Call us toll-free

Quick academic help

Don't let the stress of school get you down! Have your essay written by a professional writer before the deadline arrives.

Calculate the price


275 Words


Data Analysis and Interpretation Presentation

Whether statistical or non-statistical methods of analyses are used, researchers should be aware of the potential for compromising data integrity. While statistical analysis is typically performed on quantitative data, there are numerous analytic procedures specifically designed for qualitative material including content, thematic, and ethnographic analysis. Regardless of whether one studies quantitative or qualitative phenomena, researchers use a variety of tools to analyze data in order to test hypotheses, discern patterns of behavior, and ultimately answer research questions. Failure to understand or acknowledge data analysis issues presented can compromise data integrity.

6 thoughts on “The Importance of Data Accuracy and Integrity for Data Analysis”

A major challenge to data integrity could occur with the unmonitored supervision of inductive techniques. Content analysis requires raters to assign topics to text material (comments). The threat to integrity may arise when raters have received inconsistent training, or may have received previous training experience(s). Previous experience may affect how raters perceive the material or even perceive the nature of the analyses to be conducted. Thus one rater could assign topics or codes to material that is significantly different from another rater. Strategies to address this would include clearly stating a list of analyses procedures in the protocol manual, consistent training, and routine monitoring of raters.

Presentation analysis and interpretation of data thesis

Environmental/contextual issues

The integrity of data analysis can be compromised by the environment or context in which data was collected i.e., face-to face interviews vs. focused group. The occurring within a dyadic relationship (interviewer-interviewee) differs from the group dynamic occurring within a focus group because of the number of participants, and how they react to each other’s responses. Since the data collection process could be influenced by the environment/context, researchers should take this into account when conducting data analysis.

Researchers performing analysis on either quantitative or qualitative analyses should be aware of challenges to reliability and validity. For example, in the area of content analysis, Gottschalk (1995) identifies three factors that can affect the reliability of analyzed data:

Thesis Data Analysis And Interpretation - …

Kendall and Grove (1988) define clinical significance in terms of what happens when “… troubled and disordered clients are now, after treatment, not distinguishable from a meaningful and representative non-disturbed reference group”. Thompson and Noferi (2002) suggest that readers of counseling literature should expect authors to report either practical or clinical significance indices, or both, within their research reports. Shepard (2003) questions why some authors fail to point out that the magnitude of observed changes may too small to have any clinical or practical significance, “sometimes, a supposed change may be described in some detail, but the investigator fails to disclose that the trend is not statistically significant ”.

No amount of statistical analysis, regardless of the level of the sophistication, will correct poorly defined objective outcome measurements. Whether done unintentionally or by design, this practice increases the likelihood of clouding the interpretation of findings, thus potentially misleading readers.

The basis for this issue is the urgency of reducing the likelihood of statistical error. Common challenges include the exclusion of , filling in missing data, altering or otherwise changing data, data mining, and developing graphical representations of the data (Shamoo, Resnik, 2003).

At times investigators may enhance the impression of a significant finding by determining how to present (as opposed to data in its raw form), which portion of the data is shown, why, how and to whom (Shamoo, Resnik, 2003). Nowak (1994) notes that even experts do not agree in distinguishing between analyzing and massaging data. Shamoo (1989) recommends that investigators maintain a sufficient and accurate paper trail of how data was manipulated for future review.

(2) assumptions about the population from which the data are drawn (i.e., random distribution, independence, sample size, etc.). If one uses unconventional norms, it is crucial to clearly state this is being done, and to show how this new and possibly unaccepted method of analysis is being used, as well as how it differs from other more traditional methods. For example, Schroder, Carey, and Vanable (2003) juxtapose their identification of new and powerful data analytic solutions developed to count data in the area of HIV contraction risk with a discussion of the limitations of commonly applied methods.

If one uses unconventional norms, it is crucial to clearly state this is being done, and to show how this new and possibly unaccepted method of analysis is being used, as well as how it differs from other more traditional methods. For example, Schroder, Carey, and Vanable (2003) juxtapose their identification of new and powerful data analytic solutions developed to count data in the area of HIV contraction risk with a discussion of the limitations of commonly applied methods.

While the conventional practice is to establish a standard of acceptability for statistical significance, with certain disciplines, it may also be appropriate to discuss whether attaining statistical significance has a true practical meaning, i.e., . Jeans (1992) defines ‘clinical significance’ as “the potential for research findings to make a real and important difference to clients or clinical practice, to health status or to any other problem identified as a relevant priority for the discipline”.

