I have a set of data for the level of antioxidants in tea, with two variables (water temperature of either 70 or 90 degrees, and steeping time of either 2, 3 or 4 minutes). There are 4 replications each of 6 treatment combinations.

I did a trend comparison in SAS, and I got the table below:

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Contrast .....................DF.....Contrast SS.....Mean Square.....F Value.....Pr > F

Temp............................1.....0.39526667.....0.39526667.......19.70.....0.0003

Steep linear ..................1.....1.14490000.....1.14490000.......57.06.....<.0001

Steep quadratic..............1.....0.08167500.....0.08167500.......4.07.....0.0588

Temp * Steep linear........1.....0.00302500.....0.00302500.......0.15.....0.7024

Temp * Steep quadratic...1.....0.10083333.....0.10083333.......5.03.....0.0378

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So I know this is telling me that there is a significant response in temperature (because the p value is .0003) and there is a significant linear response in steeping (p value <.0001) but not in the quadratic response (p value .0588). It looks like there is a significant interaction between temperature and steep quadratic, but not temperature and steep linear.

I think I'm reading it correctly (I THINK), and I can tell you all of the above, but I don't know what it all means! I'm struggling to understand it. What does it mean to say that there is a significant linear response, or a significant quadratic response? I know we are somehow comparing the treatments, to see what changes happen during each treatment, and if it's significant. But I don't know the difference between linear and quadratic (and cubic and quartic, for that matter).

I greatly appreciate any enlightenment you can give me, so that when I run this stuff in SAS, I actually understand what I'm doing! If you need more information than what I gave above, let me know.

Thank you!

Jungle Rat