financial energy technology 0 5.5 5.2 7.3 1 7.1 7.4 8.2 2 6.9 6.6 7.1 3 5.1 5.7 7.6 4 4.6 5.6 8.2 5 5.3 5.5 11.5 6 5.9 6.4 9.2 7 5.6 6.1 9.5 8 5.5 5.2 7.3 9 7.1 7.4 8.2 10 6.9 6.6 7.1 11 5.1 5.7 7.6 12 4.6 5.6 8.2 13 5.3 5.5 11.5 14 5.9 6.4 9.2 15 5.6 6.1 9.5 16 4.7 4.4 6.2 17 6.4 6.6 7.4 18 6.7 6.4 6.9 19 4.3 4.8 6.4 20 4.1 5.0 7.4 21 5.1 5.3 11.1 22 5.7 6.2 8.9 23 4.7 5.2 8.1 24 5.3 5.0 7.1 25 6.4 6.6 7.4 26 5.8 5.6 6.0 27 4.9 5.5 7.4 28 4.1 5.0 7.4 29 4.8 4.9 10.3 

test statistic = 55.07 test statistic = 0.0 

1. Define the null and alternative hypothesis in mathematical terms and in words.
2. Report the level of significance.
3. Include the test statistic and the P-value. See Step 2 in the Python script.
4. Provide your conclusion and interpretation of the test. Should the null hypothesis be rejected? Why or why not?
5. Does a side-by-side boxplot of the 10-year returns of ETFs from the three sectors confirm your conclusion of the hypothesis test? Why or why not? See Step 3 in the Python script.