Final answer:
The query is a math issue related to probability and the Poisson distribution, needing specific data about Kim's email habits to answer directly. Instead, the provided information suggests a need to understand Poisson distributions and how to calculate probabilities of email-related events.
Step-by-step explanation:
The question you've asked about the ratio of e-mails Kim received to the mails she answered is fundamentally a Mathematics problem concerning ratios and probabilities. Unfortunately, the information you've provided is not directly related to Kim's email activities but instead describes different statistical email scenarios and their probabilities. To accurately provide the ratio of emails received to emails answered, specific data about the emails Kim receives and answers would be necessary.
However, from the context of the information provided, it seems that your question may actually be related to understanding Poisson distributions, as the email features an example regarding the average number of emails received daily by a user and a case of the discrete random variable X. Let's tackle this from a mathematical standpoint. The Poisson distribution helps to predict the probability of a certain number of events happening within a fixed interval.
For instance, to find out the probability that an email user receives exactly 160 emails per day when the average number of emails received is 147, you use the Poisson probability formula, usually involving factorial calculations and the exponential constant e. The computations can be complex and typically rely on the use of statistical tools or software. Similarly, to determine the probability of receiving emails within a given time frame or the number of households that have never sent an email, Poisson distribution or binomial distribution could be employed, respectively.