, Wainer, Spence, p. 3).

At an early age brother John asked William to keep graphical records of daily temperatures--and guess what--William acknowledged that experience as his inspiration for time series charts (Playfair, Wainer, Spence, p. 3). Before you leave the subject of William Playfair, don't forget that William probably personally engraved the lines of the line charts he produced about comparative products between countries (Playfair, Wainer, Spence, p. 13).

You Need a Starting Point

Suppose you face a dilemma about where to begin with your tables and charts. You have been asked to look for significant data. What are significant data? Look for questions where the answers will make the point in your report. Let's say you have written the following question on your survey: "Do you experience regularly scheduled meetings (weekly, monthly, and so forth)?" This question would make a good table of data. You could place columns for the "Yes," "No," and "No opinion" responses and the numbers of managers, assistant managers, and office employees who answered in each case. The numbers could be placed in rows. Your horizontal labels will become the types of respondents, such as managers. Now, you have the beginnings of a table. You took one important question and made it into a table.

One of my students sharply saw what could become a table. He asked a question about number of semesters students attended at a particular institution. He then set up columns for 1-2, 3-4, and 5-6 and so forth for the number of semesters. He created a banner head for Semesters. Then, in the section for Stub Head he placed the paraphrased question. He tallied the number of responses across for each semester. This report writer had the beginnings of an excellent table.

Tables Present Their Own Concerns

Tables present their own dilemma. What is a table? A table is an arrangement of rows and columns. Tables can be quantitative with mostly numbers. Tables can be qualitative with mostly words. You distinguish a table from a chart by having representations of geometric shapes (lines, pies, bars, flows) and the visual representation of data. Tables deal with raw data. You usually have columns for percentages, descriptive statistics, or dollars. You can tell it is a table by the structure. You look at column after column of information. You read across with row after row of information.

Edward Tufte Provides All the Criteria We Need

In 2003 I had the privilege of hearing Dr. Edward Tufte, former professor of statistics and political science, at Yale. Tufte (pronounced Tough-ee) is known for three major books in data analysis: The Visual Display of Quantitative Information, Envisioning Information, and Visual Explanations. Each of these books took approximately seven years to write and was self-published. The first book has already been recognized as one of the leading books of the 20th Century.

Tufte provides unique ways of looking at his three books. The first book involves the picturing of numbers. The second book deals with nouns. That means Tufte names charts, tables, and visualizations. In the third book Tufte is concerned with verbs. Verbs, in this case mean process, causality, and dynamics. You see pictures of verbs.

What struck me as so useful for our classes is the quality of Tufte's criteria for viewing data. Tufte likened the initial criteria to viewing Euclid's Geometry as a first translation in Ben Jonson's original library in England. Tufte thinks we should look at all dimensions of a visualization (chart, table, whatever) as he expressed these criteria:

  1. Principle 1: Show data comparisons.

    Note: First, does the visual have at least two data comparisons? What are they, and how important are they? How do you know? Are the data being compared worth being compared? How do you know?

  2. Principle 2: Show causality (learning about the evidence).
  3. Principle 3: Show more than one or two variables (capturing multivariate complexity).

    Discussion: Whenever you hear a Tufte seminar you will be immediately introduced to the Minard line chart (surface chart) of Napoleon's Retreat from Moscow during the European War of 1812. When you look at the masterful description, you will note six variables. Minard has calculated the number of troops lost during certain miles of the retreat. Minard provided all the temperatures at certain locations through Russia and Poland that affected the troops. To paraphrase Tufte, Minard captured a multivariate analysis.

  4. Principle 4: Completely integrate word, number, and image.

    You are interested in an intellectual architecture. You should supplement page after page of text with appropriate graphics.

  5. Principle 5: Always show documentation, including footnotes.

    Discussion: People have to trust your data. People want to know where you found the information. The problem of missing data can create less trust. Your documentation adds to your quality control.

  6. Principle 6: Get better content (quality, relevance, integrity of your content).

    Discussion: You cannot risk poor content when you present data. If your numbers are not sufficient, get better numbers. You don't want Chartjunk. It is interesting that nowhere on Minard's surface chart does Napoleon's name appear. The chart was meant to honor the fallen Frenchmen who fought for Napoleon.

