Testing Statistical Significance Essay

1217 Words Nov 30th, 2011 5 Pages
Testing statistical significance is an excellent way to identify probably relevance between a total data set mean/sigma and a smaller sample data set mean/sigma, otherwise known as a population mean/sigma and sample data set mean/sigma. This classification of testing is also very useful in proving probable relevance between data samples. Although testing statistical significance is not a 100% fool proof, if testing to the 95% probability on two data sets the statistical probability is .25% chance that the results of the two samplings was due to chance. When testing at this level of probability and with a data set size that is big enough, a level of certainty can be created to help determine if further investigation is warranted. The …show more content…
The sigma was calculated to be 2.295 for group X and 2.563 for group Y. Plugging these numbers into the following calculation results in t. This number is then taken with the total datum size minus one to the t table. But, let’s not get to far ahead of the calculation:

[pic] As you can see the results of the calculation is 0.719267, taking this number and the total number of datum in the two samples. Since these are sample sets, the total size of the combined data minus one is used on the t chart to find a range from zero to x. And if the formula produces a number that is above the listed range, there is a 95% probability that the numbers are statistically different. If the number produced is above the range then Sam’s hypothesis would be supported, if not Sam would have a couple of choices. In this case, there were 16 datum, taking into account that these are sample sets, we minus one to produce 15. The range for 15 on the t chart is from zero to 2.145 and there is not enough data to support Sam’s theory. If Sam has significantly more funding to conduct his research he can create larger sized data samples. This would bring stronger results especially since the sample Y had a larger sigma and needed a larger sample to retain validity. Regardless of the size of the samples, I do not think that Sam has a chance to prove his hypothesis without lowering the level of

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