We analyzed the distribution of radon concentration levels using a histogram. Here's what we learned:

This visualization helps in identifying patterns or outliers in radon concentration levels, contributing to a better understanding of the data's characteristics.

We attempted to test the null hypothesis stating that there is a statistical difference between the radon concentrations in different offices by performing a one-way ANOVA test. However, the test resulted in NaN values for both the test statistic and the p-value, indicating an issue with the data or the test execution.

This outcome suggests that the data might not be suitable for the ANOVA test as performed, possibly due to missing values, non-numeric data, or insufficient data points per group. Further investigation and data preprocessing might be necessary to correctly perform the hypothesis test.