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Related Concept Videos

Surveys02:16

Surveys

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Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally. Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.
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Ranks01:02

Ranks

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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...
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Data Collection by Survey01:07

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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...
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Stratified Sampling Method01:16

Stratified Sampling Method

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...
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Random Sampling Method01:09

Random Sampling Method

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
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Ordinal Level of Measurement00:55

Ordinal Level of Measurement

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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...
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Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning
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Using ranked survey data in education research: Methods and applications.

Anna E Bargagliotti1, Susan E Martonosi2, Michael E Orrison2

  • 1Loyola Marymount University, USA.

Journal of School Psychology
|March 15, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces advanced methods for analyzing ranked data in education and school psychology, moving beyond simple mean rank examinations to provide deeper insights for decision-making.

Keywords:
Cluster analysisRanked dataRanked data visualizationSurvey dataTests of uniformity

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Area of Science:

  • Educational Psychology
  • Psychometrics
  • Data Analysis

Background:

  • Ranked data are frequently used in education and school psychology for decision-making.
  • Current analysis methods for ranked data are often limited to basic approaches like mean rank examination.
  • There is a need for more comprehensive techniques to fully utilize ranked data.

Purpose of the Study:

  • To provide a unified roadmap of classical and novel methodologies for analyzing ranked data.
  • To demonstrate the application of these methods in school psychological research.
  • To enhance the insights derived from ranked data for researchers and practitioners.

Main Methods:

  • Descriptive analyses and visualizations of ranked data.
  • Statistical tests, including tests of uniformity.
  • Advanced techniques such as cluster analyses and predictive modeling.
  • Application to existing survey data for illustration.

Main Results:

  • A broader set of analytical tools yields improved insights from ranked data.
  • Demonstration of diverse techniques on real-world school psychology data.
  • Validation of advanced methods for analyzing ranked preferences and competencies.

Conclusions:

  • Researchers and practitioners can benefit from employing a wider array of analytical techniques for ranked data.
  • The proposed methodologies offer a more robust approach to understanding student and system-level information.
  • This work serves as a guide for leveraging the full potential of ranked data in educational and psychological research.