Qualitative and Quantitative Research

Qualitative and  Quantitative Research

Qualitative Research and Quantitative research both are important for gaining different kinds of knowledge.

When collecting and analyzing data, quantitative research deals with numbers and statistics but Qualitative Research deals with words and meanings 

Qualitative and  Quantitative Research

                                  

                               

Qualitative Research:

Qualitative Research is expressed in words. It is used to understand concepts, thoughts or experiences. This type of research enables you to gather in-depth insights on topics that are not well understood.

Common Qualitative methods include interviews with open-ended questions, observations described in words, and literature reviews that explore concepts and theories. Qualitative Research is multimethod in focus, involving an interpretive, naturalistic approach to its subject matter. This means that Qualitative Researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them.

The aim of Qualitative Research is to understand the social reality of individuals, groups and cultures as nearly as possible as its participants feel it or live it. Thus, people and groups, are studied in their natural setting.

Quantitative research:

Quantitative research is expressed in numbers and graphs. It is used to test or confirm theories and assumptions. This type of research can be used to establish generalizable facts about a topic.

Common quantitative methods include experiments, observations recorded as numbers, and surveys with closed-ended questions. Quantitative data is information about quantities, and therefore numbers, and Qualitative data is descriptive, and regards phenomenon which can be observed but not measured, such as language.

The differences between quantitative and Qualitative Research

Quantitative and Qualitative Research use different research methods to collect and analyze data, and they allow you to answer different kinds of research questions.

Qualitative vs. quantitative research:   

                

Qualitative Research	Quantitative research
Focuses on exploring ideas and formulating a theory or hypothesis	Focuses on testing theories and hypotheses
Analyzed by summarizing, categorizing and interpreting	Analyzed through math and statistical analysis
Mainly expressed in words	Mainly expressed in numbers, graphs and tables
Requires few respondents	Requires many respondents
Open-ended questions	Closed (multiple choice) questions
Key terms: understanding, context, complexity, subjectivity	Key terms: testing, measurement, objectivity, replicability

                                   

Data collection methods:

Quantitative and Qualitative data can be collected using various methods. It is important to use a data collection method that will help answer your research question(s).

Many data collection methods can be either Qualitative or quantitative. For example, in surveys, observations or case studies, your data can be represented as numbers (e.g. using rating scales or counting frequencies) or as words (e.g. with open-ended questions or descriptions of what you observe).

Qualitative data collection methods:

Interviews: Asking open-ended questions verbally to respondents.

Focus groups: Discussion among a group of people about a topic to gather opinions that can be used for further research.

Ethnography: Participating in a community or organization for an extended period of time to closely observe culture and behavior.

Literature review: Survey of published works by other authors.

Quantitative data collection methods:

Surveys: List of closed or multiple choice questions that is distributed to a sample (online, in person, or over the phone).

Experiments: Situation in which variables are controlled and manipulated to establish cause-and-effect relationships.

Observations: Observing subjects in a natural environment where variables can’t be controlled.

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Data Analysis

Qualitative Research is endlessly creative and interpretive. The researcher does not just leave the field with mountains of empirical data and then easily write up his or her findings.

Qualitative interpretations are constructed, and various techniques can be used to make sense of the data, such as content analysis, grounded theory (Glaser & Strauss, 1967), thematic analysis (Braun & Clarke, 2006) or discourse analysis.

When to use Qualitative or Quantitative research:

A rule of thumb for deciding whether to use Qualitative or quantitative data is:

Use quantitative research if you want to confirm or test something (a theory or hypothesis)

Use Qualitative Research if you want to understand something (concepts, thoughts, experiences)

For most research topics you can choose a Qualitative, quantitative or mixed methods approach. Which type you choose depends on, among other things, whether you’re taking an inductive vs. deductive research approach; your research question(s); whether you’re doing experimental, correlational, or descriptive research; and practical considerations such as time, money, availability of data, and access to respondents.

Key Features:

Events can be understood adequately only if they are seen in context. Therefore, a Qualitative Researcher immerses her/himself in the field, in natural surroundings. The contexts of inquiry are not contrived; they are natural. Nothing is predefined or taken for granted.

1-For Qualitative Reasearcher:

Qualitative Researchers want those who are studied to speak for themselves, to provide their perspectives in words and other actions. Therefore, Qualitative Research is an interactive process in which the persons studied teach the researcher about their lives.

The Qualitative Researcher is an integral part of the data, without the active participation of the researcher, no data exists.

The design of the study evolves during the research, and can be adjusted or changed as it progresses.

