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What’s the difference between qualitative and quantitative research?

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❶Describe the uses of quantitative research design. Thanks for the clear and wonderful distinction between the two research methods.

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This pin never expires. Select an expiration date. About Us Contact Us. Search Community Search Community. An Overview of Quantitative Research This modules provides a basic overview of quantitative research, including its key characteristics and advantages.

Describe the uses of quantitative research design. Provide examples of when quantitative research methodology should be used. Discuss the strengths and weaknesses of quantitative research. The data collected is numeric, allowing for collection of data from a large sample size.

Statistical analysis allows for greater objectivity when reviewing results and therefore, results are independent of the researcher. Numerical results can be displayed in graphs, charts, tables and other formats that allow for better interpretation.

Data analysis is less time-consuming and can often be done using statistical software. Results can be generalized if the data are based on random samples and the sample size was sufficient. Data collection methods can be relatively quick, depending on the type of data being collected. Numerical quantitative data may be viewed as more credible and reliable, especially to policy makers, decision makers, and administrators. How often do college students between the ages of access Facebook?

Quantitative research design also tends to generate only proved or unproven results, with there being very little room for grey areas and uncertainty. For the social sciences, education, anthropology and psychology, human nature is a lot more complex than just a simple yes or no response. Check out our quiz-page with tests about:. Martyn Shuttleworth Mar 7, Retrieved Sep 12, from Explorable.

The text in this article is licensed under the Creative Commons-License Attribution 4. You can use it freely with some kind of link , and we're also okay with people reprinting in publications like books, blogs, newsletters, course-material, papers, wikipedia and presentations with clear attribution. Quantitative and Qualitative Research. Want the full version to study at home, take to school or just scribble on? Whether you are an academic novice, or you simply want to brush up your skills, this book will take your academic writing skills to the next level.

Don't have time for it all now? No problem, save it as a course and come back to it later. Share this page on your website: This article is a part of the guide: Select from one of the other courses available: Don't miss these related articles:. Check out our quiz-page with tests about: Make sure you do not invade privacy? Avoid asking questions just because you can - make sure they are completely relevant to your study: As you can see there is a long list.

There are many mistakes that are apparent in questionnaires used by people and sometimes even with figures in published research. It is not so easy to design a questionnaire. As well as avoiding all the points above, you need to make some basic decisions and then create the questions appropriately.

A basic decision is between questionnaires that will be sent to people and questionnaires that will be used in an interview. In both cases, you have to follow all the rules above, but when the completion is done at a distance there is less chance to catch errors and to correct misunderstandings.

So questions have to be simple and logical and unbiased if they are to be sent to the person as in a survey. Often people are drawn to open-ended questions since they seem very simple to ask. Unfortunately, this simplicity may be its weakness when it comes to analysing the results. There are also problems in collecting qualitative responses at a distance, as people are often reluctant to write long essays on their feelings. It is often the case that we cannot determine whether people are just not prepared to write or have no special opinion.

Closed Questions or Fixed-choice Questions. These are more common in surveys or postal questionnaires. They can be of different types:. They are rather crude. Ranking questions where you ask the person to place numbers beside a series of ideas, statements, objects and so on. These can be more complex to analyse. Scale questions are usually simple and on a single scale.

Avoid offering different adjectives in the same question. The convention is to use equal intervals and 3 or 5 or 7 points. At the point where you start to generate the questions based on these guidelines, you are highly likely to forget your original intention. So go back to your original aim and make sure every question that you ask has some relevance to the original aim. This is so often a weakness of the whole process. Now having constructed a questionnaire, try it out.

Pilot work is vital and it has to cover both the content and the administration itself. Not only does the questionnaire have to work in terms of the content and the questions, but also you the researcher have to be able to use it effectively, smoothly and with complete confidence. You have to know exactly which question follows which and must be clear about what you can explain and what you cannot. Usually researchers can repeat questions but are not allowed to give for instances.

However, the limits of the information that can be given have to be set out in advance. You have to follow your own guidelines. Make sure the questionnaire is simple to administer.

A common problem is making an interview too long or too short. It can be too long because it is the first time you have used it - you can expect it to take twice as long on the first use. Or it can be too long, because the questions are too complex. Use the pilot study to reduce the overall length. It can be too short if you find that the questions are irrelevant to the person.

Job questions might not be appropriate if a person is a student, still at school or retired. Make sure you target your interviewees properly. More about survey sampling later. Perhaps the biggest issue for us is how to translate a questionnaire into BSL.

