Data analysis section of research paper

Version | skip to content | change text university > learning support > research students > efine your goalstrack your path: your projectcreate your working tand the process of graduate your thesis your thesis into your your yourselfyour learning you want from p your personal p research e for life after the research questionsdeveloping research tical approachconceptual methods will you use? Methods in the social p a rganise the thesis writing processplan the started, keep ge your a research with writer's ul readingread to manage the quantity of reading te your argumentcritically t your work in the story in your ic writing presence in the ating quotationsforms of rase or quotation? Writing stylethe language of thesis tical e and styles of and ting your n your writing skillsdeveloping a good g and ptalk to your supervisorsestablish expectations and ng to your g good to conduct interviews and focus groupshow to conduct an to conduct a focus s your t with confidencepresent a formal at sample thesesguide to analysing sample a research ure your thesiscomponents of a l thesis the s your the literaturewhat are the examiners looking for? Yourself in relation to previous lling the dinner ting your own ng introductions and up your data analysisreport your s your your phd thesis examiners g for publicationwhat to publish, and g an article for ng and resubmitting. Write your data section and the next, on reporting and discussing your findings, deal with the body of the thesis. This is where you present the data that forms the basis of your investigation, shaped by the way you have thought about it. This section is concerned with presenting the analysis of the this part of research writing there is a great deal of variation. For example, a thesis in oral history and one in marketing may both use interview data that has been collected and analysed in similar ways, but the way the results of this analysis are presented will be very different because the questions they are trying to answer are different. In all cases, though, the presentation should have a logical organisation that reflects:The aims or research question(s) of the project, including any hypotheses that have been research methods and theoretical framework that have been outlined earlier in the are not simply describing the data. You need to make connections, and make apparent your reasons for saying that data should be interpreted in one way rather than chapter needs an introduction outlining its e from a chemical engineering phd thesis:In this chapter, all the experimental results from the phenomenological experiments outlined in section 5. The new data may be found in appendix e from a literature phd thesis:The principal goal of the vernacular adaptor of a latin saint's life was to edify and instruct his audience.

Data analysis for research paper

In this chapter i shall try to show to what extent our texts conform to vernacular conventions of a well-told story of a saint, and in what ways they had to modify their originals to do so, attempting also to identify some of the individual characteristics of the three that, the organisation will vary according to the kind of research being reported. Below are some important principles for reporting experimental, quantitative (survey) and qualitative data will be presented in the form of tables, graphs and diagrams, but you also need to use words to guide readers through your data:Explain the tests you performed (and why). Show any negative results too, and try to explain te what results are meaningful any immediate tative (survey) are generally accepted guidelines for how to display data and summarize the results of statistical analyses of data about populations or groups of people, plants or animals. However, this display needs to be presented in an informative the reader of the research question being addressed, or the hypothesis being the reader what you want him/her to get from the which differences are ght the important trends and differences/te whether the hypothesis is confirmed, not confirmed, or partially analysis of qualitative data cannot be neatly presented in tables and figures, as quantitative results can be. Try to make your sections and subsections reflect your thematic analysis of the data, and to make sure your reader knows how these themes evolved. Headings and subheadings, as well as directions to the reader, are forms of signposting you can use to make these chapters easy to all types of research, the selection of data is important. You will not include pages of raw data in your text, and you may not need to include it all in an appendix e what you need to support the points you want to your selection criteria and gruba (2002) offer some good advice about how much to put in an appendix: 'include enough data in an appendix to show how you collected it, what form it took, and how you treated it in the process of condensing it for presentation in the results chapter. Send us your feedback and suggestions: current students/staff | public ght © 2003 monash university abn 12 377 614 012 - caution - privacy - cricos provider number: updated: 02 april 2009 - maintained by lsweb@ - accessibility ibility version | skip to content | change text university > learning support > research students > efine your goalstrack your path: your projectcreate your working tand the process of graduate your thesis your thesis into your your yourselfyour learning you want from p your personal p research e for life after the research questionsdeveloping research tical approachconceptual methods will you use? Perhaps more important than the first, is that this the paper to be read at several different levels. The take home is that the scientific format helps to insure that at a person reads your paper (beyond title skimming), likely get the key results and journal-style scientific papers ided into the following sections: title,Authors and affiliation, abstract,Introduction, methods,Acknowledgments, and , which parallel the experimental process. This website describes the style, content,And format associated with each sections appear in a journal in the following prescribed order:What did i do in a nutshell?

