You are a data analyst working for a retail store chain working with loss prevention, and there's been a recent uptick in shoplifting incidents. You suspect that the times these incidents occur might follow a certain pattern. Your goal is to use the normal distribution to uncover these patterns and help the store management take preventive measures.

Here are some fun questions to get our discussion started:

Peak Hours: If shoplifting incidents follow a normal distribution around certain peak hours of the day, with the mean incident time being $3$:$00$ PM and a standard deviation of $1$ hour, what might this tell us about the distribution of shoplifting incidents? How would you describe the time window during which most incidents occur? Specifically, explain how the $68-95-99\mathrm{.}7$ rule applies to this scenario $($e$.$g$.,68\%$ of incidents occur within one standard deviation, $95\%$ within two, and $99\mathrm{.}7\%$ within three$).$