Graphical Representation of Data

GRAPHICAL REPRESENTATION OF DATA

Introduction

·       Data: Facts, observations, and measurements collected for analysis and decision-making.

·       It can be qualitative (descriptive) or quantitative (numerical).

Classification of Data

A. According to Nature:

1. Qualitative Data – Descriptive attributes (e.g., gender, blood group, marital status).
2. Quantitative Data – Numerical values (e.g., age, height, income).
• Discrete: Countable (e.g., number of patients).
• Continuous: Measurable (e.g., temperature, blood pressure).

B. According to Source:

1. Primary Data – Collected first-hand by the researcher.
2. Secondary Data – Collected by someone else, used by the researcher.

C. According to Time:

1. Cross-sectional Data – Collected at one point in time.
2. Time Series Data – Collected over different time periods.

D. According to Area:

1. Regional/Geographical Data – Data by location.
2. Global/National Data – Large-scale data for countries or the world.

Collection of Data

Planning of Statistical Investigation

Before collecting data:

1. Define Objectives – Purpose of study.
2. Decide Scope – Area, population, variables.
3. Choose Sources – Primary or secondary.
4. Design Tools – Questionnaire, interview schedule.
5. Select Sampling Method – Random, stratified, cluster.
6. Train Investigators – Ensure uniformity.
7. Collect Data – As per plan.
8. Check & Edit – Correct errors before analysis.

Methods of Collecting Primary Data

1. Observation Method – Direct visual examination.
2. Interview Method – Personal or telephonic.
3. Questionnaire Method – Written list of questions.
4. Schedule Method – Filled by interviewer.
5. Experimental Method – Controlled conditions.
6. Survey Method – Large-scale data collection.

Methods of Collecting Secondary Data

1. Published Sources – Books, journals, reports, census.
2. Unpublished Sources – Research manuscripts, hospital records.
3. Government Publications – Health ministry, statistical office.
4. Online Databases – WHO, PubMed.

Tabulation of Data

·       Systematic arrangement of data in rows and columns for easy understanding.

Types of Tables

1. Simple Table – Shows one characteristic.
2. Complex Table – Shows multiple characteristics.
3. Frequency Table – Shows values with their frequencies.

Steps in Preparing a Table

1. Decide Objective – Purpose of table.
2. Determine Size – Number of rows/columns.
3. Frame Title – Self-explanatory.
4. Classify Data – Into categories.
5. Arrange Entries – Logical order.
6. Provide Headings – Row and column heads.
7. Insert Source Note – If required.

Frequency Table Preparation

Steps:

1. List Data.
2. Find Range – Max value – Min value.
3. Decide Class Interval – Usually 5–10 groups.
4. Tally Data – Mark frequencies.
5. Prepare Table – Include cumulative frequencies if needed.

Graphical Representation of Data

·       Graphical representation is the visual display of data using diagrams, charts, or graphs to simplify complex information.

Importance

• Easy to understand.
• Attracts attention.
• Quick comparison.
• Shows trends and patterns.

Types / Modes of Graphical Representation

Line Graph

• Definition: Data points connected by straight lines.
• Use: Show changes over time.
• Advantages: Clear trend analysis.
• Example: Monthly hospital OPD attendance.

Bar Graph

• Definition: Rectangles of equal width, different lengths representing values.
• Types: Vertical bar, horizontal bar, multiple bar, stacked bar.
• Advantages: Easy comparison.
• Example: Deaths by cause.

Pie Chart

• Definition: Circle divided into sectors proportional to data values.
• Advantages: Shows relative proportions.
• Example: Budget allocation in hospital departments.

Pictograph

• Definition: Uses pictures or symbols to represent data.
• Advantages: Attractive for public education.
• Example: Immunization coverage using vaccine icons.

Grouped Data Representation

Histogram

• Definition: Adjacent bars showing frequency distribution of continuous data.
• Use: Shape of distribution.
• Steps:
1. Mark class intervals on x-axis.
2. Mark frequencies on y-axis.
3. Draw bars without gaps.

Frequency Polygon

• Definition: Line graph connecting midpoints of histogram bars.
• Advantages: Easy comparison of distributions.

Frequency Curve

• Definition: Smooth curve joining points of frequency polygon.
• Use: For theoretical distribution study.

Ogive (Cumulative Frequency Curve)

• Types:
1. Less Than Ogive – Plot cumulative frequencies less than upper class limit.
2. More Than Ogive – Plot cumulative frequencies more than lower class limit.
• Uses: Determine median, quartiles, percentiles.

Video Description

·        Don’t forget to do these things if you get benefitted from this article

·        Visit our Let’s contribute page https://keedainformation.blogspot.com/p/lets-contribute.html

·        Follow our page

·        Like & comment on our post

·