  7. Principle 7: Try to show information adjacent in space (rather than stacked in time).

    Discussion: If you ever looked at Galileo's (Earth moved around the Sun) original drawings of sunspots, you would see immediately what Tufte meant by "adjacent in space." If we took a special effect mechanism and ran through each sighting of sunspots, we notice immediately that spacing of the sunspots catches our eyes. It was if we had a time-lapse photography of all Galileo's sunspot observations. Contrast that image with the computer screen with too many applications as icons stacked in time. The eye becomes weary.

  8. Principle 8: Use small multiples (easy on your viewers).

    Discussion: Bar charts, for example, act as information architecture. With small multiples on these charts we can demonstrate mastery of detail. As you know, I always ask you to label the axes, both horizontal and vertical. You may need a legend. By labeling every appropriate multiple, you do not run the risk of someone accusing you of evidence selection. You need to understand the credibility of the information.

    Selection of Charts Requires Sharp Analysis

    You have to make a selection first about whether you will use a pie, bar, line, surface, or flowchart. Once that decision has been made and you have determined the chart's purpose, you are ready to choose a question from your survey or interview guide. You should not choose too much data for the chart presentation.

    A student was recently faced with an interview guide. What questions were most important to present what the apartment complex should do to increase tenancy? The student had to examine his problem question as well as his purpose. Eventually, the student decided that the use of media recommended by the tenants and the manager might be the most important information to present. The student could use a horizontal bar chart (bar chart) to present the data with the vertical axis showing the different media and the horizontal axis showing the number of respondents for each kind of media. Here's how the student arrived at all these decisions:

    Choosing Charts Causes Concern

    In the latest Style Guide for Business and Technical Communication from Franklin-Covey, a well-known scheduling book and time management company providing seminar services, the issue of which chart for which occasion occurred. You may also recognize Covey as the author of several books on Effective Habits for individuals and families. The book is devoted to all kind of business communication situations, but the chart section of the reference was particularly strong. We can classify certain charts as to their uses. First, the pie charts are considered:

    Advantages and Disadvantages
    Comparison and Contrast
    Decisions and Alternatives
    This list suggests you should consider a pie chart when you are expressing the previous items. For example, 100 percent of some costs might necessitate a pie chart. You could also use a line chart, depending on your preference and what you wanted to show.

    You could compare or contrast certain slices of the pie and percentages. Think of an example, such as percentage cost to run each department of a retail store. You comparison and contrast works well in that case.

    For line chart selection you have a number of alternatives. The uses include:

    Decisions and Alternatives
    Comparison and Contrasts
    Chronology particularly interested me in this list. You see all the time the chronology of certain stock transactions in the newspaper. You see the history of the stock as well as the ups and downs of the market prices. Can you think of a line chart that would show decisions and alternatives?

    Pie Charts Can Tell a Good Tale

    One semester a student did a fascinating report on store tastings for a particular chain store. I did not know anything about store tastings. Apparently, store tastings occur when the employees are asked to sample different beverages or other merchandise before the product is made available to the public. According to the student, a store tasting "provides a time set aside for employees to either sample new products entering the store, or items that have not been sampled before to help increase familiarity about the products." Therefore, the student was interested in presenting data about whether employees engaged in a free for all by taking a free lunch instead of tasting the products. Out of that desire to present grew a pie chart.

    As we remember a pie chart, you need to have 100 percent of something. You usually deal with percentages in a pie chart. You try to avoid more than six segments or slices in the pie for readability. The student presented data about attitudes toward the store tastings. The student calculated the percentages of responses for three major categories: (1)Store Tastings Are a Free for All; (2)Store Tastings Are Sometimes a Free for All; and (3)Store Tastings Are Not a Free for All. The student discovered that the largest percentages occurred in the first two categories. Even though the student only had 13 respondents or employees, the percentages made the point quickly. That is what you must do with your chart selected. Make your point quickly.

    Explanation Tie-In Requires Analysis

    In the newly revised analytical report memo you are asked to provide an explanation tie-in for the table and figure. You are technically writing part of the Considerations section of the memo. You are doing more than saying the table and chart contain data. Your explanation in paragraph memo form with captions means you tell the significance of the numbers. You talk about percentages and averages. Your work will probably encompass close to a page of single-spaced keyboarding. You don't have to report every single number. However, you do not let the table or chart speak for themselves.

