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Anyone in the world
In the dim light of my heart, your presence shines,
A crush, like a delicate flower blooming in the garden of my thoughts,
Your smile, a beacon of hope amidst life's chaos.
[ Modified: Wednesday, 21 February 2024, 12:07 PM ]
Anyone in the world
We have our own world
I don't know you, we're totally strangers.
My innocence lead me to explore
Try other sports and learn more.
I met you but nothing else
Knowing one's self and just be friends.
[ Modified: Thursday, 22 February 2024, 10:21 PM ]
Anyone in the world
Monday's dawn, a timid brush takes flight
Canvas whispers softly, under morning light.
In tentative strokes, the colors start to blend
As creativity's journey finds its gentle bend.
Next>>
[ Modified: Tuesday, 27 February 2024, 11:24 AM ]
Anyone in the world
Loyalty, the anchor, holding steadfast and true
In the vast of sea of life, a sail with you
A trust, a brigde of built with the word unspoken
In the symphony of friendship, our heart are awaken
Anyone in the world
Where the wind blows
Your red hair flows
A sunny glare
When your eyes stare
Oh, Rozanette
Where had you go
Until today
I miss you so
-Ziah
[ Modified: Friday, 23 February 2024, 3:51 PM ]
Anyone in the world
Life is but a stopping place,
A pause in what's to be,
A resting place along the road,
To sweet eternity.
[ Modified: Wednesday, 28 February 2024, 12:37 PM ]
Anyone in the world
In the garden of campanionship a seed sown
A frienship bloosom a bond brightly ston
Through laugther and tears, side by side we stride
In the tapestry of time our connection won't hide.
Anyone in the world
On This Post:
- What Is Qualitative Research?
- Qualitative Methods
- Examples
- Qualitative Data Analysis
- Key Features
- Limitations of Qualitative Research
- Advantages of Qualitative Research
- What Is Quantitative Research?
- Quantitative Methods
- Examples
- Quantitative Data Analysis
- Key Features
- Limitations of Quantitative Research
- Advantages of Quantitative Research
What is the difference between quantitative and qualitative?
The main difference between quantitative and qualitative research is the type of data they collect and analyze.
Quantitative research collects numerical data and analyzes it using statistical methods. The aim is to produce objective, empirical data that can be measured and expressed in numerical terms. Quantitative research is often used to test hypotheses, identify patterns, and make predictions.
Qualitative research, on the other hand, collects non-numerical data such as words, images, and sounds. The focus is on exploring subjective experiences, opinions, and attitudes, often through observation and interviews.
Qualitative research aims to produce rich and detailed descriptions of the phenomenon being studied, and to uncover new insights and meanings.
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.
What Is Qualitative Research?
Qualitative research is the process of collecting, analyzing, and interpreting non-numerical data, such as language. Qualitative research can be used to understand how an individual subjectively perceives and gives meaning to their social reality.
Qualitative data is non-numerical data, such as text, video, photographs, or audio recordings. This type of data can be collected using diary accounts or in-depth interviews and analyzed using grounded theory or thematic analysis.
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.
Denzin and Lincoln (1994, p. 2)
Interest in qualitative data came about as the result of the dissatisfaction of some psychologists (e.g., Carl Rogers) with the scientific study of psychologists such as behaviorists (e.g., Skinner).
Since psychologists study people, the traditional approach to science is not seen as an appropriate way of carrying out research since it fails to capture the totality of human experience and the essence of being human. Exploring participants’ experiences is known as a phenomenological approach (re: Humanism).
Qualitative research is primarily concerned with meaning, subjectivity, and lived experience. The goal is to understand the quality and texture of people’s experiences, how they make sense of them, and the implications for their lives.
Qualitative research aims to understand the social reality of individuals, groups, and cultures as nearly as possible as participants feel or live it. Thus, people and groups are studied in their natural setting.
Some examples of qualitative research questions are provided, such as what an experience feels like, how people talk about something, how they make sense of an experience, and how events unfold for people.