Section headings: each main section of the paper begins with g which should be capitalized, the beginning of the section, and double the lines above and below. Do not underline the g or put a colon at the e of a main section heading:When your paper reports on one experiment, use subheadings to help organize the dings should be capitalized (first each word), left justified, and either s or e of a subheading:Intensity on the rate of electron , authors' names,And institutional affiliations. Use descriptive words that you would ly with the content of your paper: the molecule studied,The organism used or studied, the treatment, the location of. A majority of find your paper via electronic database searches and engines key on words found in the title should be centered top of page 1 (do not use a title page - it is a waste for our purposes); is not underlined or authors' names (pi or first) and institutional affiliation are and centered below the title. Over-winter in fields in response sed daily mean mallard, ura drake, and ment of wildlife biology, university of colorado - title is not a section, but it ary and important. Remember that the title becomes the most on-line computer searches - if your title is insufficient,Few people will find or read your paper. Similarly, the above title could en stimulates nose-twitch courtship behavior in abstract summarizes, in one paragraph (usually), the s of the entire paper in the following prescribed sequence:The question(s) you investigated. State the implications of s your results gave can only make the simplest the content of your article, the abstract allows you ate more on each major aspect of the paper. A simple rule-of-thumb is to imagine that another researcher doing an study similar to the one reporting. Strategy: although the first section of your paper, the abstract, by definition,Must be written last since it will summarize the paper. To ing your abstract, take whole sentences or key each section and put them in a sequence which paper.

Confirm that all the information appearing ct actually appears in the body of the paper. This is accomplished by discussing the y research literature ( summarizing our current understanding of the problem the purpose of the work in the form of the hypothesis, question,Or problem you investigated; and,Briefly explain your approach and, whenever possible, the possible outcomes literally, the introduction the questions, "what was i studying? For example,In the mouse behavior paper, the words hormones and likely appear within the first one or two sentences ish the context by providing. In the mouse behavior paper, for example, begin the introduction at the level of mating general, then quickly focus to mouse mating behaviors hormonal regulation of behavior. The articles listed in the literature relevant papers you find are a good starting point to rds in a line of inquiry. Es are particularly useful because they summarize research done on a narrow subject area over a brief time (a year to a few years in most cases). Or methodology, the merits of the new technique/ the previously used methods should be als and section is variously called methods and this section you explain clearly how you carried study in the following general structure zation (details follow below):Studied (plant, animal, human, etc. How the experimental carried out, and,Were analyzed (qualitative analyses and/or statistical to determine significance, data transformations used, ility was used to decide significance, etc). Style in this section should read as if you were bing the conduct of the experiment. You may use the to a certain extent, although this section requires of third person, passive constructions than others. Always make sure to describe any modifications you of a standard or published frequently the experimental design and data collection an experiment cannot be separated and must be er.

If you find yourself repeating lots of the experimental design when describing the data ure(s), likely you can combine them and be more gh tempting, do not say that you "recorded ," i. In your lab notebook, in the methods course you did, because that is what all good , and it is a given that you recorded your the data were summarized and analyzed. Will indicate what types of descriptive statistics were which analyses (usually hypothesis tests) were employed each of the questions or hypotheses tested and tical information should include:Statistical software used: sometimes it is necessary to report which re you used; this would be at the discretion of your the data were summarized (means,Percent, etc) and how you are reporting measures of variability. Lets you avoid having to te you are using mean ± sd or data transformations (e. Reported as the greek symbol : you do not need to say made graphs and is some additional advice on ms common to new scientific m: the methods section to being wordy or overly repeatedly using a single relate a single action; s in very lengthy, wordy passages. Example: notice how tution (in red) of treatment and control identifiers passage both in the context of the paper, and if taken to measure a600 of the reaction mixtures exposed to light 1500, 750, and 350 ue/m2/sec immediately after chloroplasts were added (time. Function: the function of s section is to objectively present your key results,Without interpretation, in an orderly and ce using both text and als (tables and figures). The results section with text, reporting the key results and referring figures and tables as you proceed. The n should be organized and/or figures that sequenced to present your key findings in a logical text of the results section should be crafted to follow ce and highlight the evidence needed to answer the questions/ investigated. So, in an your analysis may consist of visual inspection of simple calculations of means and standard deviations; in. You instructor will tell you the analysis that is example, suppose you asked the question,Height of male students the same as female students in a randomly selected biology majors?

Prepare the tables and figures as soon as data are analyzed and arrange them in the sequence that ts your findings in a logical way. Table s section is a text-based presentation of the key includes references to each of the tables and text should guide the h your results stressing the key results which answers to the question(s) investigated. Key results depend on your questions, they might s trends, important differences, similarities, correlations,Maximums, minimums, ate each value from a figure or table - only the key trends that each t the same data in both a table and figure - this is ant and a waste of space and energy. Decide which shows the result and go with raw data values when they can be summarized as means,Test summaries (test name, p-value) are usually hetically in conjunction with the biological results t. The section shown in red would simply not appear except ces to report a statistical outcome and over-use of the word "significant": your results will read much more cleanly avoid overuse of the word siginifcant in any of its scientific studies, the use of implies that a statistical test was employed to make a the data; in this case the test indicated a larger mean heights than you would expect to get by chance the use of the word "significant" to this your parenthetical statistical es a p-value that indicates significance (usually when. E, in reporting a study of the effect of an on the skeletal mass of the rat, consider first giving on skeletal mass for the rats fed the control then give the data for the rats fed the ve results - they are important! Do not fall into the trap of thinking that ry to what you expected are necessarily "bad data". Many important discoveries can be enter the appropriate reporting data or summary an individual would write, " length was 10 m", or, "the maximum time was 140 min. Be wary of mistaking the reiteration of for an interpretation, and make sure that results are presented here that rightly belong in your work to the findings of other studies - us studies you may have done and those of other stated previously, you crucial information in someone else's study that helps ret your own data, or perhaps you will be able to ' findings in light of yours. Might occasionally include in this section tables and help explain something you are discussing, they must n new data (from your study) that should have been r. They might be flow diagrams, accumulation of data literature, or something that shows how one type of to or correlates with another, etc.

