There are numerous types of recent and historical evidence that I could obtain, in answering the proposed question. It would be interesting to look at the number of students at the university, and how this has changed over the years. I could obtain this kind of information by perhaps asking the administration staff at University House, or looking in the university archives. I could then, assuming that more people attend the University now, than in the 1970’s look at the rate of acceleration of the number of students over the years by producing a time series. This kind of quantitative evidence would be indirect and intentional, as quite clearly the numerical data would have been kept and recorded deliberately, for later use. Other numerical data I could look for in the university archives is how much the number of international students has changed over the past thirty years. I could again, look at a time series, to show the differences between the number of international students now, compared to thirty years ago. I could also do this with looking at gender, to find out if there were any differences in the gender distribution, and how this affects, or affected the student life at Lancaster. I could also obtain details of student loans, and compare this to the financial system that was in place when Lancaster University was first established. It would be interesting to look at quantitative evidence of the student’s, past and present, financial situation, to see if this reflects the different ways in which they live. This evidence could be obtained from Local Council files, government files, or again, from Lancaster University files.
It can be seen here that a considerable amount of quantitative evidence can be used in answering the question of student life at Lancaster University. The information can be collected from a number of sources and brought together to be compared with similar data from different years. Such data is valid and can be very useful in researching certain topics. However, there are also limitations, which must be considered in using the data. Some numerical data may contain proxies, or gaps showing missing data, which could raise issues of validity. The comparability of the data must be taken into account, and whether or not the categories, or the way the data has been collected, has changed over time. Questions should be asked such as who collected the data and what were there reasons? This will help establish just how valid the information is.
Other quantifiable evidence that I could use in answering the research question could be questionnaires for past and present students. I could ask them questions on their life at Lancaster; whether they participated in any clubs or societies, what they did for evening entertainment, how they managed their finances, what was important to them as a student. I could how also look at how they arranged their social lives (for example, at present, the mobile phone is appears to be a key possession of students and for many, an essential part of their life, yet ten, of even five years ago, most students would not have considered owning mobile phone). This is an example f quantitative evidence, as I could show the results of the questionnaires as numerical graphs and charts. This would obviously be “intentional evidence” (Knopf, 1953:60), as it would be collected for the purpose of answering my specific question. I would also have to make sure that I was using a representative sample of people. As there are far too many past and present students, I would have to draw on a smaller sample that would represent the students as a whole; for example I would need to ask an equal percentage of male and female past and present students, a representative sample of international students and students with varying types of degree.
Although some researchers regard quantitative data very highly, and believe that it is superior to other sources of evidence, others believe that it is on an equal level with, or even less respected than in some cases, qualitative evidence. Despite the fact that it is believed that statistics cannot be disagreed with, it can be seen that they can often be distorted and manipulated, in order to show the desired results. For example, a researcher could ask specific questions on a questionnaire in order to find specific answers, particularly for closed questions, where the possible answers are very limited. Qualitative evidence, although it cannot be quantified or counted in any way, can often be more reliable, as it allows people to give the full story without being guided in any way. Similarly, it is much harder to argue with such evidence, as they are often people’s own opinions or perceptions.
In answering