How does all of this look in practice? Recall the two examples that were outlined above. You need to make a table, as in TABLE 1 below, which identifies means and standard deviations for all these variables.
When commenting upon the results, you can say:. Participants were on average Note that, in this example, you are concluding that participants had moderate self-esteem levels if their self-esteem was assessed on a 1 to 10 scale. Since the value of 5 falls within the middle of this range, you are concluding that the mean value of self-esteem is moderate.
If the mean value was higher e. Descriptive statistics for all variables used in research: M SD Height cm You can also outline descriptive statistics for specific groups. Descriptive statistics for the determination to read the book, by gender: Thus, you are not reporting means and standard deviations, but frequencies and percentages. To put this another way, you are noting how many males versus females wanted to read the book and how many of them were in a relationship, as shown in TABLE 3.
You can report these statistics in this way:. Frequencies statistics for all variables used in research: The first of these is correlation, which you use when you want to establish if one or more continuous, independent variables relate to another continuous, dependent variable. The first step here is to report whether your variables are normally distributed. You do this by looking at a histogram that describes your data.
If the histogram has a bell-shaped curve see purple graph below , your data is normally distributed and you need to rely on a Pearson correlation analysis. Here, you need to report the obtained r value correlation coefficient and p value which needs to be lower than. If you find a correlation, you need to say something like:.
Histogram testing the normal distribution of data: Note also that positive correlation occurs when higher levels of one variable correlate with higher levels of another variable. Negative correlation, however, occurs when higher levels of one variable correlate with lower levels of another variable.
One final thing to note, which is important for all analyses, is that when your p value is indicated to be. If your data is skewed rather than normally distributed see red graphs , then you need to rely on a Spearman correlation analysis. Here, you report the results by saying:. You also need to make a table that will summarise your main results.
Correlations between all variables used in research: Height cm Self-esteem Height cm 1. Correlations between all variables used in research, before and after controlling for a covariate: These are the specific points that you need to address in order to make sure that all assumptions have been met:.
All of this may sound quite complex. But in reality it is not: Once you conclude that your assumptions have been met, you write something like:. Since none of the VIF values were below 0. Durbin-Watson statistics fell within an expected range, thus indicating that the assumption of no autocorrelation of residuals has been met as well. Finally, the scatterplot of standardised residual on standardised predicted value did not funnel out or curve, and thus the assumptions of linearity and homoscedasticity have been met as well.
If your assumptions have not been met, you need to dig a bit deeper and understand what this means. A good idea would be to read the chapter on regression and especially the part about assumptions written by Andy Field. You can access his book here. This will help you understand all you need to know about the assumptions of a regression analysis, how to test them, and what to do if they have not been met. You have entered height and weight as predictors in the model and self-esteem as a dependent variable.
First, you need to report whether the model reached significance in predicting self-esteem scores. Look at the results of an ANOVA analysis in your output and note the F value, degrees of freedom for the model and for residuals, and significance level. You need to multiply this value by to get a percentage. Thus, if your R 2 value is. Model summary for regression: This value represents the change in the outcome associated with a unit change in the predictor.
You can report all these results in the following way:. For every increase in height by 1 cm, self-esteem increased by. Reporting the results of a chi-square analysis As we have seen, correlation and regression are done when all your variables are continuous. Chi-square analysis, which is what we will describe here, is done when all your variables are categorical. For instance, you would do a chi-square analysis when you want to see whether gender categorical independent variable with two levels: Then you need to report the results of a chi-square test, by noting the Pearson chi-square value, degrees of freedom, and significance value.
You can see all these in your output. You report these values by indicating the actual value and the associated significance level. The closer the value is to 1, the higher the strength of the association.
You can report the results of the chi-square analysis in the following way:. This test assesses whether there are significant differences between two groups of participants, where your independent variable is categorical e.
Thus, in our example, you are assessing whether females versus males showed higher determination to read a romantic novel. Now you need to report the obtained t value, degrees of freedom, and significance level — all of which you can see in your results output.
In the t-test example, you had two conditions of a categorical independent variable, which corresponded to whether a participant was male or female. You would have three conditions of an independent variable when assessing whether relationship status independent variable with three levels: Here, you would report the results in a similar manner to that of a t -test. You first report the means and standard deviations on the determination to read the book for all three groups of participants, by saying who had the highest and lowest mean.
Then you report the results of the ANOVA test by reporting the F value, degrees of freedom for within-subjects and between-subjects comparisons , and the significance value. There are two things to note here. For example, you may have noticed an unusual correlation between two variables during the analysis of your results. It is correct to point this out in the results section.
Speculating why this correlation is happening, and postulating about what may be happening, belongs in the discussion section. It is very easy to put too much information into the results section and obscure your findings underneath reams of irrelevance. If you make a table of your findings, you do not need to insert a graph highlighting the same data.
If you have a table of results, refer to it in the text, but do not repeat the figures - duplicate information will be penalized. One common way of getting around this is to be less specific in the text. For example, if the result in table one shows Table One shows that almost a quarter of….. Perhaps the best way to use the results section is to show the most relevant information in the graphs, figures and tables.
The text, conversely, is used to direct the reader to those, also clarifying any unclear points. The text should also act as a link to the discussion section, highlighting any correlations and findings and leaving plenty of open questions. For most research paper formats , there are two ways of presenting and organizing the results. The first method is to present the results and add a short discussion explaining them at the end, before leading into the discussion proper.
This is very common where the research paper is straightforward, and provides continuity. Not all of this can possibly appear in your dissertation without completely overwhelming the reader. As a result, you need to be able to make smart decisions about what to include and what to leave out.
One of the easiest ways to approach this task is to create an outline. In approaching the outline, it is in your best interest to focus on two key points. Firstly, you need to focus on answering your research questions.