    Actual Paragraphs Show Handling of Tie-In

    I suspect it would be helpful to see some actual paragraphs from a report and how the student handled part of the Considerations. In the report you are seeing the student surveying elementary school youngsters about their languages used and homework help obtained. You see one of the paragraphs called the explanation tie-in:

    Attachment B, Table 1, describes people helping the sample students with their homework. The results show that 12 students (46 percent), the largest number, do not obtain assistance with their homework by any member of their home. They do homework by themselves. Five students (15 percent) are assisted by a third relative (aunt, uncle, or cousin). Three students (12 percent) obtain help from their siblings (brothers, sisters, or both).

    In the second illustration we see explanation tie-in for charts, especially a pie chart. The student is trying to find out how to improve training in an investment banking firm. We will call the firm HEI. In the pie chart the student report writer had given the statistics of Strongly familiar (one slice), 23 percent, and Somewhat familiar (another slice or segment), 31 percent. From this pie chart the student wrote the following as part of the Considerations:

    Figure 1 (Attachment B) presents a graphic display of the answers given to the HEI operations question. Out of the 13 people surveyed, only seven respondents (54 percent) were able to state they had some familiarity with HEI. The survey further revealed that some employees are not even aware that other key agencies in the settlement process exist.

    Think about: Did you spot that 54 percent was arrived at by adding 23 and 31 percents respectively? It is always wise to combine numbers where appropriate in pie and horizontal bar charts. If we looked at the rest of the pie chart, we would see Just get-by, 23 percent, and Don't know, 23 percent. Did you notice the writer did not have to repeat the question to present the data? The report writer simply stated the "HEI operations question" and let the reader refer to the Attachments for more information about the exact wording of the question.

    Exercise: Draw the chart you have just read about.

    Tables and Charts Create Their Own Problems

    In the analytical report we place, for the most part, the tables and charts in the Attachments. Each table has its own table number and table title written this way:

    TABLE 1

    For charts you should use the Figure number and the Figure title. The figure title must be a talking caption. The figure number and figure title must be centered over the visual. Let's take an example:

    FIGURE 1

    What you do in a figure is find some piece of data that stands out. That might be a pie chart, a line chart, or a bar chart. You make that piece of data your title. You avoid saying some of the following phrases:


    These previous, vague titles do not let the reader know what is going on. You need to have your caption "talk" to the reader.

    Look Out for Quantitative and Qualitative Data

    Tables require columnar presentation of data. Often, selecting specific questions or a whole range of interview of questionnaire questions will give you the data for a table. You may even build a quantitative data table from the interviews. You simply conceive the categories and place in the data in some workable fashion with the columns and rows. For example, columns for advantages and disadvantages of some particular plan may be a helpful way to present the qualitative data, categories you conceived from open-ended questions..

    Qualitative Data Present Choices

    Perhaps an actual example of a student facing a dilemma with presenting data will further explain the use of qualitative data. The student's report originally dealt with cash flow and advertising's impact. He interviewed two major department heads, including the customer service representative who gave him superb data about suggested solutions to the cash flow problem. The student did not have quantitative data; he had two interviews. Then, a light bulb dawned in the student's mind. Why couldn't he set up vertical columns headed "Department," "Problem," and "Suggested Solution"?

    The student made choices. He knew management would appreciate a capsule form of the data shown in a qualitative data table. The customer representative provided particularly good data for presenting in the table. The student could place "n=2" after the title in the table. In quantitative tables, such as numbers and percentages, you may want to provide each question on the left side of the table. You may shorten or paraphrase the question to accommodate the space. Then, your columns can be numbers, percentages, and total. Never forget to include a total column.

    Don't forget that every table and figure should have "n=25 or number of respondents" placed in parentheses immediately after the table title. You need to clarify how many people responded. The reader should not be left to guess how many percentages or have to calculate the appropriate statistics.

