MHB What is the relationship between Z-scores and probability?

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The discussion explores the relationship between Z-scores and probability within a normally distributed dataset, specifically in the context of accident distances from home. It highlights that 99% of individuals are within a certain distance, with a mean of 30 kilometers and a standard deviation of 8 kilometers. The conversation emphasizes the importance of eliminating the extreme lower and upper 0.5% of data to focus on the central distribution. It references the empirical rule, noting that one standard deviation from the mean encompasses approximately 68% of the data. Understanding these concepts is crucial for interpreting Z-scores and their associated probabilities effectively.
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On average, 99% of the people were between ___ and ___kilometers away from their home when they got
into an accident
the mean is 30 with a standard deviation of 8
 
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Hello and welcome to MHB! :D

Did you mean to use the [SOLVED] prefix for your thread? When you use this, people assume you don't need help.

So, given the symmetry of normally distributed data about the mean, we know we want to eliminate the lower and upper 0.5% of the data.

So, what area do we want associated from the mean to the upper limit?
 
Another way of thinking about what Mark is suggesting is to remember the rule for going 1,2 and 3 standard deviations away from the mean in both directions. 1 SD both ways covers about 68%, 2 covers ______ and 3 covers _______. Have you seen this before?
 
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