Data Presentation

• Primary Purpose of Data Presentation : communicate information about the data to the user 
• (1) Textual Presentation

  • describing data by the use of statements with few numbers
  • presented in paragraphs or sentences
  • explain results and trends, and provide contextual information
  • Purpose: to stress or emphasize significant information
• • Advantages of Textual Presentation:
  • gives emphasis to significant data
  • use for few data
• • Disadvantages of Textual Presentation:
  • data becomes incomprehensive when large quantitative data are included in paragraph
  • paragraph involving many figures can be tiresome to most readers when same words are repeated many times
• (2) Tabular Presentation 

  • data are converted into words or numbers in rows and columns
  • Note: data should never be put in a table if it can be described in 1-2 sentences
• • Consideration in table construction:
  • Simplicity
  • Clarity 
  • Directness
• • Purposes of Tabular Presentation:
  • data checking and editing
  • summarizing and presenting data
  • basis, aid in graph or chart construction
• • Guidelines of Tabular Presentation:
  • self-explanatory
  • all sources are specified
  • headings are specific and understandable for every column & row
  • row and column totals are checked for accuracy
  • cells are not left blank; enter “0” or “-”
  • categories are mutually exclusive and exhaustive
• (2.1) Master Table 

  • single table which allows the distribution of observations across many variables of interest in a given study
  • each observation is cross classified across the variables which may be quantitative or qualitative data
  • Purpose : 
  • store information with an aim of presenting detailed statistical data
  • facilitate generation and tabulation of smaller table
• (2.2) Dummy Table 

  • complete except for data
  • give preview of what table outputs may be expected from the study
  • Purpose:
  • help researcher clarify instrument
  • help protocol reviewer & computer programmer
• Tables by number of variables presented : 

  1. One-way table (1 variable) 
  2. Two-way table (2 variable) 
  3. Multi-way Table (3 or more Variable) 
• • Advantages of Tabular Presentation:
  • easy to understand
  • compact and concise than textual form
  • presents greater detail of data than graph
  • readily points out trends, comparisons and interrelations
  • facilitates analysis of categories of given variable
• • Disadvantages of Tabular Presentation:
  • too many rows and columns could make it difficult for the reader to understand the data
  • requires more time to construct
• (3) Graphical Presentation 

  • pictorial representations of certain quantities plotted with reference to a set of axes
  • graphs simplify complex information by using images and emphasizing data patterns or trends
  • useful for summarizing, explaining, or exploring quantitative data
  • present both large and small amounts of data
• • Uses of Graphical Presentation
  • visually summarize the variables (data set is large)
  • emphasize particular statement about data set
  • enhance readability
  • appeal the visual memory
• • Guidelines of Graphical Presentation:
  • include, below the figure, a title providing all relevant information
  • be referred to as figures in the text
  • identify figure axes by the variables under analysis
  • quote the source which provided the data, if required
  • demonstrate the scale being used
  • be self-explanatory
• (3.1) Pie Chart 

  • circles subdivided into a number of slices
  • area of each slice represents the relative proportion data points falling into given category
  • use to show how a whole is divided into its component parts which could be breakdowns of groups or totals
• (3.2) Bar graph

  • consists of bars of the same sizes
  • horizontal or vertical with gaps between to emphasize discontinuities
  • also known as one dimensional diagram
  • Types:
  • simple bar graph (horizontal, vertical) 
  • multiple bar graph (component) 
  • height of bars/rectangles: quantity of variables
• • Guidelines of Bar Graph:
  • height of bars should be proportional to the frequencies or rates of categories
  • width of bars should be equal
  • percentages & rates must be used when total number of observations for the groups are not uniform
  • when percentages are used, the sum of the heights of all the bars must be equal to 100%
  • to make them more appealing, bars are either colored or shaded in different ways
• • Horizontal - used for qualitative variables 
  • Vertical - used for discrete quantitative variables 
• • Component bar graph
  • each bar is divided into smaller rectangles representing the parts
  • area of each smaller rectangle is proportional to the relative contribution of the component to the whole
  • generally used for nominal data
  • different shades or colors can be applied to the components to emphasize differences between parts of the whole
  • preferable over the pie in situations where the compositions of two or more groups are to be compared
• (3.3) Line graph

  • plot of dots joined with lines over some period of time in sequential series
  • Time Series chart
  • horizontal axis: time series
  • vertical axis: variable values
• (3.4) Histogram

  • bar is used to depict number or relative frequencies of data points falling into the given class
  • bars are drawn over the true limits of the classes, no gaps exist in between
  • horizontal axis: continuous quantitative
  • vertical axis: number of relative frequencies
  • preferred for grouped interval data
• (3.5) Frequency polygon

  • similar to histogram except that:
  • frequencies are plotted against the corresponding midpoints of the classes
  • adjacent points are joined with lines and the plot is tied down to the horizontal axis resulting in multi-sided polygon
• (3.6) Stem-and-leaf plot

  • primarily for small set of data
  • provides rank-ordered lists and its easier to restore the original value of the observation
  • lines gives more information than bars in histogram
  • sed to show the actual data value instead of using bars to represent the height of an interval
• (3.7) Box Plot

  • shows description of a large quantitative data
  • include center, spread, shape, tail length, and outlying data points
  • can be presented horizontal or vertical
  • height of rectangle is arbitrary and has no specific meaning
  • used for comparing the distributions of several variables or the distribution of a single variable in several groups on the same scale
• (3.8) Scatter Plot

  • shows the relationship between two quantitative variables
  • gives rough estimate of the type and degree of correlation between the variables
• • Advantages of Graphical Presentation:
  • main feature & implications of the body of data can be grasped at a glance
  • more attractive & appealing to a wider range of readers
  • simplifies concepts that would otherwise have been expressed in so many words
  • shows trends & patterns of a large set of data
  • comparisons could be made more striking
  • can be readily clarify data
• • Disadvantages of Graphical Presentation:
  • cannot show as many sets of facts
  • can only show approximate values
  • require more time to construct
  • may be used to misinterpret results