5 data processing and presentation

Data Processing

the series of actions taken to prepare raw data into meaningful information. According to Rosner (2010), data must be edited, coded, classified, tabulated, and presented before any statistical analysis is performed

Data Processing

A systematic procedure to ensure that the information/data gathered are complete,

consistent and suitable for data analysis

a “necessary" Step before data analysis

data encoding
data editing

major activities in data processing

Data encoding

Conversion Of verbal/written information into

numbers (or other symbols) which can be

more easily encoded, counted and tabulated

Example: “1” for Male and “2” for Female; “0” for No and “1” for Yes

data encoding

Permits rapid of data

Helps to avoid errors in encoding data

Sometimes necessary so that the statistical software can perform various analyses on the data

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number of codes must be kept to a minimum preferably less than _

codes should be exhaustive and mutually exclusive

adopt coding convention for questions with similar answers

Coding manual

A coding manual is a document which

contains a record of all codes assigned to

the responses to all questions in the data

collection forms

Variable name

Variable description

Coding instruction

Minimum information that must be contained in a coding manual:

Variable name

has to be as short

as possible since computer

software usually allow a limited

number of characters

Variable description

a description of the variable in the

coding manual to make it easier

for those who will be analyzing

and writing the final report to

identify which variables are being

taken under consideration

Coding instruction

actual codes to be used

data encoding

Entering of data/answers in a spreadsheet

Some computer programs for encoding

o MS Excel

o MS Access

o Epi Info

DATA EDITING

• Inspection and correction of any errors or

inconsistencies in the information collected

• Editing occurs during data collection, encoding

and prior to analysis

Data presentation

is the process of transforming

processed data into a clear, concise, and meaningful

format—allowing the audience to see and understand the

story behind the numbers.

clarity
accuracy
simplicity
relevance
aesthetic appeal

qualities of food data presentation

NARRATIVE OR TEXTUAL PRESENTATION

o Simply presents data in a narrative form

or story-fashion

o Uses statements with few numbers,

highlighting significant data

Advantage: Appropriate "hen there are

few figures to be presented

Disadvantage: Paragraph Wolving many

figures can be tiresome to most readers

when the same words are repeated

several times

TABULAR METHOD

o Systematic arrangement of values that

groups data into rows and columns

o Example: Frequencies of morbidity rates,

Hospital admission and discharge data

o Basis for graphs and charts, where some

details may be lost.

table number

title

column heading or box head

row headings or stubs

body

footnotes

source of data

parts of a table

table number

should be written in Arabic numerals on the same line as the title, separated by a period, and placed at the beginning of the title.

title

should be a brief but complete statement that clearly relates to the table’s content, providing information on what, who, where, and when. The first letter of the first word, as well as all proper nouns and adjectives, should be capitalized. A headnote may be added only when necessary to clarify details not explained in the title.

column heading or box head

should be concise but clearly describe the data they represent. Proper spacing between headings must be observed; if there are no vertical lines, at least two spaces should separate them. Each column caption should be wide enough to match the maximum width of the figures in that column.

row headings or stubs

should be grouped to facilitate interpretation. They indicate the basis of classification for the rows or horizontal series of figures.

body

is composed of cells, which are the intersections of rows and columns, and may be single or double. Figures within the cells of a particular column should be aligned by their decimal points, and consistency in the number of decimal places must be maintained. For example, 4.5, 7, 2.5, and 3.53 should be written as 4.50, 7.00, 2.50, and 3.53. An empty cell should be indicated with either a zero or a hyphen and should never be left blank.

footnotes

written in small letters, contain explanations for anything that cannot be easily understood by the reader from the title, box head, or stub.

source of data

should include the exact reference, especially if the data presented is not original.

GRAPHICAL METHOD

SImpler to read and appeal to more people, especially those who are not numerically inclined

Horizontal line (abscissa/x-axis)

Basis of classification.

Vertical line (ordinate/y-axis)

Enumerates data such as the number of observations, percentages, or rates.

Bar Graph/Chart/Diagram (Horizontal or Vertical)

Qualitative or Discrete

comparison of absolute or relative amounts, rates, etc. between categories of a qualitative or a discrete quantitative variable.

Used to portray numerical measurements across categories of a qualitative variable or discrete quantitative variable.

Should be of equal width, and gaps should separate them to show discontinuities.

Pie Chart

Quantitative
Shows the breakdown of a group or total where the number of categories is not too many.
Shows the percentage of the total number of observations falling into each of the categories.
In public health, the pie chart is commonly used to show breakdowns of funds, budgets, and expenses.

Bar Diagram/Chart

Qualitative
Function same as Pie Chart
Each bar is divided into smaller rectangles representing the components.
The area of each smaller rectangle is proportional to the relative contribution of the component to the whole.
An alternative to the pie chart but better depicts percentage distribution of two or more groups.

Histogram

Continuous quantitative
including frequency distribution of a variable or measurement.
Presents frequency distribution of a continuous quantitative variable.
Bars are continuous.
Class intervals are joined on the horizontal axis against its corresponding frequencies on the vertical axis.

Frequency polygon

Quantitative.
Presents frequency distribution of a continuous quantitative variable (same as Histogram).
Looks like a line graph; however, plots of the first and last class intervals are joined to the horizontal axis.
Midpoints of each class interval are connected against its corresponding frequencies.

Line Diagram

Time series
Shows trend data or changes with time or age with respect to some other variable.
Portrays trends over time; these could be trends of disease rates, mortality rates, % immunized, annual family income, etc.

Scatterpoint (Scatterplot; Dot Diagram; Scattergraph)

Quantitative
Between quantitative variables.
Presents relationship between two quantitative variables.
One variable plotted on the x-axis and the other on the y-axis.
Plotted points that fall in a straight line indicate a linear relationship between x and y.
Widely scattered points indicate no relationship between x and y.