Data Presentation

Data: is any observational collected in respect of any characteristic or event.

Types of data:

1)    Qualitative / quantitative data.

2)    Discrete / continuous data.

3)    Primary / secondary data.

4)    Nominal / ordinal data.

Principals of data presentation:

a)    To arrange data in order to create interest in reader’s mind.

b)    To present information in a compact and concise form without losing important details.

c)    To present data in a simple form to draw conclusion directly by viewing data.

d)    To present data in order to help in further statistical analysis.

Types of presentation of data:

Tabulation (making tables): is the most common method of presenting analyzed data which offers a useful means of presenting large amounts of detailed information in a small space. Tables can clarify text, provide visual relief, and serve as quick point of reference.

To write table in a perfect way:

1)    Tables should be numbered ex: table 1, table 2,….

2)    Title should be given to the table which should be brief and self-explanatory.

3)    The headings of columns and rows should be clear and concise.

4)    The data must be presented according to size and importance chronologically, alphabetically, or geographically.

5)    If percentages or averages are to be compared, they should be put as close as possible.

6)    No table should be too large.

7)    Most of people find a vertical arrangement better than horizontal one because it is easier to scan data from top to bottom instead from left to right.

8)    Foot notes should be given to provide explanatory notes or additional information.

Parts of table:

·    Sub, its variables are listed along y-axis while column headings, their variables are listed along x-axis Supplementary notes may be: source note, other general note, note on specific part of table, or note on level of probability. 

Types of table:

a)    Univariate (frequency tables) contains one variable.

b)    Bivariate (cross tables) contains 2 variables.

c)    Multivariate contains more than 2 variables.

Another types of tables:

1)    Line list tables.

2)    Frequency distribution table.

3)    Epidemiological table.

Frequency distribution table is a list, table or graph that displays the frequency of various outcomes in a sample. Here, the data is first split up into convenient groups (class interval) and number of items (frequency) which occur in each group.

Epidemiological table: you can review cross-sectional study section.

Charts and Diagram or Graphs: are useful methods of presenting data which have powerful impact on imagination of people, give information at glance, and are better retained in memory than statistical table.

Rules to draw them:

a)    A graphic presentation is constructed in relation to two axes: horizontal and vertical.

b)    If a graph is designed to display only one variable, it is customary, but not essential, to represent the subcategories of the variable along the x-axis and the frequency or count of that subcategory along the y-axis.

c)    A graph, like a table, should have a title that describes its contents. The axes should be labelled also.

d)    A graph should be drawn to an appropriate scale. It is important to choose a scale that enables your graph to be neither too small nor too large.

Types of charts:

a)    Bar charts: is used for displaying categorical data and for variables measured on nominal or ordinal scales.

Characteristics:

1)    Data presented is categorical.

2)    Is presented in form of rectangular bar of equal breadth.

3)    Each bar represents one variant.

4)    The gaps between bars should be equal.

5)    The length of bar should be proportional to magnitude of variable

6)    Bar may be vertical or horizontal.

It has many forms:

Simple bar chart:

Multiple bar chart:

Stacked bar chart:

Here, each bar shows information about two or more variables stacked onto each other vertically. The sections of a bar show the proportion of the variables they represent in relation to one another. The stacked bars can be drawn only for categorical data.

The 100 per cent bar chart:

is very similar to the stacked bar chart. In this case, the subcategories of a variable are converted into percentages of the total population. Each bar, which totals 100, is sliced into portions relative to the percentage of each subcategory of the variable.

b)    Histogram: consists of a series of rectangles drawn next to each other without any space between them, each representing the frequency of a category or subcategory and can be drawn for both categorical and continuous variables.

Forms of histogram:

1)    Here, there is one variable:

2)    Here, there is 2 variables:

c)    Frequency polygon: is very similar to a histogram where is drawn by joining the midpoint of each rectangle at a height commensurate with the frequency of that interval.

d)    Cumulative frequency polygon:

is drawn on the basis of cumulative frequencies.

Cumulative frequency distribution tells you the number of observations less than a given value.

e)    Pie chart: is the most common way to represent data where the value of each data is divided by total values and then multiplied by 360, so the circle or pie is divided into sections in accordance with the magnitude of each subcategory.

f)     Line diagram: A set of data measured on a continuous interval or a ratio scale can be displayed using it. Line diagram is a useful way of visually conveying the changes when long-term trends in a phenomenon or situation need to be studied, or the changes in the subcategory of a variable are measured on an interval or a ratio scale. Here, time is plotted on x-axis, other variable on y-axis.

g)    Scatter diagram: When you want to show visually how one variable changes in relation to a change in the other variable.

h)    Pictogram: is a chart that uses pictures to represent data.

Wait for us in another topic in Medical Research!!!!!!