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Why it is said that number of theoretical plates should be high for a good efficiency?
Wiki User
∙ 15y ago
In liquid chromatography the 'theoretical plates' number is a measure of the resolution between the peaks of different eluting substances. The higher the plate value the greater the separation. This is particular important as the load reaches the maximum the column is designed for.
Wiki User
∙ 15y ago
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What is a column plate number?
It is the efficiency of the column. The larger the number, the more theoretical plates the column possesses; a typical well-packed column with a 5-micrometer particle size porous packing in a 15cm x 46 mm column should provide10,000-20,000 plates. sorry. I forgot to put a point in there. It should be 4.5 mm, not 45
What are the si units for efficiency?
Efficiency is adimensional, meaning there is no associated unit, just a number - and the number should be the same in different measurement systems. Efficiency can be any number between 1 (equivalent to 100%) and 0 (equivalent to 0%).
What is theoretical proablity?
Theoretical probability- what the probability "should be" if all outcomes are equally likely.
How does one determine efficiency?
One way to determine efficiency is to compare the results with similar cases: * How efficient a person is compared to other people doing similar work * How efficient a process is compared to similar processes Another way is to determine what the minimum steps are required and how long each step should take. Then compare the actual results with the theoretical results.
What does a negative percent of the difference mean between experimental and theoretical probabilities of a given event?
First, it is important to note that it is very unlikely that the experimental and theoretical probabilities will agree exactly. As an extreme example, if you toss a coin an odd number of times, the resulting experimental probability cannot possibly be exactly 1/2. It should be easy to see that this remains true even if the coin is tossed googleplex+1 number of times.A negative difference could be because the number of trials was too small and, with an increased number of trials, the experimental probability would gradually increase towards the theoretical probability.It is also possible that the theoretical model is wrong. You may have assumed that the coin that was being tossed was fair when it was not. Or there were some factors that you failed to take full account of in your theoretical model.Or, of course, it could be a mixture of both.First, it is important to note that it is very unlikely that the experimental and theoretical probabilities will agree exactly. As an extreme example, if you toss a coin an odd number of times, the resulting experimental probability cannot possibly be exactly 1/2. It should be easy to see that this remains true even if the coin is tossed googleplex+1 number of times.A negative difference could be because the number of trials was too small and, with an increased number of trials, the experimental probability would gradually increase towards the theoretical probability.It is also possible that the theoretical model is wrong. You may have assumed that the coin that was being tossed was fair when it was not. Or there were some factors that you failed to take full account of in your theoretical model.Or, of course, it could be a mixture of both.First, it is important to note that it is very unlikely that the experimental and theoretical probabilities will agree exactly. As an extreme example, if you toss a coin an odd number of times, the resulting experimental probability cannot possibly be exactly 1/2. It should be easy to see that this remains true even if the coin is tossed googleplex+1 number of times.A negative difference could be because the number of trials was too small and, with an increased number of trials, the experimental probability would gradually increase towards the theoretical probability.It is also possible that the theoretical model is wrong. You may have assumed that the coin that was being tossed was fair when it was not. Or there were some factors that you failed to take full account of in your theoretical model.Or, of course, it could be a mixture of both.First, it is important to note that it is very unlikely that the experimental and theoretical probabilities will agree exactly. As an extreme example, if you toss a coin an odd number of times, the resulting experimental probability cannot possibly be exactly 1/2. It should be easy to see that this remains true even if the coin is tossed googleplex+1 number of times.A negative difference could be because the number of trials was too small and, with an increased number of trials, the experimental probability would gradually increase towards the theoretical probability.It is also possible that the theoretical model is wrong. You may have assumed that the coin that was being tossed was fair when it was not. Or there were some factors that you failed to take full account of in your theoretical model.Or, of course, it could be a mixture of both.
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3 and 7
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