Keep It Simple... Use A Supertable

Introduction

Tables, charts, and graphs are common elements of research and Extension papers. Without them, written expository exercises will be devoid of visual tools that help convey a message to the audience. In particular, tables and graphs facilitate value comparisons, help discern trends, and indicate the magnitude or lack of differences between and/or among test variables when used in conjunction with statistical analysis. One type of table, called a supertable, overcomes the need for many tables and/or graphs while presenting many comparisons in common, easily understood dimensions. The same structure that renders supertables larger than ordinary tables also makes it easy to get the message across to the intended audience without overwhelming them. This paper demonstrates the design and construction of a supertable for a typical Extension survey.

Since 1992, the Texas Agricultural Extension Service has been participating in the 4-H Wildlife and Fisheries School Enrichment Program by developing modules administered to selected schools throughout the state. One module entitled "Wildlife Success Stories and Endangered Species," seeks to teach elementary students about wildlife conservation and management. Module components include a large, freestanding display, videotape, lesson plans for classroom activities, and testing materials (Higginbotham, 1992). The module also features an interactive computer program making use of video, animation, text and sounds to educate the school children on wildlife issues.

A ten question pre-test survey, coupled with inquiries about gender, ethnicity, and school demographics, was administered prior to the module's arrival on each school's campus. Data collected from the pre-test established benchmark knowledge, demographics, and counts of students who responded to the survey.

Two days following exposure to the educational module, the same set of students were tested again using a 10-question post-test. When reckoned against their corresponding scores in pre-test, post-test measures students' gain in knowledge on the subject. County Extension agents helped administer the tests. Survey forms were processed at the Extension Data Center of the Texas Agricultural Extension Service, Texas A&M University at College Station.

The notion that tables or graphs should only convey "few" dominant ideas has been considered to be the golden rule of presentation. Seemingly oblivious to such principle, Tufte (1983) developed the idea of supertables, which he defined as a type of elaborate table with an organized, sequential detail and reference-like quality. A supertable is a concentrated table with numerous row variables (Gravely, 1998). In brief, supertables make use of tabular columns as posting places for categorized topics unified into one or few dominant themes ("dimensions"). Rows are treated as containers for classification variables ("paragraph headings") with the familiar titles such as age, gender, and other variables of interest to the audience. Unlike any other tables, supertables require that row variables be arranged in a logical sequence akin to a book's chronological chapters developing into a story.

PROC TABULATE procedure in SAS was used to produce the supertable printout. Other statistical software such as SPSS (R) and Statgraphics (R) may also have similar procedure that can produce the same output. The pre-test and post-test was designated as columnar topics with percent respondent counts as the unifying dimension across two tests. Gender, ethnicity, schools, and the 5-questionnaire variables served as the row or "paragraph" headings. It is for expediency that only frequencies from five out of the ten questionnaires in the survey were included in the table. In practice, additional dimensions and classification variables can be added to the table to give a good coverage to a subject of interest. Once the rough supertable was generated, a plain text editor was used to refine it by putting a separator line between "paragraphs" and deleting rows flagged by SAS to contain missing data. Separator lines distinctly identify one data "paragraph" from another while increasing the readability of the final table. Note that the deletion of rows with missing data caused some percentage values to fall short of 100% when subtotaled.

The refined supertable is shown in Table 1. Values within the supertable represent percentage counts of respondents broken down into demographic and wildlife questionnaire sections spanning across the two tests. Two characteristics of displayed values are noticeable in this table: (a) values within a class variable were arranged in decreasing order (high to low) of magnitude, and (b) class variables were logically arranged such that the table starts from a specific variable (such as gender) on top and then to a more general one (such as ethnicity) towards the middle part. Effectiveness of these two structural strategies increases with increasing number of variables. Both of them facilitate the perception and identification of data trends and make for easy comparison between extreme values (for example, high vs. low) in adjacent columns or rows of the same variable.

Overall, the objective of the supertable is to provide logically ordered numerical and/or textual values that would support any espoused finding or to answer a research question (Is the wildlife module effective?) using the least number of possible dimension (percent count). Indeed, there are advantages to using supertables. By employing many sequentially arranged class variables that addressed the different aspects of the subject matter, a supertable progressively offers easily comprehensible, bite-sized pieces of information to the intended audience without overwhelming them.

When used alone, a supertable minimizes the introduction of extraneous data and redundant statistics, a feat not easily accomplished when many small tables, charts, and/or graphs are used to prove a point. Despite all its virtues, the effectiveness of supertables depends mostly on when and how one uses them. The power and simplicity of supertables can best be harnessed when use in typical project reports, briefings, summaries, and overhead transparencies commonly used in Extension programming. However, one drawback to its use is that it cannot be adapted as a content material for developing slide presentations due to its large size.

Gravely, A.R. (1998). Your guide to survey research using the SAS system. Cary, NC: SAS Institute, Inc.

Higginbotham, B. (1995). Wildlife success stories and endangered species: A 4-H school enrichment program. Progress Report. College Station: Texas Agricultural Extension Service.

Tufte, E.R. (1983). The visual display of quantitative information. Cheshire, CN.. Graphics Press.

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