Research Paper on:
The Use of Power Analysis in Statistical Analysis

Unformatted Sample Text from the Research Paper:
hypothesis is proven, and can be accepted or needs to be rejected. To understand the role and importance of power analysis we have to consider the way in which there  may be flaws with the usual approach to hypothesis testing. The acceptance or the rejection of the null hypothesis will depend on the probability, known as the alpha (?),  the usual approach is to have the barrier set at a 95% level of probability which is an alpha of 0.05. If, when the test is conducted the probability is  less than the alpha the null hypothesis is rejected if it is over the alpha value the null hypothesis is accepted. In this way the process of hypothesis testing may  be seen as similar to a search for evidence, the search is undertaken to look for a way in which the null hypothesis can be rejected. For example, we may  want to assess if there ids the demand for a budget airline travelling to the United States, here the null hypothesis will state there is no demand and to prove  the hypothesis we are looking for evidence to reject the null hypothesis. There are three factors generally seen as influencing whether the null hypothesis. The first is the level  of confidence that is set, meaning the alpha. This is an arbitrary measure at best, and the potential here is a type I error where the null hypothesis is rejected  when it is true. In this case a search may be interpreted as finding a search finding something that is not there. The second generally accepted principle is the  sample size. This helps to reduce the potential of the type I error, the larger the sample size the less chance of the error emerging, however it can also be