I think that the terminologies are confused. Computing and predicted values are one and the same. Actually, you will get two values, experimental and predicted values. They are used to calculate weight.

hi selvaraju, in that experimental and predicted value.which one i should choose as a final answer. experimental or predicted?

Obviously experimental value because predicted value is hypothetical.

Your target should not be just reporting the value, The conclusion is about if the objective achieved, such as if the experimental group is better than control group, you may need report the average scores and standard deviation of each group.

If you want make a prediction, you probably need report the predicted value, the experimental value may not exist.

Vinod -

I am not clear on your context here, but in regression, the points on the regression line or curve are the predicted values, say y*, and the observed values are y. I factor the residuals into a random factor, and a nonrandom factor based on the regression weight, the product of which we will call e, such that we have yi = y*i + ei . 

So the answer to your question depends upon your goal. If you are looking for an observed value, you take that which was observed. But perhaps you are more interested in the model?

I do not know if what you refer to by 'experiment' is a single observation, or a set of observations from which you estimate/'calculate' one aggregate observation, and whether the predictions are from one model or different ones, the details of which might be important, but it would seem that regardless, the answer to your question depends upon whether you want to know what was observed/calculated, or modeled. If you are looking to future use, the models may be more important. Regardless, you should also consider estimating the variance of the prediction error.

Cheers - Jim