For the Qualitative Researcher, there is no single reality, it is subjective and exist only in reference to the observer.

Theory is data driven, and emerges as part of the research process, evolving from the data as they are collected.

Limitations:

Because of the time and costs involved, Qualitative designs do not generally draw samples from large-scale data sets.

The problem of adequate validity or reliability is a major criticism. Because of the subjective nature of Qualitative data and its origin in single contexts, it is difficult to apply conventional standards of reliability and validity.

Strengths:

Because of close researcher involvement, the researcher gains an insider's view of the field. This allows the researcher to find issues that are often missed (such as subtleties and complexities) by the scientific, more positivistic inquiries.

Qualitative descriptions can play the important role of suggesting possible relationships, causes, effects and dynamic processes.

Qualitative analysis allows for ambiguities/contradictions in the data, which are a reflection of social reality (Denscombe, 2010).

Qualitative Research uses a descriptive, narrative style; this research might be of particular benefit to the practitioner as she or he could turn to Qualitative reports in order to examine forms of knowledge that might otherwise be unavailable, thereby gaining new insight.

2-For Quantitative Researcher:

Quantitative researchers try to control extraneous variables by conducting their studies in the lab.

The research aims for objectivity (i.e., without bias), and is separated from the data.

The design of the study is determined before it begins.

For the quantitative researcher reality is objective and exist separately to the researcher, and is capable of being seen by anyone.

Research is used to test a theory and ultimately support or reject it.

Limitations:

Context: Quantitative experiments do not take place in natural settings. In addition, they do not allow participants to explain their choices or the meaning of the questions may have for those participants (Carr, 1994).

Researcher expertise: Poor knowledge of the application of statistical analysis may negatively affect analysis and subsequent interpretation (Black, 1999).

Variability of data quantity: Large sample sizes are needed for more accurate analysis. Small scale quantitative studies may be less reliable because of the low quantity of data (Denscombe, 2010). This also affects the ability to generalize study findings to wider populations.

Confirmation bias: The researcher might miss observing phenomena because of focus on theory or hypothesis testing rather than on the theory of hypothesis generation.

Strengths:

Scientific objectivity: Quantitative data can be interpreted with statistical analysis, and since statistics are based on the principles of mathematics, the quantitative approach is viewed as scientifically objective, and rational (Carr, 1994; Denscombe, 2010).

Useful for testing and validating already constructed theories.

Rapid analysis: Sophisticated software removes much of the need for prolonged data analysis, especially with large volumes of data involved (Antonius, 2003).

Replication: Quantitative data is based on measured values and can be checked by others because numerical data is less open to ambiguities of interpretation.

Hypotheses can also be tested because of the used of statistical analysis (Antonius, 2003)

Research Question:

How satisfied are students with their studies?

Quantitative research approach

You survey 300 students at your university and ask them questions such as: “on a scale from 1-5, how satisfied are your with your professors?”

You can perform statistical analysis on the data and draw conclusions such as: “on average students rated their professors 4.4”.

Qualitative Research approach

You conduct in-depth interviews with 15 students and ask them open-ended questions such as: “How satisfied are you with your studies?”, “What is the most positive aspect of your study program?” and “What can be done to improve the study program?”

Based on the answers you get you can ask follow-up questions to clarify things. You transcribe all interviews using transcription software and try to find commonalities and patterns.

Mixed methods approach

You conduct interviews to find out how satisfied students are with their studies. Through open-ended questions you learn things you never thought about before and gain new insights. Later, you use a survey to test these insights on a larger scale.

It’s also possible to start with a survey to find out the overall trends, followed by interviews to better understand the reasons behind the trends.

How to analyze Qualitative and quantitative data:

Qualitative or quantitative data by itself can’t prove or demonstrate anything, but has to be analyzed to show its meaning in relation to the research questions. The method of analysis differs for each type of data.

Analyzing quantitative data:

Quantitative data is based on numbers. Simple math or more advanced statistical analysis is used to discover commonalities or patterns in the data. The results are often reported in graphs and tables.

Applications such as Excel, SPSS, or R can be used to calculate things like:

• Average scores
• The number of times a particular answer was given
• The correlation or causation between two or more variables
• The reliability and validity of the results

Analyzing Qualitative data:

Qualitative data is more difficult to analyze than quantitative data. It consists of text, images or videos instead of numbers.

Some common approaches to analyzing Qualitative data include:

Qualitative content analysis: Tracking the occurrence, position and meaning of words or phrases

Thematic analysis: Closely examining the data to identify the main themes and patterns

Discourse analysis: Studying how communication works in social contexts