One Way Anova, Essay Example

How can the application of one- way ANOVA be used for decision making?

“ANOVA can be used to compare the results from more than two sets of data at the same time, and how it is particularly useful in analyzing data from designed experiments.” (Burke, 1997). ANOVAs’ are the best means to calculate data rather than t-tests because it decreases the chance of increased room for the wrong conclusion because using t-tests requires the accomplishment of several t-tests to accomplish the same goal an Anova could occupy. There are fewer values to calculate by using an ANOVA. The mean values are calculated from a series of replicate observations through an ANOVA. There is less chance variation with an ANOVA. The disadvantage to an ANOVA is that it will not tell us the individual mean of difference from the consensus value and in what direction do they deviate. One would have to run a comparison test such as the Scheffe’s test and plot the data to determine this. One must further ask the correct question to determine the right data is being plotted. This is to prevent any such ambiguities in the experiment at hand so that the conclusions are clear and valid.

One-way ANOVA’s require “fewer measurements to discover significant effects of which the tests are said to have more power than other tests. This is why these tests are used when analyzing data from statistically designed experiments.” (Burke, 1997). A calculated F- value or or p-value is used to indicate the degree of confidence we have that there is a significance difference between the means of the experiment. “Normally a p-value of <0.05 is considered to denote a significant difference.” (Burke, 1997). We assume the data is distributed in a normal ration. Since the data is not of large value it is quite difficult to be distributed away from normal ration. “It has been shown even large variations do not affect the decisions made on the basis of the F-test.” (Burke, 1997). It is postulated that the spread between the variance amongst the groups is homogenous for the most part and if it is not then the data should be plotted. Bartlett’s test is recommended to overcome any such mishap of homogenous.

ANOVA is a powerful tool to test a strong statistical difference between two or more sets of data. One-way ANOVA is most useful when comparing several sets of data. A spreadsheet or statistical software is most useful when using ANOVA. One should always plot his data to ensure the assumptions of ANOVA are not violated in any means.

The best and most advantageous decision making using ANOVA is for sets of items that can be theoretically bound in sets when attempting to replicate data. It is further used when there are several variances and the use of t-sets would not be the best avenue because too many testing parameters would be inefficient causing too many variances hence causing too many possible false conclusions. ANOVA is simply a more scientific means of producing cleaner results with fewer steps along the way because there is less room for mistake through the elimination/minimization of variances.

References

Burke, S. Analysis of Variance RHM Technology Ltd. High Wycombe, Buckimbshire, UK 1997.