Answer to Question 1
Random error is caused by any factors that randomly affect measurement of the variable across the sample. For instance, people's moods can inflate or deflate their performance on any occasion. In a particular testing, some children may be in a good mood and others may be depressed. If mood affects the children's performance on the measure, it might artificially inflate the observed scores for some children and artificially deflate them for others.
The important thing about random error is that it does not have any consistent effects across the entire sample. Instead, it pushes observed scores up or down randomly. This means that if you could see all the random errors in a distribution they would have to sum to 0random errors tend to balance out on average. There would be as many negative errors as positive ones. (Of course you can't see the random errors because all you see is the observed score X). The important property of random error is that it adds variability to the data but does not affect average performance for the group. Because of this, random error is sometimes considered noise.
Answer to Question 2
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