- #1

runningman19

- 19

- 3

## Homework Statement

We recently collected data on a reverse osmosis system for our unit ops lab. The report LERF (Laboratory Experiment Request Form) requests that we ascertain a value of A

_{w}, the water permeability coefficient, for our membrane. We need to perform a T-Test on the data, however exactly how this is to be done is unclear to me.

Some more in depth information:

We ran a reverse osmosis system at two different pressures, and two different feed concentrations at each pressure. Data is given to provide some insight on exactly what we are trying to do:

Where P (psig) and Feed Conc (mg/L) are manipulated variables and the rest are measured "response" variables. From this data, we are calculating a value for the water permeability coefficient A

_{w}via a model (given by Equation 1 in the Relevant Equations section).

My questions are these:

**What is a T-Test and how is it performed in this situation? I understand that T-Tests are performed to determine statistical differences between averages, but which averages?**

Is there any other statistical analysis I should be performing on this data?

Is there any other statistical analysis I should be performing on this data?

## Homework Equations

Where J

_{W},ΔP, ΔC

_{S}and Ψ are all known, and A

_{W}is being calculated. ΔC

_{S}is Change in Conc [mg/L], ΔP is pressure drop (psi), which is simply P (psi) in the data given above as the permeate stream leaves at atmospheric, J

_{W}is permeate flux [ft/min], and Ψ is a constant equal to 0.00864.

## The Attempt at a Solution

[/B]

I feel as though the best way to approach this problem is to average the results of each of the measured "response" variables at their respective concentrations and pressures (in this case, we would have 4 averages as we have 3 trials for each concentration and pressure and 12 trials total), perform a T-Test on each of the calculated averages, and then calculate A

_{W}if the averages are statistically significant.

As for other statistical tests, I feel that this may be sufficient but was told to consider an outlier analysis as well. I feel this is not necessary, and in addition I am not sure how to perform an outlier analysis.