Order now

    As soon as we have completed your work, it will be proofread and given a thorough scan for plagiarism.


    Our clients' personal information is kept confidential, so rest assured that no one will find out about our cooperation.


    We write everything from scratch. You'll be sure to receive a plagiarism-free paper every time you place an order.


    We will complete your paper on time, giving you total peace of mind with every assignment you entrust us with.


    Want something changed in your paper? Request as many revisions as you want until you're completely satisfied with the outcome.

  • 24/7 SUPPORT

    We're always here to help you solve any possible issue. Feel free to give us a call or write a message in chat.

Order now

Data Analysis and Interpretation Presentation

A common practice of investigators is to defer the selection of analytic procedure to a research team ‘statistician’. Ideally, investigators should have substantially more than a basic understanding of the rationale for selecting one method of analysis over another. This can allow investigators to better supervise staff who conduct the data analyses process and make informed decisions

While methods of analysis may differ by scientific discipline, the optimal stage for determining appropriate analytic procedures occurs early in the research process and should not be an afterthought. According to Smeeton and Goda (2003), “Statistical advice should be obtained at the stage of initial planning of an investigation so that, for example, the method of sampling and design of questionnaire are appropriate”.

The chief aim of analysis is to distinguish between an event occurring as either reflecting a true effect versus a false one. Any bias occurring in the collection of the data, or selection of method of analysis, will increase the likelihood of drawing a biased inference. Bias can occur when recruitment of study participants falls below minimum number required to demonstrate statistical power or failure to maintain a sufficient follow-up period needed to demonstrate an effect (Altman, 2001).

When failing to demonstrate statistically different levels between treatment groups, investigators may resort to breaking down the analysis to smaller and smaller subgroups in order to find a difference. Although this practice may not inherently be unethical, these analyses should be proposed before beginning the study even if the intent is exploratory in nature. If it the study is exploratory in nature, the investigator should make this explicit so that readers understand that the research is more of a hunting expedition rather than being primarily theory driven. Although a researcher may not have a theory-based hypothesis for testing relationships between previously untested variables, a theory will have to be developed to explain an unanticipated finding. Indeed, in exploratory science, there are no a priori hypotheses therefore there are no hypothetical tests. Although theories can often drive the processes used in the investigation of qualitative studies, many times patterns of behavior or occurrences derived from analyzed data can result in developing new theoretical frameworks rather than determined (Savenye, Robinson, 2004).

It is conceivable that multiple statistical tests could yield a significant finding by chance alone rather than reflecting a true effect. Integrity is compromised if the investigator only reports tests with significant findings, and neglects to mention a large number of tests failing to reach significance. While access to computer-based statistical packages can facilitate application of increasingly complex analytic procedures, inappropriate uses of these packages can result in abuses as well.

Every field of study has developed its accepted practices for data analysis. Resnik (2000) states that it is prudent for investigators to follow these accepted norms. Resnik further states that the norms are ‘…based on two factors:

analysis and interpretation of ..

Extent of analysis

Upon coding text material for content analysis, raters must classify each code into an appropriate category of a cross-reference matrix. Relying on computer software to determine a frequency or word count can lead to inaccuracies. “One may obtain an accurate count of that word's occurrence and frequency, but not have an accurate accounting of the meaning inherent in each particular usage” (Gottschalk, 1995). Further analyses might be appropriate to discover the dimensionality of the data set or identity new meaningful underlying variables.

Order now
  • You submit your order instructions

  • We assign an appropriate expert

  • The expert takes care of your task

  • We send it to you upon completion

Order now
  • 37 684

    Delivered orders

  • 763

    Professional writers

  • 311

    Writers online

  • 4.8/5

    Average quality score

Order now
  • Kim

    "I have always been impressed by the quick turnaround and your thoroughness. Easily the most professional essay writing service on the web."

  • Paul

    "Your assistance and the first class service is much appreciated. My essay reads so well and without your help I'm sure I would have been marked down again on grammar and syntax."

  • Ellen

    "Thanks again for your excellent work with my assignments. No doubts you're true experts at what you do and very approachable."

  • Joyce

    "Very professional, cheap and friendly service. Thanks for writing two important essays for me, I wouldn't have written it myself because of the tight deadline."

  • Albert

    "Thanks for your cautious eye, attention to detail and overall superb service. Thanks to you, now I am confident that I can submit my term paper on time."

  • Mary

    "Thank you for the GREAT work you have done. Just wanted to tell that I'm very happy with my essay and will get back with more assignments soon."

Ready to tackle your homework?

Place an order