    Chart Assignment Aids Growth (Makeup)

    In class we looked at five different problems and the charts that would satisfy each situation. You are asked to first say whether the chart should be component, item, time series, frequency distribution, or correlation. Use these exact words in explaining the chart. Then, rough out the chart by labeling Y and X axis and a title for each chart. Remember to use different kinds of plot lines for correlation (if appropriate) than for a horizontal bar chart. The exercises now follow:

    1. Sales are forecast to increase over the next 10 years.
    2. The largest number of employees earns between $30,000 and $35,000.
    3. In September, the turnover rates for the six divisions were about the same.
    4. The sales manager spends only 15 percent of the time in the field.
    5. Size of merit increases is not related to tenure.
    6. Region C ranks last in productivity.

    Tables and Charts Assignment Needs Clarification

    Certain students over the semester have asked about the tables and charts assignment with the Tufte criteria. I have chosen selected paragraphs from previous students' memos to talk about clarification:

    Quantitative Table Needs Investigation

    The table shows heads for the rows and columns. The figures given are in percentages and in dollars in the first item in each column. Percentages are given for the first column and dollar signs for the next two columns. The title clearly states the main point. The graphic shows chronological order from 4.25% to 8.25%. It compares different interest rates, monthly payments and total costs. A source is shown at the bottom of the graphic. The research was performed by Times Research.

    The table shows exact figures, and serves its purpose. However, the table needs a line between interest rate and monthly payment.

    Think about: You are doing content thinking, not analysis thinking. We don't care what the table shows. We are interested in Tufte's principles.

    What evidence is shown through footnotes and text that suggest you can trust the data?

    In this case I looked at three variables, interest rate, monthly payment, and total cost. How clearly were those variables presented? Can you find the information you need to discover? How?

    Principle 4 talks about integration of number, image, and word. As you look at the table, how effectively were those three elements integrated into the visual? How do you know? Give some specifics.

    Think about: What kind of data comparisons are shown? Are the figures arranged in such a way that a clear presentation is given?

    Think about: How could better content be achieved in the table or the graph?

    Principle 8 talks about ease of reading. How clear were the numbers or the figures in understanding the visual? Did you find the table or the chart appealing to the eye? How do you know? Give some specific examples.

    We Drown in Numbers

    Charles Osgood, now narrator of Sunday Morning on CBS, featured a special Osgood File about how we are drowning in numbers. We have license permit numbers and PIN numbers. Osgood asks us if we are tired of numbers. We have social security numbers and tax numbers. Numbers define and locate us. You have an access code. You have area codes and telephone numbers to remember. You have so many numbers to remember.

    Charles Gibson Presents New Orleans Numbers Simply

    Let's say you are looking at the evening news one day on the TV--even though college students don't have time for TV. You note the newly hired anchor for ABC News, Charles Gibson. He is explaining why many residents and evacuees from New Orleans have not returned from various cities around the United States. How does one show that graphically? Here's what Gibson did. He visually took the huge telephone directory and yellow pages from New Orleans before Hurricane Katrina. He placed those books on a table before the viewer. Then, he contrasted the telephone directory now (half the size and white pages packed with yellow)to prove his point about whether evacuees had returned. That dramatic and simple illustration in front of the camera brought home the problem. Sure, Gibson used props, but he visually described the dilemma. Simplicity was the key, and he made his point with graphics.

    Memo Example Helps Clarify Assignment

    A number of students have asked for an example of the memo evaluating tables and charts. As you look at this example, please realize it is not perfect. Further, I will add certain Notes after certain paragraphs to clarify what I think the reader is doing. Let's try this example:

    To:		Dr. G. Jay Christensen
    From:		Gustave Gomez
    Date:		Current
    Visuals Receive Attention
    This memo is written to critique and analyze two tables and two charts.  Table 
    1 in Attachment A presents a qualitative explanation of seven various types of 
    automotive fuel cells.  Table 2 in Attachment B contains a breakdown of the top
    ten box office earners.  All elements of the daily weather of North America are 
    illustrated in Attachment C.  Attachment D  is a bar chart demonstrating the
    costs associated with ownership of a Mercedes-Benz E65 AMG. Each of these 
    illustrations attempts to conquer the difficult task of clearly presenting 
    an explanation through a chart or table. 
    Illustrations Show Comparison
    Qualitative Table 1 (Attachment A)presents various data being compared.  This 
    table sufficiently compares data by comparing and explaining five facets of 
    seven various options.  Advantages are provided alongside disadvantages in a 
    non-biased manner. The table clearly and understandably compares the data found 
    within the research.  The creator of the table successfully transfers 
    understanding of the topic onto the reader.  Table 2 (Attachment B)also provides 
    data comparisons on an array of important information.  The data shown in the 
    table cover every bit of information a reader would expect to see in such a   
    table.  The illustration fairly and adequately compares various objective details 
    of the films.  Figure 1 (Attachment C) also properly shows ample data 
    comparison for the reader. The chart contains multiple legends and explanations  
    necessary for this type of chart.  Without the graphic assistance the average  
    reader would not be able to comprehend the chart and, therefore, miss the 
    purpose.  Figure 2 (Attachment D)includes data comparison as well as the other  
    three but with less data to compare. Illustrations A, B, and C completed a higher  
    task of data comparison because of the excessive amount of information given 
    in each.  
    Note:  The writer could have helped the reader by putting information about the 
    intended purpose of each table and chart.  What did the writer or the preparer 
    Figures Boast Causality
    All four figures allow a reader to easily learn about the presented evidence.  
    Table 1 (Attachment A)provides clear column headings to complement the data 
    given within the table.  This method further improves the chance a reader will 
    have of understanding the point of the table.  This explanation allows the reader 
    to learn about the evidence uncovered during the research and testing of the  
    subjects.  The setup of Table 2 (Attachment B)creates a similar effect.  
    Attachment C allows the reader to understand the daily weather.  This allowance 
    is made possible by the previously mentioned legend.  The legend enhances the 
    reader's understanding of the illustration.  The reading of Figure 1 
    (Attachment C) is quite simple.  This simplicity of the chart allows the 
    reader an opportunity to easily learn the presented evidence.
    Dr. G. Jay Christensen
    Page 2
    Current Date 
    Multiple Variables Require Appearance
    A seemingly infinite number of variables exist in Table 1 (Attachment A). The 
    headings for each column allow a wide array of data responses as entered data.  
    The use of multiple variables in this chart guarantees a complete explanation 
    of the subject.  Attachment B also addresses a number of important variables.  
    Each of the included variables builds on the next.  This system of variables 
    helps the reader understand the flow and significance of the variables on one 
    another. Many variables are also included in Figure 1 (Attachment C).  The data 
    in this type of chart vary from one area to another.  Each presented variable 
    is necessary to construct a complete chart.  Each of the variables is 
    accompanied by an explanation to inform the reader of the reason for the 
    variable's presence.  The simplicity of Attachment D is obtained as a direct   
    result of the low number of variables.  An excessive number of variables in 
    this chart would only cause confusion and defeat the purpose. Only a few  
    variables are necessary to understand the few items that need to be examined 
    in this bar chart.
    Note:  As I read over the previous paragraph, I am left with questions.  Why is
    there so much that the visual preparer had to include as variables?  Did you 
    notice the sentences became a little long with so many prepositions? 
    Understanding Demands Integration
    The flow of the variables in Attachment A results in beautiful integration.  
    The data from one area relate directly to the data in the next.  The structure of 
    Table 2 (Attachment B) immediately forms an understanding of the topic in the 
    reader's head.  Each column of data relates to the next column to the right. 
    This pattern stays consistent within the entire table.  Attachment C is 
    flawlessly drawn. The reader can credit understanding of this chart to the 
    creator's integration of words, images, and explanations.  Various colors are 
    used to assist in conveying the information to the reader.  Figure 2 
    Attachment D)contains text to explain the expressed data entries.  Integration of 
    of the data is not too difficult in this case because of the minimal variables.
    Note:  The writer has made a sincere attempt to use words that convey meaning.  You
    can tell the person has studied the visuals.  The Tufte criterion is applied, 
