Terry
What does it mean? I am in a hurry. Can you explain it to me? Statistical manipulation of existing sets of data about human societies may be a partial substitute for experimental techniques, but it could be argued that few convincing data sets exist. What does it above mean? I am in a hurry. Can you explain it to me?Typically science is seen as characterized by the testing of hypotheses through experiment. The experimental method is largely closed to political scientists since they do not possess the power to dictate to whole human societies how they should behave. In any case, experiments require identical control groups for comparison which, it is arguable, cannot be created. Some small-scale laboratory simulations of human power situations have been attempted with interesting results, but the applicability of the results of these to whole societies is disputable. Statistical manipulation of existing sets of data about human societies may be a partial substitute for experimental techniques, but it could be argued that few convincing data sets exist. Some attempts at marshalling these include the World Handbook of Political and Social Indicators, and the Country Indicators for Foreign Policy Project at Carleton University, Canada. One very basic problem for international data sets is that many countries do not have reliable population figures, for example Nigerian census figures have been politically contested because of their influence on the ethnic balance of power. It is also difficult to compare financial values in different currencies because of artificial exchange rates and differences in purchasing power.
Nov 8, 2018 9:05 PM
Answers · 6
In an experiment, you take two groups, keep conditions the same for one, and change conditions form the other. You then make conclusions based on the different results. You can't do that for sociological questions: you can't change the nature of a whole society just to answer an experimental question. So, you use statistics instead. You look at data for existing countries, and you examine how different factors correlate with each other. However, statistics requires good data: if you do good statistics on bad data, you get bad results. The authors think that most major datasets have bad data. They gave a few reasons why they think the data is bad.
November 8, 2018
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Terry
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English, Korean
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