The Classic Wanderer

What Is A Descriptive Study In Psychology?

• Sabrina Sarro
• 05.05.2023
• 0
• 16

– Descriptive research methods are scientific tools used by researchers and psychologists for gathering information and describing the specifics of behaviors, patterns, and other phenomena. These methods focus on the who, what, and where, versus the why or how.

Correlational research: examines two variables at once, and may be used to identify patterns of relationships Experimental research: determines cause and effect by exposing one group to a particular variable, while another is not exposed to the variable

Descriptive research does not typically rely on a hypothesis and may be more flexible than the other types of psychological research. This type of research can act as a springboard for further exploration by allowing scientists to gather information needed to form a hypothesis. That hypothesis could then serve as the basis for a correlational study or a formal experiment.

What is a descriptive study in psychology example?

Descriptive Research: Assessing the Current State of Affairs – Descriptive research is designed to create a snapshot of the current thoughts, feelings, or behavior of individuals. This section reviews three types of descriptive research: case studies, surveys, and naturalistic observation,

• Sometimes the data in a descriptive research project are based on only a small set of individuals, often only one person or a single small group.
• These research designs are known as case studies — descriptive records of one or more individual’s experiences and behavior,
• Sometimes case studies involve ordinary individuals, as when developmental psychologist Jean Piaget used his observation of his own children to develop his stage theory of cognitive development.

More frequently, case studies are conducted on individuals who have unusual or abnormal experiences or characteristics or who find themselves in particularly difficult or stressful situations. The assumption is that by carefully studying individuals who are socially marginal, who are experiencing unusual situations, or who are going through a difficult phase in their lives, we can learn something about human nature.

Sigmund Freud was a master of using the psychological difficulties of individuals to draw conclusions about basic psychological processes. Freud wrote case studies of some of his most interesting patients and used these careful examinations to develop his important theories of personality. One classic example is Freud’s description of “Little Hans,” a child whose fear of horses the psychoanalyst interpreted in terms of repressed sexual impulses and the Oedipus complex (Freud (1909/1964).

Figure 2.4 Political polls reported in newspapers and on the Internet are descriptive research designs that provide snapshots of the likely voting behavior of a population. Another well-known case study is Phineas Gage, a man whose thoughts and emotions were extensively studied by cognitive psychologists after a railroad spike was blasted through his skull in an accident.

• Although there is question about the interpretation of this case study (Kotowicz, 2007), it did provide early evidence that the brain’s frontal lobe is involved in emotion and morality (Damasio et al., 2005).
• An interesting example of a case study in clinical psychology is described by Rokeach (1964), who investigated in detail the beliefs and interactions among three patients with schizophrenia, all of whom were convinced they were Jesus Christ.

In other cases the data from descriptive research projects come in the form of a survey — a measure administered through either an interview or a written questionnaire to get a picture of the beliefs or behaviors of a sample of people of interest, The people chosen to participate in the research (known as the sample ) are selected to be representative of all the people that the researcher wishes to know about (the population ).

In election polls, for instance, a sample is taken from the population of all “likely voters” in the upcoming elections. The results of surveys may sometimes be rather mundane, such as “Nine out of ten doctors prefer Tymenocin,” or “The median income in Montgomery County is $36,712.” Yet other times (particularly in discussions of social behavior), the results can be shocking: “More than 40,000 people are killed by gunfire in the United States every year,” or “More than 60% of women between the ages of 50 and 60 suffer from depression.” Descriptive research is frequently used by psychologists to get an estimate of the prevalence (or incidence ) of psychological disorders.

A final type of descriptive research—known as naturalistic observation —is research based on the observation of everyday events, For instance, a developmental psychologist who watches children on a playground and describes what they say to each other while they play is conducting descriptive research, as is a biopsychologist who observes animals in their natural habitats.

