In theory they are very important. Without statistics it is almost impossible to come to an informed conclusion in any piece of research. The use of statistics is wide ranging in the field of research and without the use of statistics it is virtually impossible to interpret a true meaning of what the research shows.
There are, however, some reasons why statistics may not be as important as some people may think. A paper written by Dr Dennis Roberts (a statistics lecturer) gives an in-depth perspective of what he believes is the "overrated importance of statistics in research". These views can be read on the following website and will give additional views on the subject: (www.personal.psu.edu/users/d/m/dmr/papers/Roberts.pdf).
Statistics, no matter how carefully collected, can always be flawed. Finding an accurate sample, is one of the biggest problems facing those attempting research. Without a sample of thousands of people (ensuring they are representative of the whole population), you cannot be certain that the results can be wholly generalised. In addition to this, statistical information can be easily manipulated to show very different results.
One clear example of this was the Olympic drugs testing story. When drug testing in the Olympic participants was increased, one paper reported that during the four-year period after it had been introduced, drug taking rose by 10 per cent, however, another paper reported that this same statistic meant that actually they had managed to catch a further 10 per cent of drug takers meaning that the scheme was a success.
There are, however, some reasons why statistics may not be as important as some people may think. A paper written by Dr Dennis Roberts (a statistics lecturer) gives an in-depth perspective of what he believes is the "overrated importance of statistics in research". These views can be read on the following website and will give additional views on the subject: (www.personal.psu.edu/users/d/m/dmr/papers/Roberts.pdf).
Statistics, no matter how carefully collected, can always be flawed. Finding an accurate sample, is one of the biggest problems facing those attempting research. Without a sample of thousands of people (ensuring they are representative of the whole population), you cannot be certain that the results can be wholly generalised. In addition to this, statistical information can be easily manipulated to show very different results.
One clear example of this was the Olympic drugs testing story. When drug testing in the Olympic participants was increased, one paper reported that during the four-year period after it had been introduced, drug taking rose by 10 per cent, however, another paper reported that this same statistic meant that actually they had managed to catch a further 10 per cent of drug takers meaning that the scheme was a success.