Research following a qualitative approach is exploratory and seeks to explain ‘how’ and ‘why’ a particular phenomenon, or behavior, operates as it does in a particular context. It can be used to generate hypotheses and theories from the data.
Qualitative Methods
There are different types of qualitative research methods, including diary accounts, in-depth interviews, documents, focus groups, case study research, and ethnography.
The results of qualitative methods provide a deep understanding of how people perceive their social realities and in consequence, how they act within the social world.
The researcher has several methods for collecting empirical materials, ranging from the interview to direct observation, to the analysis of artifacts, documents, and cultural records, to the use of visual materials or personal experience.
Denzin and Lincoln (1994, p. 14)
Examples
Here are some examples of qualitative data:
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Interview transcripts: Verbatim records of what participants said during an interview or focus group. They allow researchers to identify common themes and patterns, and draw conclusions based on the data. Interview transcripts can also be useful in providing direct quotes and examples to support research findings.
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Observations: The researcher typically takes detailed notes on what they observe, including any contextual information, nonverbal cues, or other relevant details. The resulting observational data can be analyzed to gain insights into social phenomena, such as human behavior, social interactions, and cultural practices.
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Unstructured interviews: generate qualitative data through the use of open questions. This allows the respondent to talk in some depth, choosing their own words. This helps the researcher develop a real sense of a person’s understanding of a situation.
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Diaries or journals: Written accounts of personal experiences or reflections.
Notice that qualitative data could be much more than just words or text. Photographs, videos, sound recordings, and so on, can be considered qualitative data. Visual data can be used to understand behaviors, environments, and social interactions.
Qualitative 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.
For example, thematic analysis is a qualitative approach that involves identifying implicit or explicit ideas within the data. Themes will often emerge once the data has been coded.
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.
- 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 study’s design 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 exists only in reference to the observer.
- The theory is data-driven and emerges as part of the research process, evolving from the data as they are collected.
Limitations of Qualitative Research
- 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. For example, because of the central role played by the researcher in the generation of data, it is not possible to replicate qualitative studies.
- Also, contexts, situations, events, conditions, and interactions cannot be replicated to any extent, nor can generalizations be made to a wider context than the one studied with confidence.
- The time required for data collection, analysis, and interpretation is lengthy. Analysis of qualitative data is difficult, and expert knowledge of an area is necessary to interpret qualitative data. Great care must be taken when doing so, for example, looking for mental illness symptoms.
Advantages of Qualitative Research
- 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 be important in suggesting possible relationships, causes, effects, and dynamic processes.
- Qualitative analysis allows for ambiguities/contradictions in the data, which reflect 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 to examine forms of knowledge that might otherwise be unavailable, thereby gaining new insight.
What Is Quantitative Research?
Quantitative research involves the process of objectively collecting and analyzing numerical data to describe, predict, or control variables of interest.
The goals of quantitative research are to test causal relationships between variables, make predictions, and generalize results to wider populations.
Quantitative researchers aim to establish general laws of behavior and phenomenon across different settings/contexts. Research is used to test a theory and ultimately support or reject it.
Quantitative Methods
Experiments typically yield quantitative data, as they are concerned with measuring things. However, other research methods, such as controlled observations and questionnaires, can produce both quantitative information.
For example, a rating scale or closed questions on a questionnaire would generate quantitative data as these produce either numerical data or data that can be put into categories (e.g., “yes,” “no” answers).
Experimental methods limit how research participants react to and express appropriate social behavior.
Findings are, therefore, likely to be context-bound and simply a reflection of the assumptions that the researcher brings to the investigation.
Examples
There are numerous examples of quantitative data in psychological research, including mental health. Here are a few examples:
- Standardized psychological assessments: One example of a standardized psychological assessment of IQ that uses quantitative data is the Wechsler Adult Intelligence Scale (WAIS).
Another example is the Experience in Close Relationships Scale (ECR), a self-report questionnaire widely used to assess adult attachment styles.
