Thank god it is the final blog. For the past 6 months I have been stressing about what to write about seriously how much can someone write about stats? I hate stats it terrifies me I find it so difficult to get my head round as soon as I see numbers and letters pretending to be numbers my brain just freezes. Its takes me all week to motivate myself to try and start the blog and then it takes me hours to actually write something. Within them hours I have stressed myself out, got annoyed with myself and cried all before I started writing the title. Maths has always scared me I don’t get numbers; I would rather sit at the back of the class messing around being the class clown rather than look stupid in front of my class mates. Even with the seminars now I have stopped going because all I do is sit in the background trying to get my head around the question but even before my brain has even tried to figure out what the question is asking me someone has already answered it so I stay at home using my books and the internet to see if I can get my head around it and get the answer myself which I probably would get wrong but I feel a little bit better that I’m giving it ago at least. I feel stupid when I try and ask someone for help because they give me that look like you seriously don’t know this are you that stupid, then when they explain it to me they don’t explain it in a way my head can figure it out so I just agree with them because I hate the thought of them thinking this girl is thick. This especially goes through my head when I’m writing comments I’m worried of what people are going to think about what I’ve put especially if it’s wrong. I’ll stop now because I’ve probably bored you to death with my rant but I am very happy these blogs are over. But next time someone you feel looks ‘stupid’ or ‘slow’ just think they may be struggling and just need that little extra help.
Is gender bias still an issue in psychological research today? And does this research only really tell us about male behaviour? Simone de Beauvoir (1949) stated the, ‘Representation of the world, like the world itself, is the work of men; they describe it from their own point of view, which they confuse with the truth’.
Hare-Mustin and Maracek suggested two ways in which gender bias can formulate in psychological studies, Alpha Bias and Beta Bias.
Alpha bias is the tendency to assume that there were real and permanent differences between males and females. Freud’s research into psychosexual development is a strong example of alpha bias in psychology because he viewed females as being inferior and jealous of their male counterparts.
Alternatively, Beta bias is the tendency to minimise the differences between males and females and assuming that females are similar to males in all aspects. Kohlberg’s research into moral reasoning is an example of beta bias because he assumed that the results he obtained from questioning men about moral dilemmas would apply to women.
As most studies are conducted by men, and most participants are male too, it can be difficult to completely remove all forms of gender bias from a study. Sampling may be biased, as in Zimbardo’s and Milgram’s studies, which then leads to generalizing results from all male research to women. Also, gender biased hypotheses may encourage stereotypical beliefs about gender differences between males and females and promote inaccurate beliefs about female behaviour.
All in all, I believe that gender bias is still an issue in some aspects, but with the development of science and the way we conduct our research now, it has become less of an issue than it was in the past. With more and more female psychologists now conducting their own studies and the issue of gender bias being more apparent, I believe that gender bias towards males will eventually be subdued with time.
Thank you for reading 😀
Reliability is one of the things that make a research worth paying attention to. When psychologists report their research as reliable, it means that no matter how many times they repeated a certain event, similar results would often occur.
However, why is reliability such an important factor when it comes to research? It is argued that reliability is important in research simply because it can tell you whether your experiment was any good or not.
An example I read on another blog which I thought was good to show reliability, was if your weights tell you every time you are two stone lighter then the scales would be high in reliability as it consistently tells you, you are two stone lighter. This is similar to experimental research; if your experiment keeps giving you extremely different results when you tested it time and again, you would come to the conclusion that it is not a very good experiment.
There are different types of reliability researchers use in order to test their own experiments. The first one is called Internal Consistency; this means that people answering a questionnaire for example, should all answer in the same way depending on what type of group they have been put into e.g. extraverted people or introverted people. This measure is good because you can clearly see if the questionnaire is reliable and if it needs to be changed in any way. The second one is called Test – retest; this means that people might be given one test and then they repeat the test in order to gain reliable results. However, the problem with this is that if people have already been tested they might already know what to expect from the questionnaire and therefore their results might not necessarily mean that the questionnaire is reliable. The last one is called Interrater; this means that two people observed the same behaviour and they should agree on what is happening. Moreover, if the people agree on the behaviour then it can be suggested that this is reliable. However, the problem with this is that the two different people might have described the behaviour in the same way, but they might not agree on the meaning of the behaviour.
