Suppose that Coke and Pepsi are fighting for the cola market. Each week each person in the market buys one case of Coke or Pepsi. If the person's last purchase was Coke, there is a 0.90 probability that this person's next purchase will be Coke; otherwise, it will be Pepsi. (You can assume that there are only two brands in the market.) Similarly, if the person's last purchase was Pepsi, there is a 0.80 probability that this person's next purchase will be Pepsi; otherwise, it will be Coke. Currently half of all people purchase Coke, and the other half purchase Pepsi. Simulate one year (52 weeks) of sales in the cola market and estimate each company's average weekly market share and each company's ending market share in week 52. Do this by assuming that the total market size is fixed at 100,000 customers. (Hint: Use the RISKBINOMIAL function. However, if your model requires more RISKBINOMIAL functions than the number allowed in the academic version of @RISK, remember that you can instead use the CRITBINOM function to generate binomially distributed random numbers. This takes the form =CRITBINOM(ntrials, psuccess,RAND()).)