    and the use of color is also mentioned.  That brings up a point.  Make sure your 
    table or chart appears in its original color.  Color is important in trying to 
    convey meaning. Also, take the time to explain the charts rather than let them 
    speak for themselves.  
    Documentation Provides Support
    Table 1 (Attachment A)is supported with extensive text and research.  A large
    amount of research was performed over the span of a few decades before the data
    were entered into this table.  The data in Attachment B is taken from another
    source.  This source is cited at the bottom of the table.  To form a table such 
    as this one, the original source must already have a system in place to gather
    the extensive amount of data.  Data were retrieved from thousands of 
    significant sources to present the data in this table.  The validity of the 
    data given in Figure 1 (Attachment C)depends on the technology used to gather   
    it. The more advanced the weather tracking device, the more accurate the data.  
    The exact sources for the construction of the data in Attachment D are given.  
    Mathematical calculations are used to obtain the data in this type of chart.  
    Some variables within the calculations are estimated or assumed.  As a result, 
    the information provided is only as accurate as the assumptions used to obtain 
    Dr. G. Jay Christensen
    Page 3
    Current Date  
    Chartjunk Decreases Value
    One column appearing in Table 1 (Attachment A) provides a unique, but trivial 
    facts.  These facts disrupt the flow of the chart more than they contribute. 
    The vague relevance of the added facts may cause a reader to lose focus of 
    the table's main points.  The breakdown of data in Table 2 (Attachment B)
    ensures the reader will only read quality, relevant information.  Unnecessary
    information are not given to obstruct the view of the table's reader.  Impor-
    tant and relevant data are all that are provided in this table.  Though only 
    a small portion of the data may be relevant to reader of Figure 1 (Attachment
    C), it must all be provided to cover the majority of the possible readers.
    Again, the quality of the data depends on the quality of the research tools
    used to gather the data.  Figure 2 (Attachment D) uses assumptions to figure
    the data entered.  The integrity and quality of the data depend on the accuracy
    of these assumptions.  The creator of this chart could easily sway the numbers
    one way or the other by manipulating the original assumptions.
    Note:  As I originally commented on the paper, "Much better analysis."  The 
    writer is starting to go on a tangent, however, with the discussions about 
    assumptions and accuracy.  One has to be careful in this kind of the table "not to 
    ramble."  Say what you have to say, and stop.  
    Information Stacking Breeds Confusion
    Tables 1 and 2 (Attachments A and B)insert data into distinct boxes, all of 
    which are the same size.  The uniformity of the tables increases the ease of 
    reading them.  Figure 1 (Attachment C)mixes much of the data together.  This 
    mixing of the data creates difficulty in the reader's understanding.  To 
    interpret the data given within this chart, a reader would need much more time to 
    separate the data and anlyze what exactly is going on.  The data provided in 
    Figure 2(Attachment D) is shown adjacent in space.  This setup permits easier 
    comprehension by the reader. 
    Number Size Plays Important Part
    Qualitative Table 1 (Attachment A)does not provide any information in numerical
    form.  Table 2 (Attachment B), on the other side, was forced to deal with 
    large numbers.  To break the numbers down for ease of comparison, the table
    expresses large aounts in smaller figures.  This breakdown is communicated to
    the reader at the top of the column.  "Millions" is stated in parentheses.  
    This labeling is a common method used to solve the problem of large multiples.  The
    numbers contained within Figure 1 (Attachment C)are broken into a scale.  The
    scale had to be wide enough to cover the entire temperature spectrum, and in
    intervals small enough to render the chart useful.  The numerical multiples used
    in Figure 2 (Attachment D)work sufficiently well for the purpose of illus-
    tration. Precise detail is not necessary for this graph to be successful in its 
    Dr. G. Jay Christensen
    Page 4
    Current Date  
    Tables and Charts Need Examining
    Many details of a chart or table must be examined before one can accept the 
    contents as valid.  Specific layouts may intentionally or non-intentionally 
    confuse a reader.  The maker of a table may use certain setups to purposefully
    lead the reader to interpret the chart in a specific way.  Written the wrong  
    way, an illustration may sway a reader in the wrong direction for the creator.  
    All of these details must be considered before one should believe the contents 
    of any table or chart.
    Attachments:  A.  Table 1, ". . . ."
                  B.  Table 2, ". . . . "
                  C.  Figure 1, ". . . ."
                  D.  Figure 2, ". . . . ."
                  Own Criteria Questions for Tables 
                  Own Criteria Questions for Charts
    Note:  Did you spot the writer needed a way to end the memo?  The writer chose to 
    comment on the importance of visuals and their place of interpretation.  The
    writer drew from class lectures and readings how important tables and charts 
    have become.  You must have some kind of summary paragraph.