One example of observational research involves a systematic procedure known as the strange situation, used to get a picture of how adults and young children interact. The data that are collected in the strange situation are systematically coded in a coding sheet such as that shown in Table 2.3 “Sample Coding Form Used to Assess Child’s and Mother’s Behavior in the Strange Situation”,

Table 2.3 Sample Coding Form Used to Assess Child’s and Mother’s Behavior in the Strange Situation

Coder name: Olive
	Coding categories
Episode	Proximity	Contact	Resistance	Avoidance
Mother and baby play alone	1	1	1	1
Mother puts baby down	4	1	1	1
Stranger enters room	1	2	3	1
Mother leaves room; stranger plays with baby	1	3	1	1
Mother reenters, greets and may comfort baby, then leaves again	4	2	1	2
Stranger tries to play with baby	1	3	1	1
Mother reenters and picks up baby	6	6	1	2
Coding categories explained
Proximity	The baby moves toward, grasps, or climbs on the adult.
Maintaining contact	The baby resists being put down by the adult by crying or trying to climb back up.
Resistance	The baby pushes, hits, or squirms to be put down from the adult’s arms.
Avoidance	The baby turns away or moves away from the adult.
This table represents a sample coding sheet from an episode of the “strange situation,” in which an infant (usually about 1 year old) is observed playing in a room with two adults—the child’s mother and a stranger. Each of the four coding categories is scored by the coder from 1 (the baby makes no effort to engage in the behavior) to 7 (the baby makes a significant effort to engage in the behavior). More information about the meaning of the coding can be found in Ainsworth, Blehar, Waters, and Wall (1978).

Stangor, C. (2011). Research methods for the behavioral sciences (4th ed.). Mountain View, CA: Cengage. The results of descriptive research projects are analyzed using descriptive statistics — numbers that summarize the distribution of scores on a measured variable,

Most variables have distributions similar to that shown in Figure 2.5 “Height Distribution”, where most of the scores are located near the center of the distribution, and the distribution is symmetrical and bell-shaped. A data distribution that is shaped like a bell is known as a normal distribution,

Table 2.4 Height and Family Income for 25 Students

Student name	Height in inches	Family income in dollars
Lauren	62	48,000
Courtnie	62	57,000
Leslie	63	93,000
Renee	64	107,000
Katherine	64	110,000
Jordan	65	93,000
Rabiah	66	46,000
Alina	66	84,000
Young Su	67	68,000
Martin	67	49,000
Hanzhu	67	73,000
Caitlin	67	3,800,000
Steven	67	107,000
Emily	67	64,000
Amy	68	67,000
Jonathan	68	51,000
Julian	68	48,000
Alissa	68	93,000
Christine	69	93,000
Candace	69	111,000
Xiaohua	69	56,000
Charlie	70	94,000
Timothy	71	73,000
Ariane	72	70,000
Logan	72	44,000

Figure 2.5 Height Distribution The distribution of the heights of the students in a class will form a normal distribution. In this sample the mean ( M ) = 67.12 and the standard deviation ( s ) = 2.74. A distribution can be described in terms of its central tendency —that is, the point in the distribution around which the data are centered—and its dispersion, or spread.

The arithmetic average, or arithmetic mean, is the most commonly used measure of central tendency, It is computed by calculating the sum of all the scores of the variable and dividing this sum by the number of participants in the distribution (denoted by the letter N ). In the data presented in Figure 2.5 “Height Distribution”, the mean height of the students is 67.12 inches.

The sample mean is usually indicated by the letter M, In some cases, however, the data distribution is not symmetrical. This occurs when there are one or more extreme scores (known as outliers ) at one end of the distribution. Consider, for instance, the variable of family income (see Figure 2.6 “Family Income Distribution” ), which includes an outlier (a value of $3,800,000).

• In this case the mean is not a good measure of central tendency.
• Although it appears from Figure 2.6 “Family Income Distribution” that the central tendency of the family income variable should be around $70,000, the mean family income is actually $223,960.
• The single very extreme income has a disproportionate impact on the mean, resulting in a value that does not well represent the central tendency.

