Below is the horseshoe crab data. We fit a Poisson regression model to the data. The outcome is the number of satellites of the female crab. The single predictor is weight (in Kg) of the female crab: poisson satellite weight_kg Poisson regression Number of obs = 173 LR chi2(1) = 71.93 Prob > chi2 = 0.0000 Log likelihood = -458.08205 Pseudo R2 = 0.0728 ------------------------------------------------------------------------------ satellite | Coefficient Std. err. z P>|z| [95% conf. interval] ------------- ---------------------------------------------------------------- weight_kg | .5893041 .0650171 9.06 0.000 .4618729 .7167354 _cons | -.4284054 .1789353 -2.39 0.017 -.7791121 -.0776987 ------------------------------------------------------------------------------ a.) Write out the model that was fit here. b.) Is there an effect of weight in Kg on the number of satellites? If so, describe the effect. c.) What alternative model is customary to also fit to count data, in addition to Poisson regression? No justification is needed