Instead of using the direct histogram chart, I created a custom histogram:

I used a scatter plot, but removed all markers and lines, then added weight to the Y error bars. I found that this made for a cleaner-looking graph. 

This also required the use of the 'data analysis > historgam' tool.

I have yet to conduct a test for normality here but will update with the results if I do so. That said, the sample size of 96 years of data is still relatively small.

The grey vertical line represents a 0% (neutral) return. 

The green vertical line represents the simple average return from the data set (11.66%). The CAGR is not included in the graph but is calculated to be 9.80%.

This column chart depicts the year-by-year returns of the US market. 

A simple green/red colour coding enhances the ease of interpreting the graph, by showing the years of growth and decline respectively.

For annual returns, I was able to find data extending back to 1928 (Damodaran, NYU). However, for daily return data, I was only able to obtain data extending back to 1963.

Nonetheless, I used the same method as with the distribution of annual returns, to plot the following histogram. 

I have yet to conduct a test for normality here but will update with the results if I do so.

This column chart shows the day-by-day returns of the US market since 1963.

Notably, comparing this chart to the earlier 'year-by-year' column chart, we would notice that the odds of having a negative day are far higher than having a negative year.

And in general, the longer the time horizon, the lower the odds of losing money during that period. Highlighting the importance of long-term investing.