Data 1. Clearly do it with nice handwriting you can useexcel
| Day | Speed (m/s) | Power (kW) |
| 1 | 5 | 0.25 |
| 2 | 6 | 0.38 |
| 3 | 5 | 0.25 |
| 4 | 5 | 0.25 |
| 5 | 3 | 0.08 |
| 6 | 4 | 0.14 |
| 7 | 3 | 0.08 |
| 8 | 6 | 0.38 |
| 9 | 5 | 0.25 |
| 10 | 6 | 0.38 |
| 11 | 6 | 0.38 |
| 12 | 4 | 0.14 |
| 13 | 3 | 0.08 |
| 14 | 3 | 0.08 |
| 15 | 5 | 0.25 |
| 16 | 4 | 0.14 |
| 17 | 3 | 0.08 |
| 18 | 8 | 0.64 |
| 19 | 6 | 0.38 |
| 20 | 4 | 0.14 |
| 21 | 3 | 0.08 |
| 22 | 6 | 0.38 |
| 23 | 5 | 0.25 |
| 24 | 4 | 0.14 |
| 25 | 4 | 0.14 |
| 26 | 2 | 0.04 |
| 27 | 5 | 0.25 |
| 28 | 6 | 0.38 |
| 29 | 3 | 0.08 |
| 30 | 3 | 0.08 |
| 31 | 10 | 0.97 |
Q.1 Why is it “clearly not” Poisson? (a) Calculate summarystatistics for Data1 and use them to argue that the distribution isnot a Poisson distribution. (b) Use the method of moments toestimate what the parameter of a Poisson distribution would be togive you those values. (c) Collate how many values there are in therange 0-4, 5-9, 10-14, etc. and plot the resulting histogram. (d)Use the Chi-square test to determine whether the data fit a Poissondistribution. Find a better distribution for Data1: (f)Show your reasoning for which distribution you choose, andremember, you may need to compare several distributions. (g) Giveall measures of fit you use, including at least the Chi-squaremeasure of fit, calculated as you did in the question above. Youare encouraged to use other measures also.
