Feedback on the data analysis: I find the 90% confidence interval to not be very informative in some situations. For example in the case of “Computing the ratio of money raised to time spent, we arrive at an average of 786 USD per hour (CI 7 USD to 3,100 USD)”, the CI range is very broad and I only really take away ‘there was high variance in the data’ or ‘there weren’t many data points’ or both. In this situation, it’s both and it’s relatively clear to see from the figures.
I’m unsure what would be more informative. Maybe a box plot of the direct work hourly rate and your hourly rate calculations could be a good way to visualise the uncertainty. A statistical test to compare the means of the two distributions (direct work and fundraising) could also be interesting but maybe there’s too much variance and too few data points in the fundraising data for now.
It would also be interesting to see the maximum and minimum money raised per hour of time values.
Regardless, it’s a great result and I look forward to hearing how the 2022 season goes!
Hi Sean, thanks for your comment and your feedback. I think you are correct on both accounts, more data would definitely increase our confidence in the results even further and the distribution has a high variance due to its heavy tailed nature (which is not uncommon when looking at donations data). Good idea also on doing statistical tests to compare distributions.
That’s a fantastic outcome, congratulations!
Feedback on the data analysis: I find the 90% confidence interval to not be very informative in some situations. For example in the case of “Computing the ratio of money raised to time spent, we arrive at an average of 786 USD per hour (CI 7 USD to 3,100 USD)”, the CI range is very broad and I only really take away ‘there was high variance in the data’ or ‘there weren’t many data points’ or both. In this situation, it’s both and it’s relatively clear to see from the figures.
I’m unsure what would be more informative. Maybe a box plot of the direct work hourly rate and your hourly rate calculations could be a good way to visualise the uncertainty. A statistical test to compare the means of the two distributions (direct work and fundraising) could also be interesting but maybe there’s too much variance and too few data points in the fundraising data for now.
It would also be interesting to see the maximum and minimum money raised per hour of time values.
Regardless, it’s a great result and I look forward to hearing how the 2022 season goes!
Hi Sean, thanks for your comment and your feedback. I think you are correct on both accounts, more data would definitely increase our confidence in the results even further and the distribution has a high variance due to its heavy tailed nature (which is not uncommon when looking at donations data). Good idea also on doing statistical tests to compare distributions.