    Zelazny Still Has the Last Word

    Is the day coming when we will talk in our language only in digits? Will the keypad replace the keyboard? What will the conversation of the future sound like? The computer has achieved the triumph of numbers. These questions are worth pondering. I am indebted to Gene Zelazny for the previous problems as explained in his Say It with Charts. If you ever want to look at this excellent reference, you will probably find the book on library reserve.

    Zelazny is famous for how he classifies the kind of charts to use:

There you have the five ways to classify major charts and their uses. Zelazny makes the classification easy, because the five elements are memorable.

Carson Varner Opens Our Eyes to the Statistical Myths

A while back when I went to the International Convention of the Association for Business Communication, a special session occurred on the program devoted to "Lurking Statistics and Legends." The gentleman who gave the presentation from Illinois was a professor in the College of Business as well as an attorney-at-law. He proved his point throughout the presentation that it pays to check sources and the kinds of data presented everywhere. With his permission I have selected portions of his handout to get at the truth.

Dr. Varner is fond of the expression, "Plausible Impossible." That refers to the Looney Tunes character still on TV, Wyle E. Coyote, who is always after the Roadrunner. Wyle, in pursuit of that bird, always seems to fall off a cliff or some precipice, and we as the viewers are not totally accepting of his plight. It is wishful thinking Wyle will survive. Usually, it is a fast descent with no hope in sight. We walk off the cliff because we are sure whether to accept the statistics.

What I like about Dr. Varner is his ability to check out the data. If he needs to write the Federal Reserve about some statistic, he writes them.

Let's now take one of Dr. Varner's examples, Credit Card Woes. We usually hear (don't we?) the average American household has about $8,000 to $9,000 in outstanding credit card debt. First, we have to define "credit card debt." That means revolving debt. As Dr. Varner phrases it, that does not include mortgages or payments on automobiles of similar consumer debt. We include common credit cards as well as department and store charges. Dr. Varner believes we are led to think most Americans are in desperate straits.

The clincher comes now. Dr. Varner's research turned up the following data:

With those statistics to lull us into thinking straight, only half the population even has outstanding debt. Then, Dr. Varner hits us between the eyes with these implausible points:

"If the average of all households is say, $8,000, but half have zero, then the outstanding debt of the remainder doubles to $16,000. Now, if we assume a fair number of households has some convenient outstanding balances of a few hundred or a thousand dollars, then that means a huge portion of Americans has in excess of $2,000 in credit card debt on top of mortgage, car payments, and what not."

How confused are you so far? Dr. Varner begins to conclude that the average credit card debt borders around $1,800 to $2,000, much lower than originally mentioned. No one knows the true figure. The surveys to determine $8,000 of debt were done by telephone. "Each person was asked how much credit card debt the individual had at that moment." Do people answering on the telephone really know their oustanding debt? Also, people may minimize the figures to make themselves look good. The Federal Reserve acknowledges the unreliability of the data. "The Federal Reserve measures revolving debt outstanding at any moment." "That revolving debt includes business credit card debt. It is not separated from personal debt. The debt is only measured at a given moment." These days items, such as airline miles and gift certificates, get put on credit cards. The Federal Reserve has admitted they don't know the exact consumer debt, but they have a published figure.

What conclusions can we derive from this explanation of information? First, be skeptical about the figures you read in newspapers, magazines, and books. Think, and, if necessary, write to the sources to check the figures if you need the data. Find out what a particular article means by an "average." Is it a mean or a median or something else? Expect numbers to be inflated, and find out what the true numbers are. By this skepticism you will go a long way toward appreciating the value and the limitations of statistics.

MAKEUP FOR WEEK 10-11 a.m. Class and 11-12 as well as TTH 3:30 p.m.

You have three sets of questions to answer. The questions are based on the notes and the videotape, Show Me the Data. Before answering the questions keyboarded on a separate sheet of paper, you may want to ponder the wording of each question.

  1. Why are the Considerations (Findings)in a report a story you should tell?
  2. Look at the sentences on pp. 107-108 in the Syllabus. How do those sentences convey an immediacy to the data?
  3. Find three sentences on pp. 107-108 and keyboard them completely. Make sure the sentences convey or possess significance of the data. Significance of data means an appeal to the reader, not the writer.


Go to Guffey and read pp. 423-24 about cross-tabulation. Then, return to pp. 457-58 and do Exercise 13.1 (b and c). Complete your work by answering Number 6 and 13 on p. 457 under "Chapter Review." Turn in all of this work.


