Homework: Chi Square testing in R

I made a table of Trust and Donation results as shown below:

The way to interpret the table is that there are only 5 options for Trust and Donation. There are 93 data entries where someone picked 0 for both trust and donation, 12 where someone picked 1 for trust and 0 for donation, etc. Notice how many of the cells in the table have small values or 0's. I then took a Chi Squared test of the table. Below are the results:

To interpret these results, we will pick an acceptable p-value. A typical p-value is 0.05. If the calculated p-value is less that 0.05, we will reject the null hypothesis. In other words, we would would conclude that there is a statistical correlation between the way people played "Trust" and "Donation". If the calculated p-value is greater than 0.05, we would fail to reject the null, meaning that there is not enough evidence to show that there is a significant difference. In this case, the p-value is much smaller than 0.05, meaning that there is a significant correlation between the two variables. However, these results should not be trusted because too many of the cells in the table had  draw meaningful conclusions since Pearson's Chi Squared test assumes the sample size is large. Since the test size is small, it would be better to use Fisher's exact test or another statistical process that would account for results where most cell values are small.