For a wine titration my results obtained were...

0.6402%, 0.5814%,& 0.6006%
the I calculated was 0.04936
according to my text sometimes the # is expressed in ppt or 100%
first which would be correct if asked to submit a RSD for the results of a lab like this and 2nd what would be the significance of this # be?
Even though I know from the text that it says that it measures the preciseness of the values, I don't exactly know what the significance of say my RSD for my result (0.04936) means when describing the preciseness of my results as that isn't described in the book.

The standard deviation is 0.02998. The mean is 0.6074. The relative standard deviation is 0.02998/0.6074 = 0.04936 as you calculated above. That is 4.936% (parts per hundred) or 49.36 parts per thousand. So any of the three [0.04936 (which is parts per one), 4.936% OR 49.36 ppt] would be correct if how it is to be expressed is not listed. My opinion is that the precision you report is not that good. You can judge how good by looking at the example in your text where standard deviation and relative standard deviation are discussed. In my 6th edition, five numbers are reported as 0.752, 0.756, 0.752, 0.751, 0.760. The s.d. is 0.00377 and the mean is 0.7542. Thus RSD is 0.00377/0.7542 = 0.00500 which is 0.5% or 5 ppt (which I consider rather good (but not GREAT) precision and the precison you quote, on the same scale is about 10 times poorer. Note in the five numbers that the variation, for the most part, is in the 3rd place while your deviations are in the second place.

AWW...I have to make a lab report on this..great..(I think it was the color problem again b/c I couldn't decide which brown was "brown" for the wine endpoint)..but what value of a RSD would be good? since you said the other one from the bk is good but not there a # that I should be aiming for when doing the calculations?

2 ppt is really quite good. However, your lab may be a "finish the experiment with acceptable results--whatever acceptable is" or graded in relative error from the accepted value.

It's not really that much of my grade b/c my prof said that it was only worth 5 points so I guess I'll have to type error as a factor in the results.
But since I have to write a abstract for my paper I was wondering if it was better to write it at the beginning or the end of the lab report.

If I was to eliminate 1 value as an outlier would I go and include that in calculations of the RSD? I would assume not since It would affect the RSD
And how would I decide on a confidence level for the Q test? How would I know if it was 90/95/or 99% conficence? It's not explained how would you choose

When writing an abstract for your lab report, it is generally recommended to write it at the beginning of your report. The abstract provides a concise summary of your entire experiment and its results, allowing readers to quickly get an overview of your study. It is usually written after the experiment is completed, but before the rest of the report is written.

If you have identified an outlier in your data, it is generally not included in the calculations for the RSD (relative standard deviation). Outliers can significantly affect the calculated variability and may not represent the true precision of your results. Therefore, it is common practice to exclude outliers when calculating the RSD.

The choice of confidence level for the Q test depends on the desired level of certainty. A higher confidence level indicates a greater level of certainty in the results. Commonly used confidence levels are 90%, 95%, and 99%. To choose the appropriate confidence level, you need to consider the importance and consequences of making a type I error (false positive) or a type II error (false negative).

For example, if the consequences of accepting an outlier as valid data are serious, you may want to choose a higher confidence level, such as 99%. On the other hand, if the consequences of excluding valid data are minimal, a lower confidence level, such as 90%, may be more appropriate. The choice of confidence level ultimately depends on the specific context and requirements of your experiment.