Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Data Collection I01:30

Data Collection I

6.0K
Data collection gathers information needed to make accurate judgments about a patient's present condition. During a health history interview, subjective data is collected from the patient, their caregivers, or family members, and objective data is collected through observations and physical assessment. Patients are the primary source of subjective data. Thus information gathered from patients through interviews, observations, and physical examination is primary data. Secondary sources of...
6.0K
Data Collection by Observations01:08

Data Collection by Observations

11.7K
Data collection refers to a systematic way of obtaining, observing, measuring, and analyzing accurate information. Observational studies are one of the most widely used methods of data collection. It involves collecting data by observing the behavior and physical characteristics of a sample without making any modifications to the sample.
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
11.7K
Review and Preview01:13

Review and Preview

8.8K
Data are individual items of information obtained from a population or sample. Data may be classified as qualitative (categorical), quantitative continuous, or quantitative discrete. Because it is not practical to measure the entire population in a study, researchers use samples to represent the population. A random sample is a representative group from the population chosen by using a method that gives each individual in the population an equal chance of being included in the sample. Random...
8.8K
How Data are Classified: Categorical Data01:11

How Data are Classified: Categorical Data

31.5K
A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
31.5K
Data Collection III01:05

Data Collection III

2.6K
The physical assessment examines the patient for objective data that defines the patient's condition, and aids in formulating the nursing care plan. The purpose of physical assessment is a health status appraisal, which includes identifying health problems, and establishing a database for nursing intervention.
The principles to begin the physical assessment include conducting a comprehensive or problem-related history in a quiet, well-lit room, emphasizing privacy and comfort for the...
2.6K
Data Collection by Survey01:07

Data Collection by Survey

6.4K
The systematic method of obtaining and analyzing accurate information of a population is called data collection. A survey is a standard method of data collection that involves collecting information from a target human population about their experience, opinion, or knowledge of a product, service, or process. The responses are recorded and interpreted. The most common survey examples are written questionnaires, face-to-face or telephonic conversations, focus groups, and electronic (e-mail or...
6.4K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

7. Developing high-performance prediction models for medical outcomes.

Journal of postgraduate medicine·2026
Same author

6. The conundrum of regression, correlation, association, and agreement.

Journal of postgraduate medicine·2026
Same author

5. Determining the size of sample for rigorous conclusions.

Journal of postgraduate medicine·2025
Same author

4. The riddle of confidence levels and the levels of significance in the era of artificial intelligence.

Journal of postgraduate medicine·2025
Same author

3. P values, power, and medical significance for credible results.

Journal of postgraduate medicine·2025
Same author

1. Study designs for making most of the limited resources.

Journal of postgraduate medicine·2024
Same journal

Assessment of exclusive breastfeeding practices in a tribal district of Maharashtra: A cross-sectional study.

Journal of postgraduate medicine·2026
Same journal

Leveraging immersive technology with virtual emulation for training of nonmedico combatants: A randomized controlled trial.

Journal of postgraduate medicine·2026
Same journal

From clinic to microscope: A study of clinicopathological concordance in 5000 skin biopsies from a tertiary care center.

Journal of postgraduate medicine·2026
Same journal

Early anticoagulation with warfarin for pulmonary embolism complicating active gastric ulcer: A case against guideline-mandated delay.

Journal of postgraduate medicine·2026
Same journal

Paradoxical Hemophagocytic Lymphohistiocytosis to Stevens-Johnson Syndrome - Toxic Epidermal Necrolysis- A rare immune phenomenon.

Journal of postgraduate medicine·2026
Same journal

Anesthetic management of neonate with hypoplastic left heart syndrome posted for exploratory laparotomy.

Journal of postgraduate medicine·2026
See all related articles

Related Experiment Video

Updated: May 24, 2025

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
09:43

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Published on: November 22, 2019

6.2K

2. Types of data and data collation for efficient processing.

A Indrayan1

  • 1Department of Clinical Research, Max Healthcare, New Delhi, India.

Journal of Postgraduate Medicine
|March 6, 2025
PubMed
Summary
This summary is machine-generated.

Proper data collation and understanding data types are crucial for accurate statistical analysis in research. This guide helps researchers, especially early-career scientists, manage data effectively for reliable conclusions.

More Related Videos

Using a Virtual Store As a Research Tool to Investigate Consumer In-store Behavior
09:17

Using a Virtual Store As a Research Tool to Investigate Consumer In-store Behavior

Published on: July 24, 2017

11.3K
Author Spotlight: Advancing Protein Structure Analysis for Drug Development
07:08

Author Spotlight: Advancing Protein Structure Analysis for Drug Development

Published on: March 8, 2024

3.3K

Related Experiment Videos

Last Updated: May 24, 2025

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
09:43

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Published on: November 22, 2019

6.2K
Using a Virtual Store As a Research Tool to Investigate Consumer In-store Behavior
09:17

Using a Virtual Store As a Research Tool to Investigate Consumer In-store Behavior

Published on: July 24, 2017

11.3K
Author Spotlight: Advancing Protein Structure Analysis for Drug Development
07:08

Author Spotlight: Advancing Protein Structure Analysis for Drug Development

Published on: March 8, 2024

3.3K

Area of Science:

  • Empirical research methodology
  • Biostatistics and data analysis

Background:

  • Data collection and collation are fundamental to empirical research.
  • Statistical analysis relies on properly collated data, with methods varying by data type.
  • Researchers, particularly early-career scientists, often need guidance on data management and presentation.

Purpose of the Study:

  • To elucidate various data types and their proper collation for statistical analysis.
  • To provide guidance on preparing tables and graphics for effective data communication.
  • To enhance the data management skills of postgraduate students, young researchers, and experienced professionals.

Main Methods:

  • Review of data types, including quantitative, qualitative, and ordinal data.
  • Explanation of data collation techniques and best practices.
  • Guidance on the effective use of tables and graphics in research reporting.

Main Results:

  • Understanding different data types is essential for appropriate statistical processing.
  • Effective data collation ensures the integrity of research findings.
  • Judicious use of tables and graphics significantly improves the communication of results.

Conclusions:

  • Accurate data management, from collection to presentation, is vital for drawing correct conclusions in empirical research.
  • This article serves as a practical resource for researchers at all career stages to improve their data handling and reporting skills.