| Traits | Qualitative | Quantitative |
| Data Collection | Data are collected in the form of words with no numerical data involved. Common procedure of data collection used in case of qualitative data analysis include interview via open-ended questionnaire. The procedure of cost-effective and helps in the assessment of the beliefs and attitudes of the people | Data collection is done in the form of numerals. Quantitative data can be obtained via surveys or via the constructing close-ended interview questionnaire. The collected data is represented over analogue scale, Likert scale. Here the respondents are able to report their own experiences. Another form of quantitative data collection in case of health care domain is via physiological measures but there lies certain ethical complications (Prion & Adamson, 2015). |
| The procedure of data collection must match with the design of the research and research question |
| Levels of Measurement | Qualitative data analysis does not deal with the levels of measurement. Here the recorded information is analyzed on the basis of personal understanding, the more or the motion of the answer | The level of measurement is significant in case of quantitative data analysis as it deals with the numerical data. Numerical data are more precise and thus levels of measurement as represented in Likert charts or other pi charts are more authentic. However, error in measurement is always possible (Prion & Adamson, 2013). |
| It is used for the quantification of the data. There are four layers of measurement like nominal, ordial, interval and ratio |
| Sampling Consideration | Sampling procedure in qualitative and quantitative research techniques is same. Both can utilize probability sampling or non-probability sampling. One important consideration of sampling in case of quantitative research is assessing the soundness of the sample (Adamson & Prion, 2013). |
| Sampling deals with the target population that must be again sub-divided into accessible population, which meets the eligibility criteria. There are two types of sampling probability and non-probability sampling. However, the sampling procedure must be designed in such a way that it reduces the sampling error or biasness (Adamson & Prion, 2013). |
References
Adamson, K. A., & Prion, S. (2013). Making sense of methods and measurement: Effect size. Clinical Simulation in Nursing, 9(6), e225–e226. Retrieved from http://dx.doi.org/10.1016/j.ecns.2013.01.005. (http://www.sciencedirect.com/science/article/pii/S1876139913000157)
Prion, S., & Adamson, K. A. (2013). Making sense of methods and measurement: Levels of measurement for quantitative research. Clinical Simulation in Nursing, 9(1), e35–e36. Retrieved from http://dx.doi.org/10.1016/j.ecns.2012.10.001. (http://www.sciencedirect.com/science/article/pii/S1876139912003441)
Prion, S., & Adamson, K. A., (2015). Making sense of methods and measurements: Helpful resources for research methods and data analysis. Clinical Simulation in Nursing, 11,(9), 431–432. Retrieved from http://dx.doi.org/10.1016/j.ecns.2015.03.011. (http://www.sciencedirect.com/science/article/pii/S1876139915000316)
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