Date Western Magnitude Estimate Soviet Reported Yield (KTons) 21-11-65 5.6 29 13-02-66 6.1 125 20-03-66 6.0 100 07-05-66 4.8 4 22-09-67 5.2 10 29-09-68 5.8 60 23-07-69 5.4 10 30-11-69 6.0 125 28-12-69 5.7 40 20-04-71 5.9 90 06-06-71 5.5 16 09-10-71 5.3 12 21-10-71 5.5 23 10-02-72 5.4 16 20-03-72 5.1 6 16-08-72 5.0 8 02-09-72 4.9 2 02-11-72 6.1 165 10-12-72 6.0 140

PYTHON, please

Problem 3 In 1989, Soviet scientists released data for nuclear weapons tests. Western scientists had previously estimated the size of the explosions using seismic data. (*Aside: Seismic data is measured on the Richter scale - it is used for earthquakes. The Richter magnitude of an earthquake is determined from the logarithm of the amplitude of waves recorded by seismographs. Because of the logarithmic basis of the scale, each whole number increase in magnitude represents a tenfold increase in measured amplitude; in terms of energy, each whole number increase corresponds to an increase of about 31.6 times the amount of energy released, and each increase of 0.2 corresponds to approximately a doubling of the energy released. (wiki: Richter_magnitude_scale) - This may help explain the model you obtain). The data is available in sovietNuclearExplosion.dat the columns are: date, Western magnitude est., Soviet Reported yield (Kilotons). Make a scatter plot and simple linear regression fit for est. magnitude (Y)v/s yield (x). Make a plot of the residuals ei=(yiy^i)v/syi. Do you see any pattern in these curves? [ ] : For this problem, transform the independant variable: x (according to the ladder of transformations). Make a scatter plot of the data in each step. Pick a suitable transformation and obtain the model for the nuclear test magnitude on the (transfiormed) yield. This is a way to obtain a model for the data using linear regression