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Related Concept Videos

Qualitative Analysis01:10

Qualitative Analysis

899
Qualitative analysis is the process of identifying elements, ions, or compounds in an unknown sample. It is the first and most fundamental type of analysis based on the hierarchy of analytical goals. This hierarchy is significant as it provides a structured approach to scientific research, with qualitative analysis serving as the initial step, providing essential information before moving on to quantitative or other forms of analysis.
There are two main approaches to qualitative analysis:...
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Qualitative Analysis03:46

Qualitative Analysis

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For solutions containing mixtures of different cations, the identity of each cation can be determined by qualitative analysis. This technique involves a series of selective precipitations with different chemical reagents, each reaction producing a characteristic precipitate for a specific group of cations. Metal ions within a group are further separated by varying the pH, heating the mixture to redissolve a precipitate, or adding other reagents to form complex ions.
For instance, group IV...
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Review and Preview01:13

Review and Preview

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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...
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Review and Preview01:10

Review and Preview

8.1K
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...
8.1K
Bar Graph01:07

Bar Graph

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A bar graph is also called a bar chart and consists of bars that are separated from each other. It either uses horizontal or vertical bars to show comparisons among categories. The bars can be rectangles, or they can be rectangular boxes (used in three-dimensional plots). One axis of the graph represents the specific categories being compared, and the other axis shows a discrete value. In this graph, the length of the bar for each category is proportional to the number or percent of individuals...
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How Data are Classified: Categorical Data01:11

How Data are Classified: Categorical Data

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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...
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Conceptualizing Qualitative Data.

Alex Broom1

  • 1The University of Sydney, Sydney, New South Wales, Australia.

Qualitative Health Research
|June 24, 2021
PubMed
Summary
This summary is machine-generated.

This editorial examines conceptualization in qualitative research, highlighting diverse perspectives and common challenges in theory development across various disciplines. It addresses the varied conceptual depth found in journal submissions.

Keywords:
methodologyqualitativeresearch designteachingtheory development

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Area of Science:

  • Social Sciences
  • Humanities
  • Health Sciences

Background:

  • Qualitative research is employed across diverse academic fields, leading to varied approaches.
  • Submissions to qualitative journals exhibit a wide spectrum of conceptualization and theory development.

Discussion:

  • This editorial probes the fundamental reasons for conceptualizing qualitative data.
  • It identifies prevalent challenges encountered in contemporary qualitative research practices.

Key Insights:

  • Understanding the 'why' behind conceptualization is crucial for advancing qualitative inquiry.
  • Addressing common challenges can elevate the rigor and impact of qualitative studies.

Outlook:

  • Future qualitative research should focus on enhancing conceptual clarity and theoretical depth.
  • Promoting consistent standards in conceptualization will strengthen the contribution of qualitative findings.