Homework for my TA 21/11/11

November 21, 2011 at 11:16 pm (Uncategorized)






Permalink Leave a Comment

Are qualitative methods less scientific than quantitative methods?

November 21, 2011 at 10:39 pm (Uncategorized)

Well to even begin answering this question, we need to look at how you would class something as scientific. Science needs to be objective, valid and reliable. I would argue that conducting research to gain qualitative data can be just as objective, valid and reliable as research gathering quantitative data. There are many ways in which it can be objective, for example, increasing inter-rater or inter-observer reliability. Having multiple observers means that experimenters can put their data together and therefore increase reliability and objectiveness of the study. There is also one major advantage with qualitative data which could make it more reliable. Both quantitative and qualitative data are subject to human error, however, quantitative data collection tends to involve more computers and other technology whereas qualitative tends to be written data or observation so there is a decreased risk of machanincal error, increasing reliability.

 I think that although there are many people who believe that quantitative methods are more scientific as they produce statistics and the results can be gathered via experimentation. Although quantitative research is not gathered by experiments, but via methods such as observation, questionnairs, interviews etc, it does not necessarily mean that the data collected cannot be statistical. There are methods such as coding ( identification of categories, themes, phrases or keywords and assigning them a numerical value.) which can then be analysed and converted into statistical data.

If we look at both qualitative and quantitative data collection in terms of objectivity, reliability and validity, there is not all that much difference. I would argue that what makes an experiment scientific is not the form of data collected, but the procedure involved in collecting it. Most errors which make a reserch project uncientientific are due to human error, error with the research design or technological faults, all of which are due not to the type of research conducted, whether it be qualitative or quantitative and therefore i would argue that they are both as scientific as each other.

Permalink 11 Comments

Homework for my TA, week 4

October 27, 2011 at 1:20 pm (Uncategorized)








Permalink Leave a Comment

How can we ensure that our findings are useful to people outside the scientific community

October 23, 2011 at 5:01 pm (Uncategorized)

As most of you know, there are many areas of psychology. Although most people think that the main area of psychology is the clinical side, which of course makes it hard to generalise to tdkhe wider community, there are many areas in which the research conducted would make it relatively simple to generalise. Here is a basic list of some of the occupations that can be done oce you have a psychology degree: http://www.psychologycoursehelp.com/whatcanyoudowithapsychologydegree.html

Research done in any of these fields could be widely used throughout the world. Take, for example, advertising and sales. the use of research in this field could show us exactly how is the best way to arrange our adverts to appeal to consumers best. http://onlinelibrary.wiley.com/doi/10.1002/mar.4220030203/abstract. this link shows research conducted on the best  colours to use for maximum readability.

if we look at education, there is much psychological research conducted on the best way to learn. http://rer.sagepub.com/content/50/2/315.short. This shows different learning styles in the classroom.

There are hundereds of different areas of psychological research which is conducted specifically for the non scientific community, but what about those smaller fields which are specific to the scientific, and more commonly, medical community? Well, clinical psychology is also widely useful for the public in general. There are many areas of clinical psychology that allow early detection of some disorders, and therefore easier treatment. Mild psychological illnesses such as depression affects 8-12% of the general population at any one time in a year (http://www.mentalhealth.org.uk/help-information/mental-health-statistics/common-mental-health-problems/). It i areas suchs as this where research into clinical psychology is useful for the mass population.

Research such as this can be used by people of all ages, whether they are part of the psychological, scientific or general community. most psychological research conducted can be generalised to the world without much effort. One of the main attractions that psychology holds for people is that exact reason. psychology is the stdy o meaning behind everything we do throughout our live, how we think, feel and behave. For that reason, i would argue that it is almost impossible to conduct research which doesnt generalise to the wider population.

Permalink 9 Comments

Homework for my TA :)

October 14, 2011 at 2:49 pm (Uncategorized)








Permalink Leave a Comment

Is it dishonest to remove outliers?

October 10, 2011 at 8:22 pm (Uncategorized)

I think the real answer t this question lies completely with the reason for removing the outlier(s). There are many goo reasons why an outlying piece of data would need to be removed. How many of us has participated in a questionnaire sent through the post and just ticked the boxes which made a nice pattern? Have you ever stopped to think how much that might screw up someones research? If it is clear from the data that the participant was not answering honestly, for whatever reason, then it seems only sensible to remove the outlier as I do not think it counts as data at all. It is merely a pretty pattern drawn in tick boxes, it might look nice, but it is hardly useful as data. There are a few other reasons in which removing outliers is ok, such as if whatever technology is used to gather data was not working correctly, or if information was recorded incorrectly. In short, it is acceptable to remove any data which is not incorrect or was not, for whatever reason, was not collected correctly.

There are, however, some outliers which are important to keep in the data set. Say, for example, you are looking at the effect of a particular exercise regime on teens in a population. If you got some outliers which are either drastically above or below the average weight for their age and gender, it is important to keep this data as it could show that more research is needed to discover exactly why these people were affected differently.

I think that as long as the reason for deleting the outliers is due to some form of error on the part of either the researcher participant or measuring then it is acceptable to remove them. The only way it becomes dishonest is if the outlying data is significant and the researcher removes it so that the data will fit his/her hypothesis.

Permalink 6 Comments

“Do you need statistics to understand your data?”

October 5, 2011 at 2:32 pm (Uncategorized)

I think this completely depends on what type of data you are dealing with. For most data that we see around us practically every day, being able to understand and interpret statistics is a huge benefit. Lets face it, if you get given data saying that 70% more people prefer one shampoo brand to another and you don’t know what percentages are, you are going to be a little bit stuck. However, if you are given a bar graph showing exactly the same information, you don’t even need to look at the numbers to see cleaarly thaat one type is more prefered than others, although an understanding of statistics is needed to create the graph in the first place.

There are many computer programmes available now with which you can ssimply input a list of numbers and it will make sense of them for you, so in that sense, an understanding of statistics is not necessarily repuired. However, if you have a greater understanding of statistics, then even if this programme is used in order to interpret your data for you,  it becomes easier to make a more in depth, complete and detailed analysis of the data gathered.

Statistics, although not essential for interpreting certain types of data, is crucial when a better understanding and a more in depth analysis is required.

Permalink 8 Comments

“Are there benefits to a strong statistical background?”

September 28, 2011 at 5:28 pm (Uncategorized)

I would say that there is no need to have a strong statistical background in every day life, although, of course, in many preffessions it is useful. Generally, however, there is a need for some sort of knowledge of stats, even just a basic one. Statistics are used every day, if not all the time. We are constantly bombarded by statistics in media, for example, adverts which tell us that 75% of people prefer one type of mascara to another, or in newspapers telling us that 1 in 5 people will end up being affected by some sort of economical crisis. Even if that is not of interest to us, ther are many other areas of everyday life that involves statistic, even without us thinking about it. For example, when we compare prices to find the cheapest loaf of bread at the supermarket. Statistics is all around us, and for that reason I would argue that even though a strong background and knowledge is not necessary, it is essential for all of us to have at least a basic understanding of how stats works and how this impacts on each of individually.

Permalink 5 Comments

« Previous page