In conclusion, reliability is important when it comes to experimental research because it can show us whether what we are measuring is actually good. However, sometimes the way we test for reliability might not necessarily be reliable in itself.
my computer is playing up it wont let me add anymore ill keep trying.
The joys of writing another blog while watching the Simpsons J
The definition of science or scientific is the knowledge that is gained from observations, study and experimentations that are carried out, so that researchers are able to answer questions or find out more about what is being studied.
Firstly qualitative research; put simply it explores the why of our area of interest, instead of the ‘how’ like in quantitative research. This can be done through the means of observations, interviews, phone conversations, videos, as well as many other ways. It enables the researcher to get a view of certain conditions, as sometimes the average of the results doesn’t give us insight to individual differences, which can be important as it allows other suffers and even those treating these individuals more knowledge of the various and possible effects.
Unlike qualitative methods, quantitative methods use numbers and analyse them through the use of mathematical or statistical means, such as SPSS which we all know about, and by doing this we are able to explore our hypothesis, something that we do not have in qualitative methods. Instead of looking at specific individuals, this method looks at the relationship between an independent variable and a dependent variable, and what is reported about the relationship between the two needs to be objective.
So just because the qualitative methods doesn’t use numbers or statistics, does it really lose its right to be classed as scientific? quantitative research methods are considered to be clear and powerful, which is a good thing for most things, it allows us to examine and explore all different areas such as affect, individual differences and many more things that quantitative does not do, and could in fact could distort the opinions of the participants. I think it is fair to say that both methods have their uses, a few points for the uses of qualitative methods are things such as gaining insight in individual cases, so that we are able to gain understanding, which allows us to gain a real life information. However, this is not always applicable or necessary for some studies, and this is where the quantitative method comes in handy as it, allows us to see how much of a percentage of Bangor University students like Malibu compared to Vodka, which allows us to generalise to a certain extent to the overall population just for an example.
So I think I have established that they both have their uses in regards to whatever you are wanting to study, and I think if we were just to use quantitative methods we would miss out on a great deal of information in terms of individual cases, therefore I would conclude that they are both scientific in their own right, they both provide us with vital information, just in different forms.
But what do you think?
Do we really need ethics or do they get in the way? Before even considering creating a study to research a certain topic the researcher needs to take into account if they will be going against the laws of ethics and if they are able to even start the study if they follow them. These laws are set up by the ‘British psychology society’ (BPS) following the devastating research conflicted in the second world war in the concentration camps this was to make sure the researchers are being honest and respectful towards the results of each individual taking part.
There are five ethical principles; consent, debrief, the right to withdrawal, no harm and no deception. If we look closely at these principles it would be very difficult to follow these and create a study worth doing. We have to deceive so the research shows a realistic result, is this only way to create a study? Milgram’s study of obedience is the perfect example to prove this as if the participants were told what the study entailed the results would be invalid as they would of know the shocks were fake so they would defiantly continue to the maximum voltage so does this make it okay to go against the principles? Similarly Zimbardo (1971)study the Stanford prison experiment was extremely unethical however participants admitted they learnt values about themselves so was the study successful? So would these studies be as successful if they followed the laws of ethics?
Who stays? Who goes? You decide 🙂
The joys of having to discuss another statistical question: when I was thinking about this question I was like what data? Who was more likely to win the grand final St Helens or Leeds Rhinos? Which mascara would make my eyes lashes longer or which aftershave is more likely to help the boys get laid? We receive data every minute of every day with any action I take. However in these situations I don’t actually have time to make a statistical analysis on what best course of action to take except when I’m in the bookies. So in everyday life we don’t really need stats to understand what is best to do and somehow we seem to cope and my eyelashes still look good.
However, when we spend hours doing our research and collecting our data, stats are a good tool to use when trying to understand our data and can be used to represent our findings in a single line of a statistical statement and with the help of the beautiful invention of SPSS which does this all for us we can easily analyze our data. With the help of graphs and tables we can discuss our findings. If one relies purely on stats, they may miss something crucial and glaringly obvious about the data being analyzed. An experimenter can analyze the data in the wrong way or choose accidentally not to take into account something that has controlled the course of the data because they may not believe its important data with data such as age or gender.
We do stats to help us to understand our data in a manageable concept however we do need to take into account other aspects of our research to gain a representative conclusion of our study.