The median is used as an alternative measure of central tendency when distributions are not symmetrical. The median is the score in the center of the distribution, meaning that 50% of the scores are greater than the median and 50% of the scores are less than the median, The distribution of family incomes is likely to be nonsymmetrical because some incomes can be very large in comparison to most incomes. In this case the median or the mode is a better indicator of central tendency than is the mean. A final measure of central tendency, known as the mode, represents the value that occurs most frequently in the distribution,

You can see from Figure 2.6 “Family Income Distribution” that the mode for the family income variable is $93,000 (it occurs four times). In addition to summarizing the central tendency of a distribution, descriptive statistics convey information about how the scores of the variable are spread around the central tendency.

Dispersion refers to the extent to which the scores are all tightly clustered around the central tendency, like this: Figure 2.7 Or they may be more spread out away from it, like this: Figure 2.8 One simple measure of dispersion is to find the largest (the maximum ) and the smallest (the minimum ) observed values of the variable and to compute the range of the variable as the maximum observed score minus the minimum observed score. You can check that the range of the height variable in Figure 2.5 “Height Distribution” is 72 – 62 = 10.

The standard deviation, symbolized as s, is the most commonly used measure of dispersion, Distributions with a larger standard deviation have more spread. The standard deviation of the height variable is s = 2.74, and the standard deviation of the family income variable is s = $745,337. An advantage of descriptive research is that it attempts to capture the complexity of everyday behavior.

Case studies provide detailed information about a single person or a small group of people, surveys capture the thoughts or reported behaviors of a large population of people, and naturalistic observation objectively records the behavior of people or animals as it occurs naturally.

• Thus descriptive research is used to provide a relatively complete understanding of what is currently happening.
• Despite these advantages, descriptive research has a distinct disadvantage in that, although it allows us to get an idea of what is currently happening, it is usually limited to static pictures.

Although descriptions of particular experiences may be interesting, they are not always transferable to other individuals in other situations, nor do they tell us exactly why specific behaviors or events occurred. For instance, descriptions of individuals who have suffered a stressful event, such as a war or an earthquake, can be used to understand the individuals’ reactions to the event but cannot tell us anything about the long-term effects of the stress.

What type of study is a descriptive study?

WHAT IS A DESCRIPTIVE STUDY? – A descriptive study is one that is designed to describe the distribution of one or more variables, without regard to any causal or other hypothesis.

What is descriptive study in simple words?

Descriptive research aims to accurately and systematically describe a population, situation or phenomenon. It can answer what, where, when and how questions, but not why questions. A descriptive research design can use a wide variety of research methods to investigate one or more variables.

What is descriptive vs experimental in psychology?

Definition –

Descriptive research is a method that describes a study or a topic. It defines the characteristics of the variable under research and answers the questions related to it. Whereas experimental research is a scientific approach to testing a theory or a hypothesis using experimental groups and control variables.

Can you give another 3 examples of descriptive type of research?

What are the methods of conducting descriptive research? – Primarily, there are three descriptive research methods:

1. Observation,
2. Survey, &
3. Case Study

We have explained how you can conduct this research type in three different ways. Each method helps gather descriptive data and sets the scene for thorough research.

Is descriptive research qualitative or quantitative?

3. Data Collection Techniques – Descriptive research typically involves the collection of both qualitative and quantitative data through methods such as surveys, observational studies, case studies, or focus groups.

How do you know if a study is descriptive?