Consider the following issue: What are the differences between quantitative and qualitative data? Rough out a table where you explain some qualitative data from interviews. Be sure to label the column, banner, and stub headings. Be as creative as you can.

Excel Charting Becomes Possible with Raw Data

Based on two sets of data from at least two business communication classes, I can now give you some raw figures to place on an Excel worksheet and prepare a chart or charts based on some of the data. For those wanting to make up work missed in a lab, the data are now available for you to make up the work. The data consist of two different classes that answered a series of 12 questions about Classroom Civility for Students and for Instructors. For your code you need the following: Uncivil--U; Moderately Uncivil--Mu; and Civil--C.

Now, you need to take the following data for both Student and Instructor Behavior and arrange in a table with banner heads, stub heads, and column heads. Then, charts can be developed on a separate worksheet for presenting certain, selected data. Note on the Instructor data I have not repeated the entire question; you need to do that on your worksheet.

When you set up your columns for your table, don't forget the admonition about a long table title stressing the 5 W's (Who-What-Where-When-Why) and a table number (e.g. TABLE 1) all centered over the cells where you are preparing the data.

11 a.m. Business Communication Class--Student Behavior Note: n=35

Question 1. arriving late to class: U--10; MU--22; and C--3

Question 2. letting cell phone ring in class: U--17; MU--14; and C--4

Question 3. leaving class early: U--5; MU--23; and C--4

Question 4. belittling a student: U--23; MU--1; and C--11

Question 5. making sarcastic remarks/gestures: U--18; Mu--9; and C--8

Question 6. dominating the discussion: U--6; MU--13; and C--16

Question 7. eating in class: U--9; MU--17; and C--9

Question 8. having side conversations in class: U--16; MU--17; and C--2

Question 9. acting bored or apathetic: U--13; MU--19; and C--3

Question 10. making hostile or vulgar comments: U--24; MU--3; and C--8

Question 11. not paying attention in class: U--19; MU--13; and C--3

Question 12. coming to class unprepared: U--20; MU--12; and C--3

11 a.m. Business Communication Class--Instructor Behavior

Question 1. U--14; MU--9; and C--12

Question 2. U--16; MU--8; and C--11

Question 3. U--7; MU--15; and C--13

Question 4. U--26; C--9

Question 5. U--19; MU--8; and C--8

Question 6. U--6; MU--13; and C--16

Question 7. U--9; MU--13; and C--13

Question 8. U--16; MU--6; and C--13

Question 9. U--25; MU--1; and C--9

Question 10. U--23; MU--2; and C--10

Question 11. U--22; MU--2; and C--11

Question 12. U--21; MU--7; and C--7

Business Communications Class 12 noon--Student Behavior (n=18)

Question 1. arriving late to class: U--6; MU--10; and C--2

Question 2. letting cell phone ring in class: U--15; MU--2; and C--1

Question 3. leaving class early: U--5; MU--11; and C--2

Question 4. belittling a student: U--14; MU--3; and C--1

Question 5. making sarcastic remarks/gestures: U--10; MU--7; and C--1

Question 6. dominating the discussion: U--2; MU--8; and C--8

Question 7. eating in class: U--5; MU--12; and C--1

Question 8. having side conversations in class: U--12; MU--6

Question 9. acting bored or apathetic: U--6; MU--10; and C--2

Question 10. making hostile or vulgar comments: U--17; C--1

Question 11. not paying attention in class: U--5; MU--10; and C--3

Question 12. coming to class unprepared: U--5; MU--12; and C--1

Business Communications 12 noon--Instructor Behavior

Question 1. U--10; MU--17; and C--1

Question 2. U--13; MU--4; and C--1

Question 3. U--3; MU--8; and C--7

Question 4. U--14; MU--3; and C--1

Question 5. U--10; MU--7; and C--1

Question 6. U--1; MU--5; and C--12

Question 7. U--10; MU--7; and C--1

Question 8. U--6; MU--8; and C--3; Blank--1

Question 9. U--16; MU--1; and C--1
Question 10. U--16; MU--1; and C--1

Question 11. U--16; MU--1; and C--1

Question 12. U--14; MU--3; and C--1

Last updated Thursday, August 31, 2006.

(c)G. Jay Christensen, All Rights Reserved

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