Analysis: (a) Automatically determine the average "benchmark" score for each \"category\" by year, for years 2010-2021 (b) Automatically determine the average '1 DP (WT score for each "category" by year, for years 2010-2021 (c) Divide the columns for (a) and (b) to yield a column which represents benchmark score per watt Present the data for parts (a). (b) and (c) in a single table. For example. something like this would be ne: Year Desktop Laptop Server Benchmark TDP BIT Benchmark TDP BJ'T Benchmark TDP 82 T 2011 2225.1 69.3 32.8 1330.8 28.0 42 4260.2 89.4 48 2012 2944.6 20.3 41.9 2128.8 31.1 68 5323.2 92.1 58 2013 3419.1 59.1 49.5 1952.8 24.6 29 6248.5 98.3 64 2014 2991.9 53.5 55.9 1995.2 21.5 93 2326.9 93.2 29 2015 3229.8 52.4 55.8 2501.5 19.8 122 8050.4 82.8 92 2016 4161.6 63. 2 55.3 2463.3 12.5 141 11 325.8 105.1 108 2012 8209.5 24.1 112.5 3114.3 18.8 166 12835.2 92.6 131 2018 11118.8 82.6 134.6 4539.4 26.6 120 11828.0 91.2 130 2019 14563.8 29.2 182.2 6363.6 25.2 252 19640.1 112.9 124 2020 1 6989.1 82.4 206.1 9080.4 22.9 396 24159.2 133.1 182 2021 1 6324.6 25.1 218.0 13834.5 30.9 448 32909.2 154.5 245 it doesn't have to be formatted exactly like that -- you are welcome to format things however you like, so long as they look professional and readable. (d) Using the data from parts {a} through (c) and whatever method you think seems appropriate. come up with an estimate for what the average "benchmark" score would be in the server category in the year 2025. This estimate should automatically update if more raw data is imported (Le. don't pull the equation from a trendline on your chart from part (en