Descriptive Studies A descriptive study is one in which information is collected without changing the environment (i.e., nothing is manipulated). Sometimes these are referred to as correlational or observational studies. The Office of Human Research Protections (OHRP) defines a descriptive study as Any study that is not truly experimental. In human research, a descriptive study can provide information about the naturally occurring health status, behavior, attitudes or other characteristics of a particular group. Descriptive studies are also conducted to demonstrate associations or relationships between things in the world around you. Descriptive studies can involve a one-time interaction with groups of people ( cross-sectional study ) or a study might follow individuals over time ( longitudinal study ). Descriptive studies, in which the researcher interacts with the participant, may involve surveys or interviews to collect the necessary information. Descriptive studies in which the researcher does not interact with the participant include observational studies of people in an environment and studies involving data collection using existing records (e.g., medical record review). Case example of a descriptive study Descriptive studies are usually the best methods for collecting information that will demonstrate relationships and describe the world as it exists. These types of studies are often done before an experiment to know what specific things to manipulate and include in an experiment. Bickman and Rog (1998) suggest that descriptive studies can answer questions such as “what is” or “what was.” Experiments can typically answer “why” or “how.” previous next

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Is a descriptive study the same as a qualitative study?

Sampling – Most qualitative research aligns itself with non-probability sampling and descriptive research is no different. Descriptive research generally uses purposive sampling and a range of purposive sampling techniques have been described ( Palinkas et al., 2015 ).

1. Many researchers use a combination of approaches such as convenience, opportunistic or snowball sampling as part of the sampling framework, which is determined by the desired sample and the phenomena being studied.
2. Purposive sampling refers to selecting research participants that can speak to the research aims and who have knowledge and experience of the phenomenon under scrutiny ( Ritchie et al., 2014 ).

When purposive sampling is used in a study it delimits and narrows the study population; however, researchers need to remember that other characteristics of the sample will also affect the population, such as the location of the researcher and their flexibility to recruit participants from beyond their base.

In addition, the heterogeneity of the population will need to be considered and how this might influence sampling and subsequent data collection and analysis ( Palinkas et al,, 2015 ). Take, for example, conducting research on the experience of caring for people with Alzheimer’s disease (AD). For the most part AD is a condition that affects older people and experiences of participants caring for older people will ultimately dominate the sample.

However, AD also affects younger people and how this will impact on sampling needs to be considered before recruitment as both groups will have very different experiences, although there will be overlap. Teddlie and Fu (2007) suggest that although some purposive sampling techniques generate representative cases, most result in describing contrasting cases, which they argue are at the heart of qualitative analysis.

To achieve this, Sandelowski (2010) suggests that maximum variation sampling is particularly useful in qualitative descriptive research, which may acknowledge the range of experiences that exist especially in healthcare research. Palinkas et al, (2015) describe maximum variation sampling as identifying shared patterns that emerge from heterogeneity.

In other words, researchers attempt to include a wide range of participants and experiences when collecting data. This may be more difficult to achieve in areas where little is known about the substantive area and may depend on the researcher’s knowledge and immersion within the subject area.

Sample size will also need to be considered and although small sample sizes are common in qualitative descriptive research, researchers need to be careful they have enough data collected to meet the study aims ( Ritchie et al., 2014 ). Pre-determining the sample size prior to data collection may stifle the analytic process, resulting in too much or too little data.

Traditionally, the gold standard for sample size in qualitative research is data saturation, which differs depending on the research design and the size of the population ( Fusch and Ness, 2015 ). Data saturation is reached ‘when there is enough information to replicate the study, when the ability to obtain additional new information has been attained, and when further coding is no longer feasible’ ( Fusch and Ness, 2015, p.1408).

• However, some argue that although saturation is often reported, it is rarely demonstrated in qualitative descriptive research reports ( Caelli et al., 2003 ; Malterud et al., 2016 ).
• If data saturation is used to determine sample size, it is suggested that greater emphasis be placed on demonstrating how saturation was reached and at what level to provide more credibility to sample sizes ( Caelli et al., 2003 ).

Sample size calculation should be an estimate until saturation has been achieved through the concurrent processes of data collection and analysis. Where saturation has not been achieved, or where sample size has been predetermined for resource reasons, this should be clearly acknowledged.

However, there is also a movement away from the reliance on data saturation as a measure of sample size in qualitative research ( Malterud et al., 2016 ). O’Reilly and Parker (2012) question the appropriateness of the rigid application of saturation as a sample size measure arguing that outside of Grounded Theory, its use is inconsistent and at times questionable.

