Hey! It’s me again I hope you have read my blog on the dissertation help UK and know my story! But if you haven’t read it then please go through that blog you will get refreshed definitely!
Well today I am here for some fun tips of data collection and analysis which I used in my dissertation they helped me a lot so I thought of sharing it with you all.
It’s kind of irritating!
Yeah I know that it’s kind of very boring to collect that data and interpret them in answers that are required for your studies. (Actually) and main problem occurs when the respondents do not fill the surveys properly. Oh wait have I discussed with you type of methodology used? Nah! So let’s first understand that;
How data is collected!
You can have detailed process of data types and collection here as I am specifically going to have a small discussion of the methodologies. There are two types of methodologies specifically;
Depending on a type of your research…….
You have collected the data. Now it’s time to analyze your data. So the main tips are:
Complete your data collection:
What I meant by completion is that there are number of people who either ignore or forget to answer a question or part of your research. This creates hole in your data which results in imbalance of your data. Figure out the data answers if either they are properly marked or not.
Interviews:
People do not answer certain questions. Try to manage that answer with their other answers or request them again to answer that question again.
Observations:
Re-check if all the observations are properly addressed in a perfect manner. If you’re missing any point? All participants are being observed without any biasness or not?
Surveys:
Some surveys are filled carelessly or incomplete try to eliminate them from your research.
Experiment:
Check the results of the experiments does it go with the hypothesis or not?
Check Data Relevancy:
It was mentioned in one of tips of UK dissertation writing that “Triple check your data before making any analysis” on your data and do not run the analysis on real file. It may cost you any problem as in: loss of data or changed data into other number or missing data.
Check the data for:
Does it go with hypothesis?
If your data is not going with the hypothesis it means you have done certain blunder in your research. Figure out that blunder.
Is data making any sense?
You have collected data. Great but is the data making any sense or not? If its for both genders have you contacted equal number of participants or is there more male response of your data which makes it imbalance.
Is data coming to a concluding point?
I know you haven’t analyzed but you can guess if its going in right direction or not by answers given by your target audience.
Is there any negative impact of data?
Check if your data is going in right direction or not by quick review of data collected.
Organize the data:
Organize the data in a manner that helps you in understanding and using it as in:
- Is data chronologically arranged?
- Did I mention all the relevant information required?
- Is my real data saved on other sheet?
- Do I have a backup data plan if I lost data?
- These are the major areas in arranging your data like a pro.
Select proper tools for data analysis:
Different data is interpreted by different types of tools as in SPSS software which is more useful in dealing quantitative data and analyzing the surveys and numeric answers so there are number of software which can guide you about data analyzing.
Anyways, when you select a proper data analyzing tool it helps you in interpreting the data in proper manner. But first you need to organize the data to run the tool.
Find out real drawbacks of your data!
Congratulations! You have run the analysis on data and dint find anything bad or irrelevant but the fun begins if you have found something that changed your whole results. As acknowledged by Thesis Writing Services;
“Many of the dissertation help we cater comes from the people who lack the skills of analyzing the data through different tools and software so we provide them help with their data analysis.”
It’s time to interpret the data:
The major part of dissertation writing comes here. The time you start interpreting the data the real joy come as you figure out if the whole dissertation have gone according to your plan or not? If it goes with the hypothesis than its good otherwise you need to take UK dissertation writing help from someone. This is the major part which decides that either the literature reviews and your own research goes together or not.
Finally the results:
All the hard work is paid off when you get the exact result according to your dissertation. It’s a genuine luck to get the good results in first go and finish your dissertation in a quick manner.
Whoa! I am tired now!
I dint knew I have written so well about data analysis tips! A big applause for me! Yayyyyyyyyyyy! Anyways! I Hope you enjoyed my write up. Well I enjoyed time spent in writing this blog as I shared my own experiences with you all. C’ya soon bye
Applicability
Never blindly follow the data you have researched. Try to confirm the information the satisfy with the objectives of the investigation. All the information should be relevant and appropriate for your study aims. Any irrelevant or inappropriate date will show the lack of focus and Confusion in the thoughts. Simply you will have to show the same level of assessment when it comes to the information you include in the thesis itself. Be expressive toward the reader as it can help you explain theoretical reasoning in your data selection and analysis. You tell that you can reflect logically and brome the centre of the issue. These lies can create a discuptancy in the overall writing of the text.
