Multinominal Discrete probablity models question

#1
In an email, 4 features are extracted. Let n=10 data are observed from this email.
  • What is your proposed model of data? (Hint: you are allowed to choose freely parameters of the model so that the conditions of the proposed model met.)
  • What is the probability that we observe 2, 1, 4, 3 data respectively from feature one to five?
  • What is the probability that we observe at least 4 data from the last feature?
  • Compute the correlation between the first and second features?
  • Generate 1000 samples from your proposed model in part (a).
  • Find the sample correlation between the first and the second features.
  • Compare the sample and model correlation between these two features.
 
#2
In an email, 4 features are extracted. Let n=10 data are observed from this email.
  • What is your proposed model of data? (Hint: you are allowed to choose freely parameters of the model so that the conditions of the proposed model met.)
  • What is the probability that we observe 2, 1, 4, 3 data respectively from feature one to five?
  • What is the probability that we observe at least 4 data from the last feature?
  • Compute the correlation between the first and second features?
  • Generate 1000 samples from your proposed model in part (a).
  • Find the sample correlation between the first and the second features.
  • Compare the sample and model correlation between these two features.
I have the exact same question for an assessment and I don't understand what is being asked nevermind how to answer. The class has repeatedly asked the lecturer to explain but it still isn't making any sense Can anyone help?
 
#5
I suspect the solution. it is not that simple.
1 - how the probability of getting feature 1 is 0.1 and getting feature 4 is 0.4? As feature 1 to 4 all has to be nominees not numbers.
2 - If your proposed solution is right for part a, the n how will you use it to answer rest of the other parts?