The ECR provides quantitative data that can be used to assess attachment styles and predict relationship outcomes.
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Neuroimaging data: Neuroimaging techniques, such as MRI and fMRI, provide quantitative data on brain structure and function.
This data can be analyzed to identify brain regions involved in specific mental processes or disorders.
- Clinical outcome measures: The use of clinical outcome measures provides objective, standardized data that can be used to assess treatment effectiveness and monitor symptoms over time, helping mental health professionals make informed decisions about treatment and care.
For example, the Beck Depression Inventory (BDI) is a clinician-administered questionnaire widely used to assess the severity of depressive symptoms in individuals.
The BDI consists of 21 questions, each scored on a scale of 0 to 3, with higher scores indicating more severe depressive symptoms.
Quantitative Data Analysis
Statistics help us turn quantitative data into useful information to help with decision-making. We can use statistics to summarize our data, describing patterns, relationships, and connections. Statistics can be descriptive or inferential.
Descriptive statistics help us to summarize our data. In contrast, inferential statistics are used to identify statistically significant differences between groups of data (such as intervention and control groups in a randomized control study).
Key Features
- 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, the reality is objective, exists separately from the researcher, and can be seen by anyone.
- Research is used to test a theory and ultimately support or reject it.
Limitations of Quantitative Research
- 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 they 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.
Advantages of Quantitative Research
- 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 statistical analysis (Antonius, 2003).
References
Antonius, R. (2003). Interpreting quantitative data with SPSS. Sage.
Black, T. R. (1999). Doing quantitative research in the social sciences: An integrated approach to research design, measurement and statistics. Sage.
Braun, V. & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3, 77–101.
Carr, L. T. (1994). The strengths and weaknesses of quantitative and qualitative research: what method for nursing? Journal of advanced nursing, 20(4), 716-721.
Denscombe, M. (2010). The Good Research Guide: for small-scale social research. McGraw Hill.
Denzin, N., & Lincoln. Y. (1994). Handbook of Qualitative Research. Thousand Oaks, CA, US: Sage Publications Inc.
Glaser, B. G., Strauss, A. L., & Strutzel, E. (1968). The discovery of grounded theory; strategies for qualitative research. Nursing research, 17(4), 364.
Minichiello, V. (1990). In-Depth Interviewing: Researching People. Longman Cheshire.
Punch, K. (1998). Introduction to Social Research: Quantitative and Qualitative Approaches. London: Sage
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There are two distinct types of data collection and study: qualitative and quantitative. Although both provide an analysis of data, they differ in their approach and the type of data they collect. Awareness of these approaches can help researchers construct their study and data collection methods.
Topics:
- What Is the Difference Between Qualitative vs. Quantitative Research?
- Qualitative vs. Quantitative Outcomes
- Benefits and Limitations of Qualitative vs. Quantitative Research
- How To Analyze Qualitative vs. Quantitative Data
- Become a Qualitative or Quantitative Researcher
What Is the Difference Between Qualitative vs. Quantitative Research?
Because qualitative and quantitative studies collect different types of data, their data collection methods differ considerably. Quantitative studies rely on numerical or measurable data. In contrast, qualitative studies rely on personal accounts or documents that illustrate in detail how people think or respond within society.
Qualitative Research: Data Collection for Your Doctorate Degree
Qualitative research methods include gathering and interpreting non-numerical data. The following are some sources of qualitative data1:
- Interviews
- Focus groups
- Documents
- Personal accounts or papers
- Cultural records
- Observation
In the course of a qualitative study, the researcher may conduct interviews or focus groups to collect data that is not available in existing documents or records. To allow freedom for varied or unexpected answers, interviews and focus groups may be unstructured or semi-structured.
An unstructured or semi-structured format allows the researcher to pose open-ended questions and follow wherever the responses lead. The responses provide a comprehensive perspective on each individual’s experiences, which are then compared with those of other participants in the study.