2. Analysis
You must use sources the fits both type of data complied and goal of the studies. Clarify and justify the methods with the same carefulness with which you collected procedure were justified. Clearly, show the reader that you didn’t choose your system randomly. Instead, show than the best choice based on extensive study and profound reasoning. The main purpose is to identify the basic patterns and trends in the data and display the results importantly.
3. Foreseeable work
Calculable data, which is distinct from the logical and practical study, and to some degree, sociological and other restraints, needs simple numerical examination. By collecting and analysing measurable information, you will be capable of drawing conclusions that can be generalised outside the model (assuming that it is demonstrative – which is one of the required procedures to carry out in your analysis) to a public. In social sciences, this tactic is occasionally mentioned to as the “scientific method,” as it has its ancestries in the natural sciences.
4. Qualitative work
Qualitative data is normally, but not uninterruptedly, alphabetical and occasionally mentioned to as ‘soft’. Though that doesn’t mean that it wants less questioning perception – you will still need to carry out a thorough study of the information collected (e.g. through thematic coding or discourse analysis). This can be a really time-consuming task, as analysing qualitative data is a process in which you repeat the checking process, sometimes even requiring the different high-end software to check. It is important to remember that the goal of search utilizes the qualitative method is not to create statistically graphic or valid findings, but to expose more profound, transferable knowledge.
5. Thoroughness
Remember The data can not itself tell you its authenticity. Believing it ensures a particularly common mistake in qualitative studies, where students doing study often present an assortment of quotation marks and think this to be enough for the thesis actually it is not. Instead, you must carefully check all data which you will use to support or reframe academic positions, demonstrating in all areas an inclusive engagement and critical standpoint, especially about possible chooses/bias and foundations of error. You must acknowledge the limitations of the information as well as the strengths of your data, as this shows the credibility of the academic work.
6. Presentation strategies
It can be a serious problem to represent a large number of data in these ways. To speak about this problem, consider all possible ways of giving information about what you have gathered. Charts, graphs, diagrams, quotes and formulae all deliver special benefits in certain situations. Tables are another brilliant way of giving data, whether qualitative or quantitative, in an orderly fashion.
The vital thing to remember is to retain is that you should always keep your reader in attention towards you when you show your data – not yourself. While a piece of specific information may be clear to you, ask your inner self whether anyone else will be equally clear understand this who less acquainted with your research. Often times, the reaction will be “no,” at least for your first draft, and you might need to reconsideration your presentation style for the dissertation.
7. Appendix
You might see your data analysis chapter looking like a messy, yet still feeling reluctant to cut down it slowly that the data which you have spent such a long time collecting. If information is relevant but is hard to adjust within the writing, you might need to transfer it to an appendix section. Datasheets, sample questionnaires and transcripts of interviews and focus groups should be placed in the appendix. Only the most related extracts of info, whether that be statistical analyses or quotes from a candidate, should be used in the Dissertation itself.
8. Conversation
In discussing your info, you will need to show a capacity to recognise trends, patterns and themes within the data itself. Consider different imaginary descriptions and balance the pros and cons of these different standpoints. Discuss loopholes as well as strengths, assessing the Importance and impression of everyone. If you are using discussions, make it certainly possible to embrace representative quotes to in your discussion.
9. Findings
What are the vital points that appear after the breakdown of your data? These results should be clearly defined, their declarations should be supported with strongly reasoned reasoning and experimental support.
10. Relation with writing
Near the finish of your data analysis, it is recommended to start by comparing your data with that available information of other academics, considering points of agreement and alteration. Are your conclusions dependable with anticipations, or do they make up a controversial or borderline position? Discuss reasons as well as effects. At this stage, it is important to know what, exactly, you said in your literature review. What were the main ideas you identified? What were the breaches? How does this relate to your conclusions? If you aren’t able to link your results to your dissertation, there is something wrong – your data should always fit with your analysis question, and your problems should be related to the literature. You must show this link clearly and unambiguously.
These are the main tips that will help you with data collection and analysis of the dissertation. If you are a nursing student, then Nursing Dissertation Writing Help UK for hiring a professional writer to write your thesis. You can also employ other services to complete your work. We are sure you will find these tips very helpful. Take care of yourself and study through out the year to complete the thesis
