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Related Concept Videos

Ranks01:02

Ranks

Unlike parametric methods, nonparametric statistics are ideal for nominal and ordinal data, requiring fewer assumptions about the population's nature or distribution. This makes nonparametric methods easier to apply and interpret, as they do not depend on parameters like mean or standard deviation. One common approach in nonparametric analysis is to sort data according to a specific criterion. For instance, we might arrange weather data from hottest to coldest days in a month or rank cities...
Review and Preview01:10

Review and Preview

In statistics, several tools are used to interpret the data. Measures of central tendency represent the characteristics of the data, such as mean, median, and mode. Additionally, measures of variance like standard deviation and range are used to find the spread of data from the mean. Relative standing measures the distance between data locations. Commonly used measures of relative standings are percentile, z score, and quartiles.
Percentiles are a type of fractile that partition data into...
Review and Preview01:13

Review and Preview

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...
Percentile01:18

Percentile

A percentile indicates the relative standing of a data value when data are sorted into numerical order from smallest to largest. It represents the percentages of data values that are less than or equal to the pth percentile. For example, 15% of data values are less than or equal to the 15th percentile. Low percentiles always correspond to lower data values. High percentiles always correspond to higher data values.Percentiles divide ordered data into hundredths. To score in the...
Ordinal Level of Measurement00:55

Ordinal Level of Measurement

The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks in the...
Ratio Level of Measurement00:54

Ratio Level of Measurement

The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
A set of data measured using the ratio scale takes care of the ratio problem and provides complete information. Ratio scale data are like interval scale data, except they have a zero point and ratios can be calculated. For...

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Related Experiment Video

Updated: Jun 6, 2026

Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning
10:39

Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning

Published on: August 29, 2025

Ratings and rankings.

Wendy C Budin1

  • 1WENDY BUDIN is the editor-in-chief of The Journal of Perinatal Education. She is also the director of nursing research at NYU Langone Medical Center and a clinical professor at New York University, College of Nursing. She is a fellow in the American College of Childbirth Educators and is a member of the Lamaze International Certification Council.

The Journal of Perinatal Education
|November 19, 2010
PubMed
Summary
This summary is machine-generated.

This column discusses scholarly journal ranking systems and highlights issue content for childbirth educators. It provides resources and research to promote natural, safe, and healthy birth practices.

Keywords:
childbirth educationhealthy birthjournal rankingsnatural birthnormal birthperinatal educationsafe birth

Related Experiment Videos

Last Updated: Jun 6, 2026

Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning
10:39

Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning

Published on: August 29, 2025

Area of Science:

  • Perinatal Education
  • Scholarly Communication

Background:

  • The Journal of Perinatal Education serves as a key resource for childbirth educators.
  • Effective promotion of natural, safe, and healthy birth requires access to current research and educational materials.

Purpose of the Study:

  • To inform readers about scholarly journal ranking systems.
  • To introduce the diverse content within this issue of The Journal of Perinatal Education.
  • To support childbirth educators in their mission.

Main Methods:

  • Descriptive analysis of journal ranking methodologies.
  • Content overview of the current issue, including research articles, resources, and inspirational pieces.

Main Results:

  • Explanation of various systems used to rank scholarly journals.
  • Presentation of a broad spectrum of materials relevant to perinatal education and practice.

Conclusions:

  • Understanding journal rankings can aid educators in identifying high-impact research.
  • The issue provides valuable tools and knowledge to enhance childbirth education and promote optimal birth outcomes.