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THE PARTICIPANT’S VIEWPOINT

❶We ask another sample of students to search for the same specific information - and we see which group did better through a variety of different measures, some subjective and some objective.

INTRODUCTION

Analyze Quantitative Data
1/19 Quantitative data analysis
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This result is masked when you report the average satisfaction level of all participants in the program is 2. In addition to the basic methods described above there are a variety of more complicated analytical procedures that you can perform with your data. These types of analyses generally require computer software e.

We provide basic descriptions of each method but encourage you to seek additional information e. For more information on quantitative data analysis, see the following sources: A correlation is a statistical calculation which describes the nature of the relationship between two variables i.

An important thing to remember when using correlations is that a correlation does not explain causation. A correlation merely indicates that a relationship or pattern exists, but it does not mean that one variable is the cause of the other.

An analysis of variance ANOVA is used to determine whether the difference in means averages for two groups is statistically significant. For example, an analysis of variance will help you determine if the high school grades of those students who participated in the summer program are significantly different from the grades of students who did not participate in the program. Regression is an extension of correlation and is used to determine whether one variable is a predictor of another variable.

A regression can be used to determine how strong the relationship is between your intervention and your outcome variables. More importantly, a regression will tell you whether a variable e. A variable can have a positive or negative influence, and the strength of the effect can be weak or strong.

Like correlations, causation can not be inferred from regression. Quantitative Analysis in Evaluation Before you begin your analysis, you must identify the level of measurement associated with the quantitative data.

There are four levels of measurement: T-shirt size small, medium, large Example: Fahrenheit degrees Remember that ratios are meaningless for interval data. You cannot say, for example, that one day is twice as hot as another day. In experimental settings, researchers can directly collect quantitative data such as reaction times, blood pressure or such data can be self-reported by research participants on a pretest or posttest.

Questionnaires — either interviewer- or self-administered — are commonly used to collect quantitative data by asking respondents to report attitudes, experiences, demographics, etc. A common quantitative approach is known as secondary data analysis, in which a researcher analyzes data that were originally collected by another research team. Often these are large-scale, nationally-representative data sets that require extensive resources to collect; such data sets are made available by many organizations to allow many researchers to conduct independent research using high quality data.

Hypotheses for quantitative analysis tend to be highly specific, describing clear relationships between the independent and dependent variables. For hypotheses involving two numeric variables, the expected direction of the relationship will be described.

For example, a hypothesis might read: Hypotheses for categorical variables specify which category of the independent will be more likely to report a certain category of the dependent variable; for example: More commonly, researchers use qualitative research software e. It is advised that researchers undertake a formal course in the use of such software or seek supervision from a researcher experienced in these tools.

If we read a little more deeply, we can ask ourselves how the participant might have come to feel that the doctor assumed he or she was aware of the diagnosis or indeed that they had only just been told the diagnosis. There are a number of pauses in the narrative that might suggest the participant is finding it difficult to recall that experience. At the end of this excerpt, the participant just trails off, recalling that no-one showed any interest, which makes for very moving reading.

There are no statistical tests that can be used to check reliability and validity as there are in quantitative research. This simple act can result in revisions to the codes and can help to clarify and confirm the research findings.

Theming refers to the drawing together of codes from one or more transcripts to present the findings of qualitative research in a coherent and meaningful way. Thus, when the findings are organized for presentation, each theme can become the heading of a section in the report or presentation. Implications for real life e. This synthesis is the aim of the final stage of qualitative research. There are a number of ways in which researchers can synthesize and present their findings, but any conclusions drawn by the researchers must be supported by direct quotations from the participants.

The work of Latif and others 12 gives an example of how qualitative research findings might be presented. As has been suggested above, if researchers code and theme their material appropriately, they will naturally find the headings for sections of their report. The final presentation of the research will usually be in the form of a report or a paper and so should follow accepted academic guidelines. In particular, the article should begin with an introduction, including a literature review and rationale for the research.

