In addition, they do not allow participants to explain their choices or the meaning of the questions may have for those participants Carr, Poor knowledge of the application of statistical analysis may negatively affect analysis and subsequent interpretation Black, 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, This also affects the ability to generalize study findings to wider populations. The researcher might miss observing phenomena because of focus on theory or hypothesis testing rather than on the theory of hypothesis generation. Sophisticated software removes much of the need for prolonged data analysis, especially with large volumes of data involved Antonius, 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, Doing quantitative research in the social sciences: An integrated approach to research design, measurement and statistics. Using thematic analysis in psychology. Qualitative Research in Psychology , 3, 77— The strengths and weaknesses of quantitative and qualitative research: Journal of advanced nursing, 20 4 , The Good Research Guide: Handbook of Qualitative Research.
The discovery of grounded theory; strategies for qualitative research. Nursing research, 17 4 , Introduction to Social Research: Quantitatie and Qualitative Approaches.
Research Methods Qualitative vs. Qualitative Research Qualitative research is empirical research where the data are not in the form of numbers Punch, , p.
Events can be understood adequately only if they are seen in context. The contexts of inquiry are not contrived; they are natural. Nothing is predefined or taken for granted. The first two examples highlight that while the name of the dependent variable is the same, namely daily calorific intake , the way that this dependent variable is written out differs in each case.
All descriptive research questions have at least one group , but can have multiple groups. You need to identify this group s. In the examples below, we have identified the group s in the green text.
The examples illustrate the difference between the use of a single group e. Sometimes it makes more sense for the dependent variable to appear before the group s you are interested in, but sometimes it is the opposite way around.
The following examples illustrate this, with the group s in green text and the dependent variable in blue text:. Sometimes, the dependent variable needs to be broken into two parts around the group s you are interested in so that the research question flows. Again, the group s are in green text and the dependent variable is in blue text:. Of course, you could choose to restructure the question above so that you do not have to split the dependent variable into two parts.
How many calories are consumed per day by American men and women? When deciding whether the dependent variable or group s should be included first or last, and whether the dependent variable should be broken into two parts, the main thing you need to think about is flow: Does the question flow?
Is it easy to read? Sometimes the name of the dependent variable provides all the explanation we need to know what we are trying to measure. Take the following examples:. In the first example, the dependent variable is daily calorific intake i. Clearly, this descriptive research question is asking us to measure the number of calories American men and women consume per day.
In the second example, the dependent variable is Facebook usage per week. Again, the name of this dependent variable makes it easy for us to understand that we are trying to measure the often i. However, sometimes a descriptive research question is not simply interested in measuring the dependent variable in its entirety, but a particular component of the dependent variable.
Take the following examples in red text:. In the first example, the research question is not simply interested in the daily calorific intake of American men and women, but what percentage of these American men and women exceeded their daily calorific allowance. So the dependent variable is still daily calorific intake, but the research question aims to understand a particular component of that dependent variable i. In the second example, the research question is not only interested in what the factors influencing career choices are, but which of these factors are the most important.
Therefore, when you think about constructing your descriptive research question, make sure you have included any words that provide greater context to your question. Once you have these details? The example descriptive research questions discussed above are written out in full below:.
In this article we will explore the different ways to ask quantitative questions in your online survey. Be sure to identify all of the variables that might affect the outcome.
Also be sure to include all of the groups you are interested in. Neglecting to recognize variables and groups involved will create gaps in your data that will make it hard for you to base sound decisions on. In the example above, work and driving are variables that likely alter texting behavior. In this example, I would also collect demographic information such as age, gender, and job function so I could compare texting habits between these groups.
Use these versatile questions more effectively in your next survey project with our detailed guide! Most online survey tools offer an array of answer formats. This is good news, as these various options will engage your customers and reduce survey fatigue.
Drop Down Menu Example: Drag and Drop Example: Net Promoter Score Example: While it is nice to vary your question types to keep respondents interested, it is important to consider the reporting options.
As the name suggests, a quantitative research questionnaire is typically about quantities, mathematics and the relationship between variables, while qualitative research is more about narrowing down the "whys" and "whats," or the qualities, of a particular venture. Either form of social research can be conducted via various types of surveys.
Although survey research, by definition, implies the use of some form of questionnaire to be administered to a sample of respondents, the questionnaire is simply one instrument that can be employed in the study of a research problem. As such, it may or may not be the most suitable tool for the task at hand.
Quantitative and qualitative research are complementary methods that you can combine in your surveys to get results that are both wide-reaching and deep. Simply put, quantitative data gets you the numbers to prove the broad general points of your research. Qualitative data brings you the details and the depth to understand their full implications. Quantitative Research Definition: Quantitative research, in marketing, is a stimulating and highly educational technique to gather information from existing and potential customers using sampling methods and sending out online surveys, online polls, questionnaires etc., the results of which can be.
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). Qualitative vs Quantitative Research Snap Survey Software is the ideal quantitative research tool where structured techniques; large numbers of respondents and descriptive findings are required. Take a look at the survey software features that will help you gather and analyze quantitative data.