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Can one correct for bias by using a large sample?
Large samples can be just as biased as small samples, depending upon how they are selected. For example, you want to do a survey to see how popular the President is, but you only interview men, refusing to interview women. No matter how many men you interview, this bias still exists. A sample of a million men is still biased if you have excluded women. (Although the data are still significant as long as you recognize that the bias exists.)
What is the difference between reagent blank and sample blank?
Reagent Blank : Take reagent and add deionised water (in place of sample to be tested). Now measure the OD at specific wavelength --> this OD is your reagent blank. Substract this OD from your test result (with sample) to avoid any false +ve effect due to colour of reagents itself.Sample Blank : Take sample and measure the OD without adding reagents --> this OD is your sample blank. Substract this OD from your test result to avoid any false +ve effect due to colour and turbidity of sample itself. As it is the fact that colour and turbidity of each sample would vary from one to another.So now it is clear that Reagent blank is used to avoid bias due to colour of reagents and Sample blank is used to avoid bias due to sample itself.
What is the difference between sample and sample size?
a sample is a sample sized piece given... a sample size is the amount given in one sample
What is represenatative sample of population?
A representative sample is one where the statistics of the sample are the same as the statistics for the parent population.
Would one expect more variance with a larger sample size in a chi distribution?
The larger your sample size, the less variance there will be. For instance, your information is going to be much more substantial if you took 1000 samples over 10 samples.
