Why quantitative methods

Quantitative data collection methods include various forms of surveys — online surveys, paper surveys , mobile surveys and kiosk surveys, face-to-face interviews, telephone interviews, longitudinal studies, website interceptors, online polls, and systematic observations.

Snap Survey Software is the ideal survey platform and online research software where structured techniques such as large numbers of respondents and descriptive findings are required.

Snap has many robust features that will help your organization effectively gather and analyze quantitative data.

Customer resources , Survey analysis and reporting. Written by Susan E. Share on facebook. Share on twitter. Share on linkedin. Qualitative Research Qualitative Research is primarily exploratory research. Quantitative Research Quantitative Research is used to quantify the problem by way of generating numerical data or data that can be transformed into usable statistics.

Always tell the reader what to look for in tables and figures. Basic Research Design for Quantitative Studies Before designing a quantitative research study, you must decide whether it will be descriptive or experimental because this will dictate how you gather, analyze, and interpret the results. It covers the following information: Identifies the research problem -- as with any academic study, you must state clearly and concisely the research problem being investigated.

Reviews the literature -- review scholarship on the topic, synthesizing key themes and, if necessary, noting studies that have used similar methods of inquiry and analysis. Note where key gaps exist and how your study helps to fill these gaps or clarifies existing knowledge. Describes the theoretical framework -- provide an outline of the theory or hypothesis underpinning your study.

If necessary, define unfamiliar or complex terms, concepts, or ideas and provide the appropriate background information to place the research problem in proper context [e.

Study population and sampling -- where did the data come from; how robust is it; note where gaps exist or what was excluded. Note the procedures used for their selection; Data collection — describe the tools and methods used to collect information and identify the variables being measured; describe the methods used to obtain the data; and, note if the data was pre-existing [i. If you gathered it yourself, describe what type of instrument you used and why.

Note that no data set is perfect--describe any limitations in methods of gathering data. Data analysis -- describe the procedures for processing and analyzing the data.

If appropriate, describe the specific instruments of analysis used to study each research objective, including mathematical techniques and the type of computer software used to manipulate the data. Statistical analysis -- how did you analyze the data? What were the key findings from the data? The findings should be present in a logical, sequential order. Describe but do not interpret these trends or negative results; save that for the discussion section.

The results should be presented in the past tense. Interpretation of results -- reiterate the research problem being investigated and compare and contrast the findings with the research questions underlying the study.

Did they affirm predicted outcomes or did the data refute it? Description of trends, comparison of groups, or relationships among variables -- describe any trends that emerged from your analysis and explain all unanticipated and statistical insignificant findings. Discussion of implications — what is the meaning of your results? Highlight key findings based on the overall results and note findings that you believe are important. How have the results helped fill gaps in understanding the research problem?

Limitations -- describe any limitations or unavoidable bias in your study and, if necessary, note why these limitations did not inhibit effective interpretation of the results. Summary of findings — synthesize the answers to your research questions. Do not report any statistical data here; just provide a narrative summary of the key findings and describe what was learned that you did not know before conducting the study.

Recommendations — if appropriate to the aim of the assignment, tie key findings with policy recommendations or actions to be taken in practice. Strengths of Using Quantitative Methods Quantitative researchers try to recognize and isolate specific variables contained within the study framework, seek correlation, relationships and causality, and attempt to control the environment in which the data is collected to avoid the risk of variables, other than the one being studied, accounting for the relationships identified.

As a result, certain informants will refuse to participate Coen et al. In addition, it will generally be more difficult to protect the anonymity of informants in qualitative studies than when collective, quantitative methods are used such as various forms of questionnaire-based methods. Irrespective of whether this involves observations or interviews, the individuals will stand out in a direct and visible manner.

In personal interviews, the informant will recount previous experiences in his or her own words, which may be recognisable to others.

When designs for collective questioning are used, however, individual characteristics will be less identifiable, and individuals who have completed a questionnaire will not be directly visible. It is often assumed that the standardized methods and formalised requirements for quantitative research help ensure academic and ethical credibility. Even though there will be fewer subjective elements of error here than in qualitative research, there will be ample opportunities for dishonesty to render the research misleading even when quantitative methods are applied.

At worst, researchers may manipulate the data, use fictitious and fabricated data or discard any unwanted results. When research is undertaken in solitude and the researcher is alone in having insight into what is being done, the road to dishonesty lies open. Numerous examples of research fraud can be found, in both an historical and contemporary context.

These examples include academics who were held to be researchers of high stature, but in reality were untrustworthy. In educational psychology, Cyril Burt — represents an especially grave case. By fabricating and manipulating research data in his studies of twins, he could "confirm" his theory of heritability of intelligence. International academic literature contains innumerable descriptions of "The Cyril Burt Affair".

The essence of Burt's reprehensible acts consisted in the fact that many of the twins in his material did not exist, nor did many of the researchers with whom Burt had "collaborated". However, this scandal draws attention to the fact that the research community has traditionally been closed and disinclined towards openness, including with regard to potential risk factors, and thus underscores the need for a clear focus on values as well as for increased transparency and monitoring.

In light of what we know about dishonesty, two self-evident countermeasures are commonly identified: first, to strengthen the monitoring, and second, to raise the ethical standard. The question is what we can do to develop these areas further. There can hardly be any doubt that the monitoring is often of a superficial nature.

