I'm doing some work comparing two sets of people: those I invited to an event, and those who actually showed up. I am comparing the amount of money they donated to our charity in the past. I have the amounts bucketed into about five categories (i.e., $100-$199, $200-$299, etc.) and I am showing the percentage of people who fall into each of these categories.

Since my invited set includes about 1,000 people and my actually showed up list is only about 400 people, I want to do some significance testing on the proportions to ensure the differences are statistically significant at the 90% confidence interval.

I used an Excel macro tool I have on hand to perform the two-tailed t-test for proportions assuming equal variances, and the results seemed to make sense (i.e., the percentages I thought would be significantly different at 90% indeed were). However, someone just pointed out to me that neither data set follows the normal distribution.

Does this mean the t-test results are invalid? What test should I be using in its place? I was thinking the Mann-Whitney, but as I was reading about how to conduct it, I don't understand how that test can compare two proportions from two separate groups with different sample sizes.

Advice would be appreciated - thank you!