Malterud et al. (2016) focus instead on the concept of ‘information power’ to determine sample size. Here, they suggest sample size is determined by the amount of information the sample holds relevant to the actual study rather than the number of participants ( Malterud et al., 2016 ).

How do you know if a research is descriptive?

Descriptive research is a type of research that is used to describe the characteristics of a population. It collects data that are used to answer a wide range of what, when, and how questions pertaining to a particular population or group. For example, descriptive studies might be used to answer questions such as: What percentage of Head Start teachers have a bachelor’s degree or higher? What is the average reading ability of 5-year-olds when they first enter kindergarten? What kinds of math activities are used in early childhood programs? When do children first receive regular child care from someone other than their parents? When are children with developmental disabilities first diagnosed and when do they first receive services? What factors do programs consider when making decisions about the type of assessments that will be used to assess the skills of the children in their programs? How do the types of services children receive from their early childhood program change as children age? Descriptive research does not answer questions about why a certain phenomenon occurs or what the causes are.

Answers to such questions are best obtained from randomized and quasi-experimental studies, However, data from descriptive studies can be used to examine the relationships (correlations) among variables. While the findings from correlational analyses are not evidence of causality, they can help to distinguish variables that may be important in explaining a phenomenon from those that are not.

Thus, descriptive research is often used to generate hypotheses that should be tested using more rigorous designs. A variety of data collection methods may be used alone or in combination to answer the types of questions guiding descriptive research. Some of the more common methods include surveys, interviews, observations, case studies, and portfolios.

The data collected through these methods can be either quantitative or qualitative. Quantitative data are typically analyzed and presenting using descriptive statistics, Using quantitative data, researchers may describe the characteristics of a sample or population in terms of percentages (e.g., percentage of population that belong to different racial/ethnic groups, percentage of low-income families that receive different government services) or averages (e.g., average household income, average scores of reading, mathematics and language assessments).

Quantitative data, such as narrative data collected as part of a case study, may be used to organize, classify, and used to identify patterns of behaviors, attitudes, and other characteristics of groups. Descriptive studies have an important role in early care and education research.

Studies such as the National Survey of Early Care and Education and the National Household Education Surveys Program have greatly increased our knowledge of the supply of and demand for child care in the U.S. The Head Start Family and Child Experiences Survey and the Early Childhood Longitudinal Study Program have provided researchers, policy makers and practitioners with rich information about school readiness skills of children in the U.S.

Each of the methods used to collect descriptive data have their own strengths and limitations. The following are some of the strengths and limitations of descriptive research studies in general. Strengths:

Study participants are questioned or observed in a natural setting (e.g., their homes, child care or educational settings). Study data can be used to identify the prevalence of particular problems and the need for new or additional services to address these problems. Descriptive research may identify areas in need of additional research and relationships between variables that require future study. Descriptive research is often referred to as “hypothesis generating research.” Depending on the data collection method used, descriptive studies can generate rich datasets on large and diverse samples.

Limitations:

Descriptive studies cannot be used to establish cause and effect relationships. Respondents may not be truthful when answering survey questions or may give socially desirable responses. The choice and wording of questions on a questionnaire may influence the descriptive findings. Depending on the type and size of sample, the findings may not be generalizable or produce an accurate description of the population of interest.

What is the difference between descriptive and experimental research?

Conclusion – Descriptive and experimental research are two significant types of research. Both these research types are helpful in analysing certain occurrences and study groups. The main difference between descriptive and experimental research is that descriptive research describes the characteristics of the research subject while the experimental research manipulates the research subject or the variables to come to a conclusion.

What is the goal of descriptive research?

The goal of descriptive research is to describe a phenomenon and its characteristics. This research is more concerned with what rather than how or why something has happened. Therefore, observation and survey tools are often used to gather data (Gall, Gall, & Borg, 2007).