Quantitative Research: Data Collection for Your Degree
Quantitative studies, in contrast, require different data collection methods. These methods include compiling numerical data to test causal relationships among variables. Some forms of data collection for this type of study include1:
- Experiments
- Questionnaires
- Surveys
- Database reports
The above collection methods yield data that lends itself to numerical analysis. Questionnaires in this case have a multiple-choice format to generate countable answers, such as “yes” or “no,” which can be turned into quantifiable data.
Qualitative vs. Quantitative Outcomes
One of the factors distinguishing qualitative from quantitative studies is the nature of the intended outcome. Qualitative researchers seek to learn from details of the testimonies of those they are studying. Over the course of a study, conclusions are drawn by compiling, comparing and evaluating the participants’ feedback and input. Qualitative research is often focused on answering the “why” behind a phenomenon, correlation or behavior.
In contrast, quantitative data are analyzed numerically to develop a statistical picture of a trend or connection. Such statistical results may shed light on cause-and-effect relationships, and they may either confirm or disprove the study’s original hypothesis. Whether positive or negative, the outcome can enrich understanding of a subject and spark action. Quantitative research is often focused on answering the questions of “what” or “how” in regards to a phenomenon, correlation or behavior.
Benefits and Limitations of Qualitative vs. Quantitative Research
Another difference between qualitative and quantitative research lies in their advantages and limitations. Each form of research has benefits and shortcomings. Researchers must consider their hypotheses and what forms of data collection and analysis are likely to produce the most relevant findings.
Benefits of Qualitative Research
There are some significant benefits of qualitative research that should be considered when evaluating the difference between qualitative and quantitative research. The qualitative method allows for creativity, varied interpretations and flexibility. The scope of the research project can change as more information is gathered.
Limitations of Qualitative Research
Qualitative studies are more subjective in their results and interpretation than are quantitative studies. The expertise and perspective of the researcher may strongly influence the interpretation of results and the conclusions reached, because personal bias can be hard to manage. In addition, qualitative studies often test a smaller sample size due to the costs and efforts associated with qualitative data collection methods.1
Benefits of Quantitative Research
The similarities of qualitative and quantitative research do not encompass their respective benefits, because each approach has unique advantages. For example, unlike qualitative studies, quantitative studies produce objective data, and their results can be clearly communicated through statistics and numbers. Quantitative studies can be quickly analyzed with the benefit of data computing software.
Limitations of Quantitative Research
Yet, although objectivity is a benefit of the quantitative method, this approach can be viewed as a more restrictive form of study. Participants cannot tailor their responses or add context. Furthermore, statistical analysis requires a large data sample, which calls for a large pool of participants.1
How To Analyze Qualitative vs. Quantitative Data
Another of the similarities of qualitative and quantitative research is that both look for patterns in the data they collect that point to a relationship between elements. Both qualitative and quantitative data are instrumental in supporting existing theories and developing new ones. Ultimately, the researcher must determine which kind of research best serves the goals of their study.
Analyzing Qualitative Data
Because qualitative data doesn’t allow for numerical data analysis, any analytical approach must be developed with care and caution. Here are a few different methods of qualitative data analysis, as follows:
- Content analysis: Groups together similar concepts, themes and words that emerge from the data in order to understand interrelationships
- Discourse analysis: Evaluates the way in which people often express themselves in various contexts through the lens of cultural and power dynamics
- Thematic analysis: Seeks to understand the true meaning behind subjects’ words by uncovering recurrent themes in the data
Analyzing Quantitative Data
The question of how to analyze quantitative data is slightly more straightforward compared to the various approaches for qualitative data. When working with quantitative data, doctoral researchers will generally review the collected data and organize it into visual elements, such as charts and graphs.
The data can be evaluated using either descriptive or inferential statistics. Descriptive statistics provide an avenue for describing the population or data set. Inferential statistics can be used to generalize results, as well as to project future trends or predictions about a larger dataset or population.