We have no fixed rules but after 20 years of doing this, I can explain what we believe to be "best practice". In order to use a survey, the researcher should have a clear idea of the type of data and the underlying rationale for the approach. In simple terms, surveys are positivistic. This means that they imply a reality in the data. They assume that what you are told is the truth and is an objective and verifiable reality.

In some ways, this is too simple but as a starting point it is important. The approach is scientific as it expects the work to arise in a theory. The theory is a set of expectations based on unifying principles - rules or laws. The scientist using a survey, generates a hypothesis from the research question - Deaf women are more likely to move from one part of the country than Deaf men; or Deaf young people are more likely to smoke if they have been to deaf school than if they have been in mainstream unit.

The survey is then constructed around certain assumptions. These are quite simple - that the answers people give are reliable will be produced in the same way if requested in consecutive weeks are mostly independent of subject variables like mood and illness and that the differences which occur are due to the real effects of the underlying variables, e.

These are assumptions, not truths. How strongly you can adhere to them varies according to your purpose and the context. This aspect is a whole science on its own. It is highly statistical and often governed by complex mathematical theory and calculation. Much more on it can be found in books in the library, with titles such as "Sampling Theory. For our purposes, there are some simple divisions.

Sampling is designed to ensure representativeness and to allow us to claim reliability. Where a population is available and easy to access, then a random sample can be constructed.

The key here is on the accessibility. In a village, all the householders can be contacted from the voter's roll the list of people eligible to vote stored in the public library. The researcher can choose a fixed number of people and then choose them with a set of random numbers and their position on the voter's roll. Random samples are vital in physical science and are achievable because the variables are under complete control.

When we deal with people, the same is not the case and it becomes much harder to use this form of sampling.

In order to get around it, sometimes, stratified sampling is used. This uses information about the population in order to make the randomisation less broad - so perhaps there are more people who are professionals than unemployed or people in unskilled jobs. So the random samples are chosen inside these strata and not across the whole population. The sampling is then balanced to represent the different types of job.

There are various types of non-probability sampling. A common one, and one that is appropriate in the case of the Deaf community, is quota sampling.

This is a technique often used in market research, where the background characteristics of the population are known and these are used to extract a quota in order to make specific comparisons. It is like stratified sampling, except specific numbers of each type within the population or the types which are of interest, are chosen and the researcher targets those people alone.

An example might be a target of 20 mothers of children aged 5 and under and 20 mothers with children aged 6 years and up - in order to examine their pattern of Christmas present buying. The disadvantage of this method is that the interviewers tend to pick the easiest to reach and the quota is filled up with friends or people known to the researcher.

Another technique that is appropriate for minority groups living in unusual circumstances not in fixed geographical locations is to use a spreading search.

In this method, targeted key people provide access to other members of the community. For example, Deaf people list the names of the people they know in that group, and those people in turn tell of the people they know. So the process snowballs. Surveys are of different types. Traditionally, they were enumeration where hard facts were obtained - the Census is a good example, and the General Household Survey is another. These evolved, and surveys began to measure attitudes - people's perceptions and beliefs.

These were taken to reflect some inner or social reality and the groups of people who were chosen could be compared in terms of their expressed opinion. This type of principle evolved further to imply that attitude and behaviour could be linked causally. People who believed one thing were more likely to behave consistently with this belief. These are very strong ideas underpinning the survey approach. There are three main approaches to take: This approach has the advantage of simplicity and ease of data collection.

It is also fraught with many problems.

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Quantitative research methods describe and measure the level of occurrences on the basis of numbers and calculations. Moreover, the questions of “how many?”.

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Quantitative methods emphasize objective measurements and the statistical, mathematical, or numerical analysis of data collected through polls, questionnaires, and surveys, or by manipulating pre-existing statistical data using computational techniques. Quantitative research focuses on gathering.

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1 Introduction to quantitative research What is quantitative research? Research methods in education (and the other social sciences) are often. What’s the difference between qualitative and quantitative research? Susan E. DeFranzo September 16, Many times those that undertake a research project often find they are not aware of the differences between Qualitative Research and Quantitative Research methods.

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Learn about the distinction between quantitative and qualitative methods of research, and some advantages and disadvantages of each. Overview of Quantitative Methods An Overview of Quantitative Research This modules provides a basic overview of quantitative research, including its .