What is an example of a descriptive case study?

An example of a descriptive case study is the journalistic description of the Watergate scandal by two reporters (Yin, 1984). The challenge of a descriptive case study is that the researcher must begin with a descriptive theory to support the description of the phenomenon or story.

What are descriptive methods used in psychology?

Psychologists use descriptive, experimental, and correlational methods to conduct research. Descriptive, or qualitative, methods include the case study, naturalistic observation, surveys, archival research, longitudinal research, and cross-sectional research.

• Experiments are conducted in order to determine cause-and-effect relationships.
• In ideal experimental design, the only difference between the experimental and control groups is whether participants are exposed to the experimental manipulation.
• Each group goes through all phases of the experiment, but each group will experience a different level of the independent variable: the experimental group is exposed to the experimental manipulation, and the control group is not exposed to the experimental manipulation.

The researcher then measures the changes that are produced in the dependent variable in each group. Once data is collected from both groups, it is analyzed statistically to determine if there are meaningful differences between the groups. When scientists passively observe and measure phenomena it is called correlational research.

Here, psychologists do not intervene and change behavior, as they do in experiments. In correlational research, they identify patterns of relationships, but usually cannot infer what causes what. Importantly, with correlational research, you can examine only two variables at a time, no more and no less.

https://assessments.lumenlearning.com/assessments/2706 There are many research methods available to psychologists in their efforts to understand, describe, and explain behavior and the cognitive and biological processes that underlie it. Some methods rely on observational techniques.

1. Other approaches involve interactions between the researcher and the individuals who are being studied—ranging from a series of simple questions to extensive, in-depth interviews—to well-controlled experiments.
2. The three main categories of psychological research are descriptive, correlational, and experimental research.

Research studies that do not test specific relationships between variables are called descriptive, or qualitative, studies, These studies are used to describe general or specific behaviors and attributes that are observed and measured. In the early stages of research it might be difficult to form a hypothesis, especially when there is not any existing literature in the area.

• In these situations designing an experiment would be premature, as the question of interest is not yet clearly defined as a hypothesis.
• Often a researcher will begin with a non-experimental approach, such as a descriptive study, to gather more information about the topic before designing an experiment or correlational study to address a specific hypothesis.

Video 1. Descriptive Research Design provides explanation and examples for quantitative descriptive research. A closed-captioned version of this video is available here, Descriptive research is distinct from correlational research, in which psychologists formally test whether a relationship exists between two or more variables.

1. Experimental research goes a step further beyond descriptive and correlational research and randomly assigns people to different conditions, using hypothesis testing to make inferences about how these conditions affect behavior.
2. It aims to determine if one variable directly impacts and causes another.

Correlational and experimental research both typically use hypothesis testing, whereas descriptive research does not. Each of these research methods has unique strengths and weaknesses, and each method may only be appropriate for certain types of research questions.

• For example, studies that rely primarily on observation produce incredible amounts of information, but the ability to apply this information to the larger population is somewhat limited because of small sample sizes.
• Survey research, on the other hand, allows researchers to easily collect data from relatively large samples.

While this allows for results to be generalized to the larger population more easily, the information that can be collected on any given survey is somewhat limited and subject to problems associated with any type of self-reported data. Some researchers conduct archival research by using existing records.

• While this can be a fairly inexpensive way to collect data that can provide insight into a number of research questions, researchers using this approach have no control on how or what kind of data was collected.
• Correlational research can find a relationship between two variables, but the only way a researcher can claim that the relationship between the variables is cause and effect is to perform an experiment.

In experimental research, which will be discussed later in the text, there is a tremendous amount of control over variables of interest. While this is a powerful approach, experiments are often conducted in very artificial settings. This calls into question the validity of experimental findings with regard to how they would apply in real-world settings.

