Fallacy is actually an error in a way of thinking and interpretation which is most of the times based on wrong suppositions and statements. Researchers usually know that when they go erroneous and with such fallacies they are at risk too. The two most important research fallacies are;

• Ecological fallacy

• Exception fallacy

Ecological Fallacy

Ecological fallacy is made when the assumptions are made with reference to the individuals that are based on assessment of group data or the suppositions that are made on statistical form to have an aggregate collection of data from the area such individuals belong to.  In the ecological studies the facts provided are true and useful but conclusions that are made on certain facts and figures are generally weak because that is not authentic for the rest of data related to specific research. This fallacy is most of the time used by the enthusiastic researcher who wants to prove their abilities to some extent. Ecological fallacy mostly occurs when the statistical data is being used and by mistake interpreted wrongly or incorrectly.

For example: a researcher may state that in such colony rents of the houses are $20,000,then its not giving the actual results and discrepancies may be found about the rent to be $15,000 or any other amount.

Exception fallacy

Exception fallacy is opposite of ecological fallacy, means that suppositions are made for the grouped data by the assessment of individuals. Evaluation is done simply on the basis of assumptions that are made by experiencing only one person or thing from the rest of population Exception fallacy most of the time arises in discrimination of gender and stereotyped.

For example:  a guy saw a woman driving a car  and making errors in driving and disobeying the rules, so he concluded that all women are bad drivers and its assumption is wrong.

Explanation

It doesn’t meant that the above mentioned fallacy are always wrong but they are supposed to be because the process of collection and disaggregation data show a discrepancy at some extent that not portray a true picture so at that time investigator, researcher and analyst should be more careful and in general both of these fallacies are a part of one’s normal life and also in research as well as in everyday interpretation.

An explanation can be made in such a way that the countries where coffee is highly consumed have lesser number of heart diseases then it doesn’t meant that everyone should start drinking coffee to have lesser heart diseases because it’s not possible that everyone is coffee drinker in that country rest of them may doing exercises to make themselves healthy and for that reason they are safe from heart diseases because it is just an assumption by only one person and authenticity and validity is not sure.

References

• www.socialresearchmethods.net, accessed on March 26, 2012.

• Achen, C. H. and Shively, W. P. (1995). Cross-level inference. University of Chicago Press.

• Freedman, D. A. (2001). Ecological inference and the ecological fallacy. International Encyclopedia for the Social and Behavioral Sciences, 6, 4027-30.