Those who have funded research are often content to receive some research reports, and unannounced observations of the research process are rarely undertaken.

In most cases, monitoring amounts to a critical reading of a report or an article. Ideally, however, replication by means of an empirical investigation of the key conclusions ought to be a standard requirement for publication. However, monitoring may be of limited value and may also entail unintended negative consequences, since the desired creativity presupposes freedom as well as trust.

Facilitating an expanded ethical competence in researchers and research communities is therefore a key concern. This includes ethical awareness and follow-up on the part of agencies that provide research funding. This is also a matter of ethics in a wider context, in the need to focus on power relationships and processes that maintain hegemony, whereby particularly subjects in the fields of care and learning are systematically discriminated against when resources are allocated.

Pricing Templates Features Login Sign up. Narrative Research This method occurs over extended periods of time and garners information as it happens. Ethnographic Research This method is one of the most popular and widely recognized methods of qualitative research, as it immerses samples in cultures unfamiliar to them.

Historical Research This method investigates past events in order to learn present patterns and anticipate future choices. Grounded Theory The grounded theory research method looks at large subject matters and attempts to explain why a course of action progresses the way it did. Case Study This involves deep understanding through multiple data sources.

What is quantitative research? Collect Quantitative Data With Online Surveys Researchers who use quantitative research method are typically looking to quantify the degree and accentuate objective measurements through polls, questionnaires, and surveys, or by manipulating an existing statistical data using computational techniques.

Correlational Research Correlational research is a non-experimental research method, where the researcher measures two variables, and studies the statistical relationship i. Survey Research Survey Research uses interviews, questionnaires, and sampling polls to get a sense of behavior with concentrated precision.

Why choose Quantitative Research over Qualitative Research? More scientific : A large amount of data is gathered and then analyzed statistically. This almost erases bias, and if more researchers ran the analysis on the data, they would always end up with the same numbers at the end of it. Control-sensitive : The researcher has more control over how the data is gathered and is more distant from the experiment.

An outside perspective is gained using this method. Researcher has clearly defined research questions to which objective answers are sought. Focused : The design of the study is determined before it begins and research is used to test a theory and ultimately support or reject it. Deals with larger samples : The results are based on larger sample sizes that are representative of the population. The large sample size is used to gain statistically valid results in customer insight.

Repeatable : The research study can usually be replicated or repeated, given its high reliability. Arranged in simple analytical methods : Received data are in the form of numbers and statistics, often arranged in tables, charts, figures, or other non-textual forms. Generalizable : Project can be used to generalize concepts more widely, predict future results, or investigate causal relationships. Findings can be generalized if selection process is well-designed and sample is representative of a study population.

Relatable : Quantitative research aims to make predictions, establish facts and test hypotheses that have already been stated. It aims to find evidence which supports or does not support an existing hypothesis.

It tests and validates already constructed theories about how and why phenomena occur. More structured : Researcher uses tools, such as questionnaires or equipment to collect numerical data.

Pertinent in later stages of research : Quantitative research is usually recommended in later stages of research because it produces more reliable results. Consistent with data : With quantitative research, you may be getting data that is precise, reliable and consistent, quantitative and numerical.

More acceptable : It may have higher credibility among many influential people e. Also, data analysis is relatively less time consuming using statistical software. Useful for decision making : Data from quantitative research—such as market size, demographics, and user preferences—provides important information for business decisions.

When to use Qualitative Research Qualitative research is explanatory and is used when the researcher has no idea what to expect.

How to Interpret Qualitative Research Data Qualitative data consists of words, observations, pictures, and symbols. See qualitative research can be analysed and interpreted with the following steps: Data familiarity : As a researcher, you should read and understand the data, noting impressions, look for meaning and weed out unnecessary data.

Identify key questions you want to answer through the analysis. One way to focus the analysis is to examine the data as it relates to a case, an individual, or a particular group. Code and index the data by identifying themes and patterns that may consist of ideas, concepts, behaviors, interactions, phrases and so on. Then, assign a code to pieces of data to label the data and make it easier to manage.

After that, you should identify patterns and make connections. Identify the themes, look for relative importance of responses received and try to find explanations from the data. The last thing to do is to interpret the data and explain findings.

You can develop a list of key ideas or use models to explain the findings. How to Interpret Quantitative Research Data Quantitative research methods result in data that provides quantifiable, objective, and easy to interpret results. Case Study of Quantitative Research Geramian et al considered the prevalent problem of drug abuse in Iran especially in adolescents and youth, and conducted a study to assess the status of drug abuse among high school students in Isfahan Province, Iran.

What is the best Data Collection tool? With Formplus builder, you can create surveys, questionnaires or polls that will help you gather data for your qualitative or quantitative research Formplus gives you an easy-to-use form builder with a variety of options including customization to beautify the form in your way. Signup on Formplus Builder to create your preferred online surveys for qualitative and quantitative research.

Collect Data Online The world is more digital than ever and will become even more digital. Email Invitation After you have created the online form, you definitely will want to get it to more people so data collection is not restricted. Geolocation You want to know where responses are coming from? Storage Integration Researches always come in with a lot of data but we got you covered.

Signup for Free to Start Collecting Online Data for Quantitative and Qualitative Research Conclusion As much as qualitative data adds humanity to data, quantitative data usually comes at the end to use numerical data to make conclusions. References Cook, T. Boston, MA: Houghton Mifflin. Abraham, I.