Article Analysis 2 For this analysis, you will read an assigned article as before.  Here is a link to the article.  Download Here is a link to the article

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Article Analysis 2 For this analysis, you will read an assigned article as before.  Here is a link to the article.  Download Here is a link to the article. Please download it so that you can locate the page numbers when asked to do so in the assignment.  You will complete a structured handout as before.  Here is a link to the handout Download Here is a link to the handout.  Please enter your answers on the handout, save and upload when you are done.  The assignment asks you to consider an important issue for all types of empirical studies, and that is the issue of generalizability.  One advantage of quantitative studies that use large, randomly drawn samples is that the sample is representative of the larger population from which it is drawn.  Qualitative studies do not usually have this advantage.  Here is a short, easy to read comparison of quantitative and qualitative methods–be sure to read how McLeod explains the issue of transferable or generalizable findings. Download

Be sure to read the instructions very carefully and ask questions in advance if there is something you do not understand.  The assigned article is short, but you should give yourself time to read it and think about the differences between qualitative research and quantitative research. What’s the difference between qualitative and
quantitative research?
By Saul McLeod, updated 2019

There exists a fundamental distinction between two types of data:

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.

Qualitative Research

Qualitative research is empirical research where the data are not in the form of numbers

(Punch, 1998, p. 4).

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)

An 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 the

behaviourists (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 what it is to be human. Exploring the experience of

participants is known as a phenomenological approach (re: Humanism).

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.

Research following a qualitative approach is exploratory and seeks to explain ‘how’ and ‘why’

a particular phenomenon, or behaviour, operates as it does in a particular context.

Methods (used to obtain qualitative data)

Qualitative researchers use a variety of methods to develop deep understandings of how

people perceive their social realities and in consequence, how they act within the social


For example, diary accounts, open-ended questionnaires, documents, participant

observation, and ethnography.

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)

A good example of a qualitative research method would be unstructured interviews which

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.

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.

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.

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


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.

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 any confidence

The time required for data collection, analysis and interpretation are lengthy. Analysis of

qualitative data is difficult and expert knowledge of an area is necessary to try to interpret

qualitative data, and great care must be taken when doing so, for example, if looking for

symptoms of mental illness.

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.


Quantitative research gathers data in a numerical form which can be put into categories,

or in rank order, or measured in units of measurement. This type of data can be used to

construct graphs and tables of raw data.

Quantitative researchers aim to establish general laws of behaviour and phenonomon across

different settings/contexts. Research is used to test a theory and ultimately support or reject


Methods (used to obtain quantitative data)
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 the possible ways in which a research participant can react to

and express appropriate social behaviour.

Findings are therefore likely to be context-bound and simply a reflection of the assumptions

which the researcher brings to the investigation.

Data Analysis
Statistics help us turn quantitative data into useful information to help with decision

making. We can use statistics to summarise our data, describing patterns, relationships, and

connections. Statistics can be descriptive or inferential.

Descriptive statistics help us to summarise our data whereas inferential statistics are used to

identify statistically significant differences between groups of data (such as intervention and

control groups in a randomised 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 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.

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


Confirmation bias: The researcher might miss observing phenomena because of focus on

theory or hypothesis testing rather than on the theory of hypothesis generation.

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).

APA Style 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


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: Quantitatie and Qualitative

Approaches. London: Sage

Further Information

Research Data…

How to reference this article:
McLeod, S. A. (2019, July 30). Qualitative vs. quantitative research. Simply psychology:

Designing qualitative research

Methods of data collection and analysis

Introduction to quantitative and qualitative research

Content Analysis

Grounded Theory

Thematic Analysis

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