Importance of data and data collection Data Data is an any concept of a matter or incident. This means to give or something given. Data comes from observations made upon reality.
First, you must develop a good idea. Dissertation ideas can come from many places. Do a thorough library search in areas that interest you.
After you have the idea, develop a good question. A good question is one that can be answered by your research, oftentimes using empirical methods. For your paper, you may be interested in looking at whether angels exist. But, how would your dissertation test that?
How would your dissertation measure the presence of angels? When thinking of a dissertation or thesis question, you must also think about the research design.
A testable question regarding angels is "Do people believe in angels? As an example, your survey might simply ask "Do you believe in angels? Developing an Empirical Question An empirical question involves the manipulation of a variable.
For example, other dissertations may have found that more women than men believe in angels.
You might also find a dissertation that reported Catholics believe in angels more often than atheists do. A third research might have reported that people are more likely to believe in angels if the people in their social circles do.
Combine it with a bunch of demographic information from your subjects and you may have a good dissertation. Answering an Empirical Question with Good Data Collection To answer this question, you could randomly assign subjects to two groups.
One group could be shown a news story about a person who claims they saw an angel. The subjects in this group, the experimental group, then complete a survey.
The other group, the control group, does not see the news story, but completes the same survey. What do you include in the survey? Good data collection involves collecting relevant data that adds to the body of knowledge. Knowing that people who believe in angels also eat spaghetti is not particularly useful nor important.
The main thing to remember with data collection is to keep it simple, but important.
And get the data you need the first time out! For this research design, you could collect demographic information thought to be associated with your dependent variable belief in angels.
Age, gender, religion, ethnicity, social network, and frequency of church attendance may be just a few. But how are you going to measure these variables? Are they dichotomous variables?
Is your survey going to use a Likert scale? Obviously, you need to start thinking about your statistics! What statistic s are you going to use?
How are you going to analyze your data? Are you looking for a relationship between two variables? Or do you want to see if one variable predicts another? When you know how you are going to analyze your data, you will know how to measure your variables.As it is indicated in the title, this chapter includes the research methodology of the dissertation.
In more details, in this part the author outlines the research strategy, the research method, the research approach, the methods of data collection. Methodological framework and data collection. from different approaches used in the thesis may be integrated, and how these contrasting data collection, is physically well constrained by the surrounding topography, and is also of a scale applicable to both cultural and environment changes.
Chapter 3 Data Collection Introduction InthischapterIwilldescribetheproceduresIemployedtocollectthedataforthisdisserta-tion. First, Section will discuss the. There are many data collection methods, but how you ultimately choose to collect data will depend on the design of your study.
Below are some common methods of collecting dissertation data and the types of projects for which these methods are most appropriate. 4 Data Collection Methods: Semi-Structured Interviews and Focus Groups example of this is the census survey, which has historically asked respondents to categorize themselves by race categories that have not always fit the self-identity of the respondents.
There must always be data that should be collected, organized, analyzed, and interpreted in any research undertaking. No research activity can be succeeded without necessary data so the data collection is important phase of the research process.