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Quantitative and Qualitative Data Study


Data can be classified as either qualitative or quantitative (Black, 1999). Quantitative data is data that can be put in numerical form while qualitative data cannot. Qualitative data deals with quality while quantitative data deals with quantity. There is a distinctive difference between the two types of data. Qualitative data deals with descriptions, data that cannot be measured but can be observed. Features of qualitative data include textures, appearance, colors, tastes, beauty, smells among others. Quantitative data on the other hand deals with numbers and data that can be measured (Shank, 2006). Examples of quantitative parameters include height, length, volume, speed, weight, temperature, time, etc.

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Literature review

The decision of whether it is effective to use qualitative or quantitative data for the research projects is controversial. A study by Rob McBride and John Schostak (1994) shows that qualitative researchers do not accept quantitative answers simply but are mostly interested in answering ‘why?’ questions. According to the study, most people doubt the validity of qualitative data and argue that when qualitative data is placed alongside quantitative data, quantitative data is more reliable because it has powerful and clear evidence. However powerful the quantitative data is, the study warns that it should not be allowed to overpower the opinions of people involved (Berg, 2007).

Gray, Williamson & Karp (2007), indicates that using both qualitative and qualitative methods of data collection would ensure that the deficiencies of each method are minimized and the benefits of both are realized. According to the book, the size of the population matters in deciding which method to use. It is not practical to conduct qualitative research on a population of 100 people because it will be time-consuming to have personal interviews with all of them (Silverman & David, 2006). In this case, the best approach will be quantitative research. The method a researcher uses to source data is a practical issue as well as a conceptual one (p 43). The sensitivity of the topic being researched would also determine which method is best suited (Berg, 2007).

Research questions

The first research questions were aimed to collect data using a quantitative approach. The open-ended interview questions were used to gather the necessary data. The research questions were supposed to gather information on whether a large number of Americans suffer health issues due to lack of exercise, improper diet, risk-taking behavior, or use of tobacco and alcohol (Centers for Disease Control and Prevention, 2004). The study, which was conducted on five students between the ages of 30-50 years from University of Phoenix doctoral studies, included the student’s age and gender, their perception of nutrition, exercise and drugs on their health.

The second research question used a qualitative approach to determine whether lack of exercise had any relation to the health problems experienced in America. The same graduate students were used to give their opinions using open-ended interview questions. The interview questions were phrased in such a way that every participant could give a detailed answer.

Development of instruments

In the first study, a sample of five students out of 722 doctoral students from the University of Phoenix between the ages of 30-50 years was taken. Each student was supposed to answer 10 questions using either a questionnaire or one-on-one interviews. The questionnaire was sent to the students via an online web-based service known as Survey Monkey while the interviews were conducted by survey researchers. In the second study, a sample of four doctorate students was used to answer a sample of five questions. Telephone interviews were the method used to collect data from the students. The students were asked open-ended questions that they were supposed to answer descriptively.

Administration of instruments

In the first study, numerical values were required as answers to the listed questions. Out of the ten answers, a student was required to answer with numerical values ranging from:

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1 to 5: 5 very likely
4 somewhat likely
3 neutral
2 not very likely
1 Does Not entirely like

The Likert scale was the code that was used to measure the participants’ response and classify it as positive or negative. Tool Pack for Microsoft Windows was the software tool that was used to analyze the data obtained from the survey questionnaires. The statistical inferences that were required to be calculated include correlation coefficient, mean and standard deviation. A table and a bar graph were the data representation method for the survey results.

In the qualitative study where the survey researchers wanted to find out whether exercise was important to health. The main theme was divided into sub-themes. The sub-themes were afterward coded using a coding system similar to the one used in filing systems labels. From the list of options, the students were supposed to choose the most favorable answer to the question asked. Since the responses were coded, the researchers would use these codes during analysis. The data was presented using a word-processing software program known as Microsoft Word.


In the first study, the 10 students in the sample responded to the questions. The total sample of the students who responded was female. The correlation coefficient lies between 0 and 1 indicating that there was a close relationship between nutrition, exercise and physical well-being. The analysis of the data suggested that people between the ages of 30-50 years considered nutritious food away from a healthy body and strong immune system. A large number thought that people who exercised were less likely to suffer from heart diseases and high blood pressure. From the sample, people who eat unhealthy foods and did not exercise were more likely to develop diabetes, stress, hypertension, cancer, and obesity. Most students believed that water is good for health and the ‘8 glasses per day’ strategy was relevant.

The second study results were analyzed one by one. Three out of four students said that exercises relieved stress while one student believed it was a way to relax. A large sample agreed that exercise was the solution to weight problems, menstrual cramps, depression, healthy heart, kill boredom and helped in self-esteem and self-confidence development. Only two students from the sample complained that exercises were boring and they hurt.


Qualitative methods of data collection do not draw statistical inferences but are mostly concerned with describing the meaning and experience. Quantitative methods on the other hand analyze the statistics and draw inferences (Berg, 2007). Quantitative methods are known to be fairly reliable but they lack in-depth description. Qualitative methods, on the other hand, are valid because they provide a rich description and provide in-depth information but they are criticized for lack of reliability (Creswell, 2005). It is, therefore, appropriate to use both approaches since it would ensure that the statistical inferences obtained are backed up with valid and in-depth information from explanations given by the research participants. In the discussed research, studies both qualitative and quantitative methods were used. Quantitative methods suggested that good nutrition and physical exercises reduced the risk of developing diabetes, stress, hypertension, cancer, and obesity (Gray, Williamson & Karp, 2007). The qualitative approach on the other hand concluded that physical exercises are a solution to good health (Hill, Goldberg, Pate & Peter, 2001).


Berg, B. L. (2007). Qualitative research methods for the social sciences. Boston: Allyn and Bacon.

Black, T. R. (1999). Doing quantitative research in the social sciences: An integrated approach to research design, measurement and statistics. London, England: Sage.

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Bryman, A. (2001, August). Social research methods. New York: Oxford University Press.

Centers for Disease Control and Prevention. (2004). Physical activity and good nutrition: Essential elements to prevent chronic diseases and obesity. Web.

Creswell, J. W. (2005). Educational research: Planning, conducting, and evaluating quantitative and qualitative research (2nd Ed.). Upper Saddle River, NJ: Merrill Prentice-Hall.

Gray D. Williamson F. and Karp L. (2007). The Research imagination: an introduction to qualitative and quantitative methods. Cambridge: Cambridge University Press.

Hill J, Goldberg J, Pate and Peters J. (2001). Introduction: Nutrition Reviews. 599 (3): S4-S6.

Neuman, W. L. (2006). Social research methods: Qualitative and quantitative approaches (6th Ed.). Boston: Pearson.

Shank, G.D. (2006). Qualitative research: A personal skills approach (2nd Ed.) Upper Saddle River, NJ: Pearson

Silverman G. and David P. (2006) Interpreting qualitative data: methods for analyzing talk, text, and interaction. Gateshead: SAGE

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