Secondly, you must include any particularly interesting findings that have cropped up as you completed your research. An outline will give you the structure you need, and should make the whole process of presenting your findings easier. We realise that it is going to be a difficult process to pick and choose pieces of data to include.
But you must be diligent in the work that you cut out. A findings chapter that is long and confusing is going to put the reader off reading the rest of your work.
This is a huge chunk of information, so it's essential that it is clearly organised and that the reader knows what is supposed to be happening. One of the ways you can achieve this is through a logical and organised introduction.
A brief description of how you intend approaching the write up of the results. Letting the reader know where they can find the research instruments i. With a findings chapter, there should be no suspense for the reader. You need to tell them what they need to know right from the beginning. This way, they'll have a clear idea about what is still to come. A good introduction will start by telling the reader where you have come from in the research process and what the outcome was in a couple of paragraphs or less.
You need to highlight the structure of the chapter as you generally will do with all chapters and where the reader might find any further information e. This is really going to depend on the type of project you have created. For example, if you have completed a qualitative research project, you might have identified some key themes within the software program you used to organise your data.
In this case, highlighting these themes in your findings chapter may be the most appropriate way to proceed. Not only are you using information that you have already documented, you are telling a story in each of your sections which can be useful in qualitative research. But what if you undertook a more quantitative type study?
You might be better off structuring your findings chapter in relation to your research questions or your hypotheses. This assumes, of course, that you have more than one research question or hypothesis. Otherwise you would end up just having one really long section. Subheadings are ultimately going to be your friend throughout your dissertation writing. Not only do they organise your information into logical pieces, they give the reader guidelines for where your research might be going.
This is also a break for the reader. Looking at pages and pages of text without any breaks can be daunting and overwhelming for a reader. You don't want to overwhelm someone who is going to mark your work and who is responsible for your success or failure. When writing your introduction, be clear, organised and methodical. Tell the reader what they need to know and try to organise the information in a way that makes the most sense to you and your project.
If in doubt, discuss this with your supervisor before you start writing. If you have conducted things like interviews or observations, you are likely to have transcripts that encompass pages and pages of work. Putting this all together cohesively within one chapter can be particularly challenging.
This is true for two reasons. Secondly, unlike quantitative data, it can often be difficult to represent qualitative data through figures and tables, so condensing the information into a visual representation is simply not possible.
As a writer, it is important to address both these challenges. When considering how to present your qualitative data, it may be helpful to begin with the initial outline you have created and the one described above. Within each of your subsections, you are going to have themes or headings that represent impactful talking points that you want to focus on.
If you have used multiple different instruments to collect data e. This is so that you can demonstrate to more well-rounded perspective of the points you are trying to make.
Once you have your examples firmly selected for each subsection, you want to ensure that you are including enough information. You must set up the examples you have chosen in a clear and coherent way. Students often make the mistake of including quotations without any other information. Usually this means writing about the example both before and after. This was a focal point for 7 of my 12 participants, and examples of their responses included: The reoccurring focus by participants on the need for more teachers demonstrates [insert critical thought here].
By embedding your examples in the context, you are essentially highlighting to the reader what you want them to remember. Aside from determining what to include, the presentation of such data is also essential. Participants, when speaking in an interview might not do so in a linear way. Instead they might jump from one thought to another and might go off topic here and there. So the quotes need to be paired down to incorporate enough information for the reader to be able to understand, while removing the excess.
Finding this balance can be challenging. You have likely worked with the data for a long time and so it might make sense to you. Try to see your writing through the eyes of someone else, which should help you write more clearly. Something to consider first with numeric data is that presentation style depends what department you are submitting to. In the hard sciences, there is likely an expectation of heavy numeric input and corresponding statistics to accompany the findings.
In the arts and humanities, however, such a detailed analysis might not be as common. Therefore as you write out your quantitative findings, take your audience into consideration. Just like with the qualitative data, you must ensure that your data is appropriately organised. Again, you've likely used a software program to run your statistical analysis, and you have an outline and subheadings where you can focus your findings.
There are many software programs available and it is important that you have used one that is most relevant to your field of study. For some, Microsoft Excel may be sufficient for basic analysis. Whatever program you have used, make sure that you document what you have done and the variables that have affected your analysis.
One common mistake found in student writing is the presentation of the statistical analysis. During your analysis of the data , you are likely to have run multiple different analyses from regressions to correlations. Often, we see students presenting multiple different statistical analyses without any real understanding of what the tests mean.
Presentation of quantitative data is more than just about numbers and tables.
Writing your Dissertation Results Section. Writing your Dissertation Results Section. Calculate your price. professional academic help in writing get my discount.
When writing a dissertation or thesis, the results and discussion sections can be both the most interesting as well as the most challenging sections to write. You should write your results section in the past tense: you are describing what you have done in the past. you should discuss how the results help to answer your research.
Sometimes the findings or results section of a dissertation comes in the same chapter as the main discussion. You will need to check with your supervisor what your university department’s rules are regarding these two sections. Whatever the case, there should be two sections if they are in the same chapter; one for the findings [ ]. cranfield masters thesis archive Help With Writing A Dissertation Results Section essays on how customers choose brands write high school essay.
Writing up the results section of your dissertation. So, you have overcome the colossal task that is doing your dissertation research – either primary or secondary, depending on which avenue you chose. very useful guide on how to write up the results section of your dissertation. To help you further, we've broken the information down into. Writing up results - How to write your dissertation. A mondofacto study skills topic to help you write a dissertation. help; contact; sitemap; How to write your dissertation. home; dictionary; word tools; it's time to write it up, and the place for this is the results section. The key to a great results section is in describing your results.