Final Comments.… on Is it ethically okay to use in… psuc15 on Is it ethically okay to use in… Last comments YAY! :… on Is it ethically okay to use in… psuc97 on Is it ethically okay to use in… 22nd feb comments… on Qualitative Versus Quantitativ…
Information and Internet technology has developed expeditiously in the recent years. This put forward the opportunities to enhance a research through the internet. Data collection has became a lot easier and the data collected would be more “generalisable” to the entire population because there is a really huge group of potential participants (that the age, job, location of the P are all varied). However here comes a problem : whether the data collection/sources would be ethical?
To protect participants’ privacy, it is necessary that letting the participants aware of the fact that they are going to take part in the research(informed consent) and if the data is collected through some websites(instead of online survey/questionnaire) that considered as private site(personal blog or personal website), the best way is to contact the owner of the site first to seek for permission to use the information. In addition researchers should not directly quote from the website that may be addressed by the searching engine, for example google.
Other than ethical problem, there are few more problems that researchers should be aware of, for example the researchers have to identify whether the information on the internet is real or not. Therefore we should be careful when selecting,filtering and/or collecting any information/data on the internet.
In my opinion, if the researchers can carry out the research step by step following the guidelines, there should not be any problem(minor problem may appears like normal research usually has). And carrying out research by using the internet would be far less time consuming and easier for both researchers and participants. And might as well become the trend of researching in the future.(But surely will be more developed, like the structure and rules/guidelines would be clearer)
I commented at 23:51 😥 lol (blog owner didnt set the time right!:( )
Can correlation show causality?//Correlation does not equal to causation.
Correlation refers to the departure of 2 variables from independence.
In psychology, Correlation is defined as a statistical measurement of the relationship between two variables. Correlation is computed/calculated into the correlation coefficient, which ranges between -1 and +1.
Relationship means there is an association between two variables. Positive correlation is as one variable increases, the other also increases, and vice versa. Positive correlation is represented by Correlation Coefficients greater than 0. (from any value > 0 to 1, the closer to (+)1 indicates the stronger correlation). Example of positive correlation could be time spent on revision and exam result; the longer time spent on revision get better results. Negative Correlation is as the amount of one variable increases, the other decreases (and vice versa). Negative correlation is represented by Correlation Coefficients less than 0. (from any value < 0 to -1, the closer to (-)1 indicates the stronger correlation).
Causation/causality is the action of causing or producing; the relationship between the cause and effect.
These two terms sound similar but they are different, Even if two variables are legitimately correlated, there is not necessarily any causal relationship between them. An example is there is a relationship between reading ability and shoe size. If an individual performed such a survey they would find that the larger shoe sizes correlate with better reading ability, but this does not mean large feet cause good reading skills.
Correlation does not imply causation. Correlation is more like suggesting a relationship between the variables whereas causality is talking about the distinct relationship between the variables (= cause and effect). Just because two events correlate does not mean that one has caused the other. The Latin term for such an error is called “non causa pro causa,” which means “non-cause for the cause.” It is important to become more critical.
Is it possible for us to be 100% sure that a correlation between two events indicates a causal relationship? It is IMPOSSIBLE, actually. The knowledge provided by the scientific method is never 100% certain. Science allows us to remain open to the possibility that new evidence will cause a change in what we already know and believe. However, the scientific methods (correlation coefficient here) can always act as a clue, therefore we can investigate more from that point, and with the stronger evidence and enough information, we can justify concluding a strong correlation between two variables points to a causal relationship.
little back up 😀
An advantage of the correlation method is that we can make predictions about events/things when we know about the correlations. If two variables are correlated, we can predict one based on the other. Just like the predicted grade system in UCAS allow the universities to decide which student to take(give offer)and who to reject.
The disadvantage is that a correlation tells us that the two variables are associated, but we cannot say anything about whether one caused the other. This method does not allow us to come to any conclusions about cause and effect.
Always remember the crucial principle: Correlation is not Causation!
For the new semester and the new blogging life, I chose the topic that I found interesting, “Is the term “approaching significance” cheating?” (cheating sounds fun!) 😛
When the result of a statistical test is significant, it means that it is unlikely to occur by chance therefore the testing hypothesis is valid/true.(at the critical value/ significant level of 5%=0.05)
For example, the research report I have done in semester 1 on reaction time, which used a paired t-test compare the 2 different conditions revealed a significant difference. (Between narrow variability distribution and wide variability distribution) In this case, simple easy straight forward! We can just stated there is a significant difference between the two, no hassle at all.
However, if the researchers/investors spent a lot of money and time for one particular research and are hoping for a definite yes or no (in the worst case), but when they come to the results, it is just ~0.001 away from being significant, (I think it is worse than being not significant) it would be a total nightmare. And as mentioned they already invested a lot on it and possibly cannot afford another re-test anymore, which I think it is acceptable to say it is approaching significant. And it does not involved cheating as approaching means “close to” therefore people should be able to understand.
In conclusion, if the term “approaching significant” is not used by purpose (to confuse people), it would be adequate and acceptable. But in most of the cases when researchers really want to reveal significant difference and the result is just an “approaching significant”, it would be better to do a re-test in order to support the result. (Therefore it won’t be an error or may even get a significant difference at the re-test which support the testing hypothesis)