In addition, many of the questions that psychologists would like to answer cannot be pursued through experimental research because of ethical concerns. Regardless of the method of research, data collection will be necessary. The method of data collection selected will primarily depend on the type of information the researcher needs for their study; however, other factors, such as time, resources, and even ethical considerations can influence the selection of a data collection method.

All of these factors need to be considered when selecting a data collection method because each method has unique strengths and weaknesses. We will discuss the uses and assessment of the most common data collection methods: observation, surveys, archival data, and tests.

Does descriptive research have variables?

Descriptive Statistics – Statistics can be broadly divided into descriptive statistics and inferential statistics. Descriptive statistics give a summary about the sample being studied without drawing any inferences based on probability theory. Even if the primary aim of a study involves inferential statistics, descriptive statistics are still used to give a general summary.

1. When we describe the population using tools such as frequency distribution tables, percentages, and other measures of central tendency like the mean, for example, we are talking about descriptive statistics.
2. When we use a specific statistical test (e.g., Mann–Whitney U-test) to compare the mean scores and express it in terms of statistical significance, we are talking about inferential statistics.

Descriptive statistics can help in summarizing data in the form of simple quantitative measures such as percentages or means or in the form of visual summaries such as histograms and box plots. Descriptive statistics can be used to describe a single variable (univariate analysis) or more than one variable (bivariate/multivariate analysis).

Sorting/grouping and illustration/visual displays Summary statistics.

What is a descriptive design in a research?

What is Descriptive Research Design? – Descriptive research design is a type of research design that aims to systematically obtain information to describe a phenomenon, situation, or population. More specifically, it helps answer the what, when, where, and how questions regarding the research problem rather than the why.

A researcher can conduct this research using various methodologies. It predominantly employs quantitative data, although qualitative data is sometimes used for descriptive purposes. It is important to note that in the descriptive research method, the researcher does not control or manipulate any variables, unlike in experimental research.

Instead, the variables are only identified, observed, and measured. Surveys and observation are the most used method to conduct this research design. You can leverage online survey tools or offline survey tools to gather data as per your research objective.

Is cohort a descriptive study?

Descriptive cohort studies are primarily ‘descriptive’ compared to classical cohort studies, which are ‘analytic.’ They typically describe events occurring in a defined population over time rather than draw conclusions about associations or causation.

What are the strengths of descriptive research?

Strengths: – Descriptive research can provide an in-depth view of any topic we might want to study, and the level of detail that we can find in descriptive research is extremely valuable. This is particularly true of descriptive research that is collected qualitatively.

Can you use survey in descriptive research?

What is descriptive research? – In descriptive research, the research investigates more than one variable. However, when you conduct this type of research, you cannot manipulate the variables present, unlike in experimental research. Descriptive research can only be conducted via survey, observation, and case Study.

Is descriptive research is structured or unstructured?

It is unstructured in nature. It generally involves the use of qualitative research.

What are the methods of descriptive research design?

What are the Data Collection Methods in Descriptive Research? – There are 3 main data collection methods in descriptive research, namely; observational method, case study method, and survey research.

What is an example of a descriptive case study?

An example of a descriptive case study is the journalistic description of the Watergate scandal by two reporters (Yin, 1984). The challenge of a descriptive case study is that the researcher must begin with a descriptive theory to support the description of the phenomenon or story.

What is an example of a descriptive research topic?

8.4.2 Descriptive Research – Descriptive research is about finding the answers to the Who? What? Where? When? How? and How many? questions. In descriptive research, in comparison to exploratory research, you have a clearer idea of what is needed and are looking for answers to more clearly defined questions.

What is an example of a descriptive study question?

Descriptive research questions Put simply, it’s the easiest way to quantify the particular variable(s) you’re interested in on a large scale. Common descriptive research questions will begin with ‘How much?’, ‘How regularly?’, ‘What percentage?’, ‘What time?’, ‘What is?’

What are some examples of descriptive methods?

Types of descriptive research – There are several types of descriptive study. The most well-known include cross-sectional studies, census surveys, sample surveys, case reports, and comparison studies.


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