Become a Qualitative or Quantitative Researcher
Some researchers choose to adhere to and hone a single methodological approach throughout their time as doctoral learners — or in their profession. Research skills are critical in a variety of careers.
If you have a desire to conduct research, a qualitative or quantitative doctoral degree can support your initiative. Throughout your program, you will learn methods for constructing a qualitative or quantitative study and producing written research findings.
1 Mcleod, S. (2023, May 10). Qualitative vs quantitative research: methods & data analysis. Simply Psychology. Retrieved in May 2023.
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What Is a Short Story?
A short story is a work of short, narrative prose that is usually centered around one single event. It is limited in scope and has an introduction, body and conclusion. Although a short story has much in common with a novel (See How to Analyze a Novel), it is written with much greater precision. You will often be asked to write a literary analysis. An analysis of a short story requires basic knowledge of literary elements. The following guide and questions may help you:
Setting
Setting is a description of where and when the story takes place. In a short story there are fewer settings compared to a novel. The time is more limited. Ask yourself the following questions:
- How is the setting created? Consider geography, weather, time of day, social conditions, etc.
- What role does setting play in the story? Is it an important part of the plot or theme? Or is it just a backdrop against which the action takes place?
Study the time period, which is also part of the setting, and ask yourself the following:
- When was the story written?
- Does it take place in the present, the past, or the future?
- How does the time period affect the language, atmosphere or social circumstances of the short story?
Characterization
Characterization deals with how the characters in the story are described. In short stories there are usually fewer characters compared to a novel. They usually focus on one central character or protagonist. Ask yourself the following:
- Who is the main character?
- Are the main character and other characters described through dialogue – by the way they speak (dialect or slang for instance)?
- Has the author described the characters by physical appearance, thoughts and feelings, and interaction (the way they act towards others)?
- Are they static/flat characters who do not change?
- Are they dynamic/round characters who DO change?
- What type of characters are they? What qualities stand out? Are they stereotypes?
- Are the characters believable?
Plot and structure
The plot is the main sequence of events that make up the story. In short stories the plot is usually centered around one experience or significant moment. Consider the following questions:
- What is the most important event?
- How is the plot structured? Is it linear, chronological or does it move around?
- Is the plot believable?
Narrator and Point of view
The narrator is the person telling the story. Consider this question: Are the narrator and the main character the same?
By point of view we mean from whose eyes the story is being told. Short stories tend to be told through one character's point of view. The following are important questions to consider:
- Who is the narrator or speaker in the story?
- Does the author speak through the main character?
- Is the story written in the first person "I" point of view?
- Is the story written in a detached third person "he/she" point of view?
- Is there an "all-knowing" third person who can reveal what all the characters are thinking and doing at all times and in all places?
Conflict
Conflict or tension is usually the heart of the short story and is related to the main character. In a short story there is usually one main struggle.
- How would you describe the main conflict?
- Is it an internal conflict within the character?
- Is it an external conflict caused by the surroundings or environment the main character finds himself/herself in?
Climax
The climax is the point of greatest tension or intensity in the short story. It can also be the point where events take a major turn as the story races towards its conclusion. Ask yourself:
- Is there a turning point in the story?
- When does the climax take place?
Theme
The theme is the main idea, lesson, or message in the short story. It may be an abstract idea about the human condition, society, or life. Ask yourself:
- How is the theme expressed?
- Are any elements repeated and therefore suggest a theme?
- Is there more than one theme?
Style
The author's style has to do with the his or her vocabulary, use of imagery, tone, or the feeling of the story. It has to do with the author's attitude toward the subject. In some short stories the tone can be ironic, humorous, cold, or dramatic.
- Is the author's language full of figurative language?
- What images are used?
- Does the author use a lot of symbolism? Metaphors (comparisons that do not use "as" or "like") or similes (comparisons that use "as" or "like")?
Your literary analysis of a short story will often be in the form of an essay where you may be asked to give your opinions of the short story at the end. Choose the elements that made the greatest impression on you. Point out which character/characters you liked best or least and always support your arguments.