There should be a section on the chosen methodology and a brief discussion about why qualitative methodology was most appropriate for the study question and why one particular methodology e. The method itself should then be described, including ethics approval, choice of participants, mode of recruitment, and method of data collection e.

The findings should be written as if a story is being told; as such, it is not necessary to have a lengthy discussion section at the end. As stated earlier, it is not the intention of qualitative research to allow the findings to be generalized, and therefore this is not, in itself, a limitation.

Planning out the way that findings are to be presented is helpful. It is useful to insert the headings of the sections the themes and then make a note of the codes that exemplify the thoughts and feelings of your participants. It is generally advisable to put in the quotations that you want to use for each theme, using each quotation only once.

After all this is done, the telling of the story can begin as you give your voice to the experiences of the participants, writing around their quotations.

Finally, as appropriate, it is possible to include examples from literature or policy documents that add support for your findings. It can be used in pharmacy practice research to explore how patients feel about their health and their treatment. An understanding of these issues can help pharmacists and other health care professionals to tailor health care to match the individual needs of patients and to develop a concordant relationship.

Doing qualitative research is not easy and may require a complete rethink of how research is conducted, particularly for researchers who are more familiar with quantitative approaches. There are many ways of conducting qualitative research, and this paper has covered some of the practical issues regarding data collection, analysis, and management. The participant age late 50s had suffered from a chronic mental health illness for 30 years. As the participant talked about past experiences, the researcher asked:.

The planned 2-year series is intended to appeal to relatively inexperienced researchers, with the goal of building research capacity among practising pharmacists. The articles, presenting simple but rigorous guidance to encourage and support novice researchers, are being solicited from authors with appropriate expertise.

Can J Hosp Pharm. Ethical issues in pharmacy practice research: Designing pharmacy practice research trials. An introduction to developing surveys for pharmacy practice research. An introduction to the fundamentals of cohort and case—control studies. Austin Z, Sutton J. C an J Hosp Pharm. An introduction to the fundamentals of randomized controlled trials in pharmacy research. What do you need to know to get started? National Center for Biotechnology Information , U.

Copyright Canadian Society of Hospital Pharmacists. In submitting their manuscripts, the authors transfer, assign, and otherwise convey all copyright ownership to CSHP. This article has been cited by other articles in PMC. Interpretation of Data Interpretation of the data will depend on the theoretical standpoint taken by researchers.

Transcribing and Checking For the purposes of this paper it is assumed that interviews or focus groups have been audio-recorded. Coding Once all of the research interviews have been transcribed and checked, it is time to begin coding.

Theming Theming refers to the drawing together of codes from one or more transcripts to present the findings of qualitative research in a coherent and meaningful way. Planning and Writing the Report As has been suggested above, if researchers code and theme their material appropriately, they will naturally find the headings for sections of their report.

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In quantitative data analysis you are expected to turn raw numbers into meaningful data through the application of rational and critical thinking. Quantitative data analysis may include the calculation of frequencies of variables and differences between variables.

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Quantitative Research Approach. Quantitative research most often uses deductive logic, in which researchers start with hypotheses and then collect data which can be used to determine whether empirical evidence to support that hypothesis exists.. Quantitative analysis requires numeric information in the form of variables. A variable is a way of measuring any characteristic that varies or has.

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Analyze Quantitative Data Quantitative data analysis is helpful in evaluation because it provides quantifiable and easy to understand results. Quantitative data can be . 1/19 Quantitative data analysis. First of all let's define what we mean by quantitative data analysis. It is a systematic approach to investigations during which numerical data is collected and/or the researcher transforms what is collected or observed into numerical data.

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Quantitative Research. Quantitative methods emphasize objective measurements and the statistical, mathematical, or numerical analysis of data collected through polls, questionnaires, and surveys, or by manipulating pre-existing statistical data using computational se66rthaae-1fboc6.gatative research focuses on gathering numerical data and generalizing it across groups of people or to explain a. Analyzing Quantitative Research. The following module provides an overview of quantitative data analysis, including a discussion of the necessary steps and types of statistical analyses.