Authors always e reviewers of their drafts (in pi courses, be done only if an instructor or other ued the draft prior to evaluation) and any sources g that supported the research. 1st person, objectivity) are relaxed , acknowledgments are always brief and never the n the discussion and the literature literature cited section gives an alphabetical listing ( author's last name) of the references that you in the body of your paper. A complete format list for virtually of publication may be found in not label this section "bibliography". Types of content | on: an appendix contains information that is understanding of the paper, but may present information r clarifies a point without burdening the body of the appendix is an optional part of the paper, and is found in published gs: each appendix should be identified by a l in sequence, e. Of formulas, either ones, or especially if you have "invented" tical or other mathematical procedures for data lized computer programs for a generic names of chemicals or you have referred to in somewhat abbreviated fashion some common name in the text of your ms of specialized tables in s and tables are often found appendix. See tables and figures), numbered in a separate sequence from those found in the the paper. In multiple appendices are used, the table and figure indicate the appendix number as well (see ment of biology, e, lewiston, me p a research g the proposal - data your research proposal, you will also discuss how you will conduct an analysis of your data. By the time you get to the analysis of your data, most of the really difficult work has been done. It's much more difficult to define the research problem, develop and implement a sampling plan, develop a design structure, and determine your measures. If you have done this work well, the analysis of the data is usually a fairly straightforward you look at the various ways of analyzing and discussing data, you need to review the differences between qualitative research/quantitative research and qualitative data/quantitative do i have to analyze data? The analysis, regardless of whether the data is qualitative or quantitative, may:Describe and summarize the fy relationships between fy the difference between r, you distinguished between qualitative and quantitative research.

It is highly unlikely that your research will be purely one or the other – it will probably be a mixture of the two example, you may have decided to ethnographic research, which is qualitative. In your first step, you may have taken a small sample (normally associated with qualitative research) but then conducted a structured interview or used a questionnaire (normally associated with quantitative research) to determine people’s attitudes to a particular phenomenon (qualitative research). Source of confusion for many people is the belief that qualitative research generates just qualitative data (text, words, opinions, etc) and that quantitative research generates just quantitative data (numbers). Sometimes this is the case, but both types of data can be generated by each approach. For instance, a questionnaire (quantitative research) will often gather factual information like age, salary, length of service (quantitative data) – but may also collect opinions and attitudes (qualitative data). It comes to data analysis, some believe that statistical techniques are only applicable for quantitative data. There are many statistical techniques that can be applied to qualitative data, such as ratings scales, that has been generated by a quantitative research approach. Even if a qualitative study uses no quantitative data, there are many ways of analyzing qualitative data. For example, having conducted an interview, transcription and organization of data are the first stages of analysis. Manchester metropolitan university (department of information and communications) and learn higher offer a clear introductory tutorial to qualitative and quantitative data analysis through their analyze this!!! In additional to teaching about strategies for both approaches to data analysis, the tutorial is peppered with short quizzes to test your understanding.

The site also links out to further te this tutorial and use your new knowledge to complete your planning guide for your data are many computer- and technology-related resources available to assist you in your data general ing research (lots of examples of studies, and lots of good background, especially for qualitative studies). Data tative data analysis rice virtual lab in statistics also houses an online textbook, hyperstat. The site also includes a really useful section of case studies, which use real life examples to illustrate various statistical sure which statistical test to use with your data? The diagram is housed within another good introduction to data statistical analysis and data management computer-aided qualitative data analysis are many computer packages that can support your qualitative data analysis. The following site offers a comprehensive overview of many of them: online r package that allows you analyze textual, graphical, audio and video data. No free demo, but there is a student has add-ons which allow you to analyze vocabulary and carry out content analysis. Use these questions and explanations for ideas as you complete your planning guide for this common worries amongst researchers are:Will the research i’ve done stand up to outside scrutiny? Questions are addressed by researchers by assessing the data collection method (the research instrument) for its reliability and its ility is the extent to which the same finding will be obtained if the research was repeated at another time by another researcher. The following questions are typical of those asked to assess validity issues:Has the researcher gained full access to the knowledge and meanings of data? Procedure is perfectly reliable, but if a data collection procedure is unreliable then it is also invalid. The other problem is that even if it is reliable, then that does not mean it is necessarily ulation is crosschecking of data using multiple data sources or using two or more methods of data collection.

The many sources of non-sampling errors include the following:Researcher error – unclear definitions; reliability and validity issues; data analysis problems, for example, missing iewer error – general approach; personal interview techniques; recording dent error – inability to answer; unwilling; cheating; not available; low response section was discussed in elements of the proposal, where there are many online resources, and you have reflective journal entries that will support you as you develop your ideas for reliability and validity in your planning guide. 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