What do qualitative and quantitative have in common

Quantitative data is compatible with most statistical analysis methods and as such is mostly used by researchers. Qualitative data, on the other hand, is only compatible with median and mode, making it have restricted applications. Although, in some cases, alternative tests are carried out on ordinal data. For example, we use univariate statistics, bivariate statistics, regression analysis etc. Although very applicable in most statistical analysis, its standardised environment may limit the proper investigation.

Quantitative research is strictly based on the researcher's point of view, thus limiting freedom of expression on the respondent's end. This is not the case for qualitative research. Nominal data captures human emotions to an extent through open-ended questions. This may, however, cause the researcher to deal with irrelevant data.

In which of the following interval does your height fall in centimetres? This is an interval data example.

Quantitative question example 2. Kindly enter your National identification number below. This is a nominal data example. Quantitative data is compatible with most statistical methods, but qualitative data isn't. This may pose issues for researchers when performing data analysis. This is part of the reason why researchers prefer using quantitative data for research. Quantitative data collection methods are more user-friendly compared to that of qualitative data.

Although open-ended questions may give the researchers much-needed information, it may get stressful for respondents. Respondents like spending as little time as possible filling out surveys, and when it takes time, they may abandon it. Both quantitative and qualitative data has an order or scale to it. That is while ordinal data is sometimes classified under quantitative data. Qualitative data do not, however, have a standardised scale.

Quantitative and qualitative data are both used for research and statistical analysis. Although, through different approaches, they can both be used for the same thing. Consider two organisations investigating the purchasing power of its target audience through the method below. What is your monthly income? In which interval does your monthly income fall? The first is a qualitative data collection example while the second is a quantitative data collection example.

Both quantitative data and qualitative data takes a numeric value. Qualitative data takes numeric values like phone number, postal code, national identification number, etc. The difference, however, is that arithmetic operations cannot be performed on qualitative data.

Although through different approaches, they use similar tools. The different types of data have their usefulness and advantages over the other. These advantages are why they are chosen over the other in some cases depending on the purpose of data collection. Here are some cases where quantitative data should be chosen over qualitative data.

Quantitative data is more suitable for scientific research due to its compatibility with most statistical analysis methods. It also has numerical properties which allow for the performance of arithmetic operations on it.

Quantitative research has a standardised procedure to it. Hence, it is easy to replicate past research, build on it and even edit research procedures. Large data sets are best analysed using quantitative data. This is why some researchers turn qualitative data into quantitative data before analysis. It is called the quantification of qualitative data. This way, they don't have to be sweeping through a large string of texts for analysis.

Due to its standard procedure of analysis, it is the most suitable data type for laboratory analysis. Research that involve sensitive data is best processed using quantitative data.

This helps eliminate cases of bias due to familiarity or leaking sensitive information. Although not compatible with most statistical analysis methods, qualitative data is preferable in certain cases. It is mostly preferred when collecting data for real-life research processes. Here are some cases where qualitative data should be chosen over quantitative data. The main purpose of customer experience research is to know how customers feel about an organisation's service and get information on what they can do to improve their service.

Therefore, to achieve this, organisations need to assess human feelings and emotions. This is something that can only be done with qualitative data.

Especially with this ever-changing workplace culture, recruiters are now more interested in the applicant's attitude, emotional intelligence, etc. For them to properly assess these traits, qualitative data about the applicant should be collected through an interview.

Organisations perform competitive analysis to assess their competition's popularity and what they did to gain such popularity.

Quantitative data do not give detailed information about this unlike how qualitative does. Many web-based companies ask personal questions like, "What is your pet's name? Numbers are usually hard to memorise, which is why some people to find it difficult to memorise their phone number to date.

Personal questions qualitative data like this is hard to forget and therefore better for security questions. Dating websites collect personal Information usually nominal data of users to properly match them with their type.

Formplus as a data collection tool was built with the notion that proper data collection is the first step towards efficient and reliable research. Therefore, the makers of Formplus form builder software have added necessary features to help you collect your data. Quantitative and qualitative data is best collected with Formplus because it not only helps you collect proper data but also arrange them for analysis. You no longer have to deal with data that is difficult to read when performing data validation process.

Each data is properly matched to the corresponding variables, making it easy to identify missing or inconsistent data. Caracelli, Valerie J. Greene and V. Caracelli eds. New Directions for Program Evaluation, No. Carvalho, S. The World Bank: Washington D. Greene, J. San Francisco: Jossey-Bass. Greene, Jennifer C. Login Login and comment as BetterEvaluation member or simply fill out the fields below.

Options When data are gathered Parallel Data Gathering : gathering qualitative and quantitative data at the same time. As in the above case, the quantitative research was possible only because the qualitative research was completed first. You wouldn't know which emotion was the most popular, if you hadn't first determined which moods were evoked. Qualitative and quantitative research can stand on its own merits, but also, and often, they can work in tandem to help with the research process.

Whether you are focused on the numbers of quantitative research or the reasons for qualitative research , both processes require that the raw data be analyzed. How that happens depends on how the research is gathered.

In a survey, each response has to be counted individually, and then the totals of each response are compared to the control group or to the other responses. For example, if you have two spouses answering questions about each other, you'd have to count each response to each question, and then you'd compare the answers from the responding spouse with the answers from the control group or to the other responses.

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