Modeling and Simulation - naughty or nice: Difference between revisions
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== What is this problem set trying to do == | == What is this problem set trying to do == | ||
To exercise your thinking about modeling and simulation. | To exercise your thinking about modeling and simulation. This problem set also raises interesting questions about right, wrong, good, bad, "degree of goodness" and "degree of badness". It's '''absolutely fascinating'''. There is a thought amongst some students this specific issue cannot be modeled. | ||
== The Problem == | == The Problem == | ||
As you think about modeling and simulation, you should build two different models which mathematically represent what factors should contribute to being "bad" or "good". Remember, a model | As you think about modeling and simulation, you should build two different models which mathematically represent what factors should contribute to being "bad" or "good". Remember, if you have a model you can answer YES to the following questions: | ||
# I have identified important features of whatever events I hope to represent. | # I have identified important features of whatever events I hope to represent. | ||
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# I have adjusted for how likely each factor is. | # I have adjusted for how likely each factor is. | ||
Once you have developed a model, please build a simulation for it. We are primarily concerned with the probability of being categorized as "naughty" or "nice". We are also concerned with "how much is any one person "naughty or nice". | Once you have developed a model, please build a simulation for it. We are primarily concerned with the probability of being categorized as "naughty" or "nice". We are also concerned with "how much is any one person "naughty or nice". | ||
== How you will be assessed == | == How you will be assessed == |
Latest revision as of 11:50, 13 February 2019
This is a problem set. Some of these are easy, others are far more difficult. The purpose of these problems sets are:
- to build your skill applying computational thinking to a problem
- to assess your knowledge and skills of different programming practices
What is this problem set trying to do[edit]
To exercise your thinking about modeling and simulation. This problem set also raises interesting questions about right, wrong, good, bad, "degree of goodness" and "degree of badness". It's absolutely fascinating. There is a thought amongst some students this specific issue cannot be modeled.
The Problem[edit]
As you think about modeling and simulation, you should build two different models which mathematically represent what factors should contribute to being "bad" or "good". Remember, if you have a model you can answer YES to the following questions:
- I have identified important features of whatever events I hope to represent.
- I identified rules that control those features and their relationships.
- I have expressed those rules with math.
- I have adjusted for how likely each factor is.
Once you have developed a model, please build a simulation for it. We are primarily concerned with the probability of being categorized as "naughty" or "nice". We are also concerned with "how much is any one person "naughty or nice".
How you will be assessed[edit]
Your solution will be graded using the following axis:
Scope
- To what extent does your code implement the features required by our specification?
- To what extent is there evidence of effort?
Correctness
- To what extent did your code meet specifications?
- To what extent did your code meet unit tests?
- To what extent is your code free of bugs?
Design
- To what extent is your code written well (i.e. clearly, efficiently, elegantly, and/or logically)?
- To what extent is your code eliminating repetition?
- To what extent is your code using functions appropriately?
Style
- To what extent is your code readable?
- To what extent is your code commented?
- To what extent are your variables well named?
- To what extent do you adhere to style guide?
References[edit]
A possible solution[edit]
Click the expand link to see one possible solution, but NOT before you have tried and failed!
not yet!