# Suggest method of analysis

#### Sunil Neelam

##### New Member
Hi,

i have two sets of data one control and the other treated. Pl. suggest a best method/s of analysis to effectively study the treatment effects.
Thanks

#### Silvanus

##### New Member
Hi Sunil,

What can you tell from inspecting the data?

Where are the mid points (median or mean) in each sample and how spread out is the data (IQR or st. dev)? What is your sample size? What are you testing: within-subjects treatment effects (in which case your treatment and control wont be independent), or between (in which case your treatment & control should be independent)?

#### Sunil Neelam

##### New Member
Hi,

The sample size is 20 and the analysis is to study within-subjects treatment effects. the data is quite spread out with good St. Dev. Can u pl suggest most appropriate method.

Thanks

#### Silvanus

##### New Member
Ok, you could use a paired t-test providing the data are normally distributed (or close to it).

First, test for normality. If you have a stats program that does Anderson-Darling, Ryan-Joiner, or Kolmogorov-Smirnov tests, this is a good way of testing it. Otherwise, you could construct a quantile plot in Excel and visually judge how close the point fall to a 45 degree angle (to do this, complete as below then make a scatter plot with Col A on the x-axis and Col B on the y-axis):

Column A Column B
(i-0.5)/n variables in order from lowest to highest

=(1-0.5)/20 Variable 1 (lowest)
=(2-0.5)/20 Variable 2
=(3-0.5)/20 Variable 3
....
=(20-0.5)/20 Variable 20

If you data appear to be sloping upward by 45 degrees in roughly a straight line then you should be ok to use a paired t-test. If not, then you might have to use a non-parametic equivalent like a Wilcoxon paired signed rank test or a paired sign test.

Make sure you set up your hypotheses correctly too, because this will affect the p-value. So, if you are testing whether Control is not equal to Treatment, then this becomes a two-tailed test. If you are testing if Control > (or<) Treatment, then this becomes a one-tailed test.

#### Sunil Neelam

##### New Member
Thanks Silvanus,

Let me be more elaborate.

The experiment is to study the effect of elevated co2 on the performance of 20 different plant germplasm lines.

One set under controlled conditions and the other under treatment (i.e elevated co2)

data such as plant ht, leaf area, leaf dry weight etc about ten such parameters were recorded. Can we do the analysis with the paired t test ? please clarify considering the data follows normal distribution.