Respuesta :
Randomly selected statistics which has been randomly selected for sampling are referred to as a random sample.
When a researcher chooses a sampling that is not representative of the entire population, a statistical mistake is produced.
Given this, it should be clear that a sampling mistake would prevent a data collection's mean & standard deviation from accurately reflecting the set of data.
The total of the numbers is the mean. To obtain a weighted mean for the variables we are modifying, we take use of it. We figure it out by adding up all the figures and then dividing the result by the total amount of figures.
The formula we use is: ∑ (Given data ÷ total data)
The variance and dispersion of the data we have are measured by the standard deviation. A little departure suggests that our data is spread, but a large divergence suggests that the data is very dispersed.
The format we use is: √((x - mean)² ÷ (number of data - 1))
Learn more about the sampling error at
https://brainly.com/question/27959474?referrer=searchResults
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