How would you perform a signifiance test?

Question

I have collected data and environmental data to use.

Answer 1

Use the computer program SPSS. You can download a free trial version at their website: http://www.spss.com/

Depending on the type of data you have, you could do a T-test or an ANOVA. Your significance will be measured by "p". If p is less than 0.05, your data are significant.

Answer 2

It very much depends on your experimental design. First off, how many statistical groups have you emasured? Then, how big are your groups (what's the N of your groups). Are your groups normally distributed (so that you can use a parametric test) or not (in which case you'd have to use a non-parametric test). Also, what is your nullhypothesis?

In other words, based on your question with no further information avaliable, one cannot really say how you would determine significances. Your main problem will be that you actually should have thought about the statistics before you collected any data. it's an essential part of your experimental design...

I would suggest the following: Check with either a statistician at your university or check a good book on statistics (a good one is Sokal and Rahlf - a classic in the biological sciences). Also, if you could tell us more about your experimental design, people could possibly help you more...

Answer 3

A significance test is performed to determine if an observed value of a statistic differs enough from a hypothesized value of a parameter to draw the inference that the hypothesized value of the parameter is not the true value. The hypothesized value of the parameter is called the "null hypothesis." A significance test consists of calculating the probability of obtaining a statistic as different or more different from the null hypothesis (given that the null hypothesis is correct) than the statistic obtained in the sample. If this probability is sufficiently low, then the difference between the parameter and the statistic is said to be "statistically significant."

Just how low is sufficiently low? The choice is somewhat arbitrary but by convention levels of .05 and .01 are most commonly used.

For instance, an experimenter may hypothesize that the size of a food reward does not affect the speed a rat runs down an alley. One group of rats receives a large reward and another receives a small reward for running the alley. Suppose the mean running time for the large reward were 1.5 seconds and the mean running time for the small reward were 2.1 seconds.

The difference between means is thus 2.1 - 1.5 = .6 seconds. The test of whether this difference is significant consists of determining the probability of obtaining a difference as large or larger than .6 seconds given there is really no effect of magnitude of reward. If the probability is low (below the significance level) then the null hypothesis that magnitude of reward makes no difference is rejected in favor of the alternate hypothesis that it does make a difference. The null hypothesis is not accepted just because it is not rejected.

Answer 4

Short of using a statistic program, Microsoft Excel offers quite a few statistical analysis functions.

Answer 5

Enter it into a database that has significance calculators...like SPSS