Statistics and Python

Needed in less than 10 hours.

Part 1:

1. Perform the Monte Carlo simulation to estimate Pi as found in Section 2.6 (Listing 2.5) of Python Programming in Context (will be attached) . Try out various values of n.

2. Perform the Monte Carlo simulation using SciPy also posted in the Canvas Python Material Module. Notice the sophistication of this algorithm compared to the brute force code in the previous solution.

Part 2:

Do the following problems using the statistical distributions in SciPy rather than hand calculations and tables.

(the book is attached )

Baron Chapter 3: [url removed, login to view], [url removed, login to view], [url removed, login to view], [url removed, login to view]

Baron Chapter 4: [url removed, login to view], [url removed, login to view], [url removed, login to view], [url removed, login to view], [url removed, login to view]*

Solve [url removed, login to view] twice: once using the binomial directly and once using the normal approximation to the binomial (don’t forget the continuity correction). Compare the results.

Use one of the Python shells (idle, iPython, etc.) to do your work.

• Include the Assignment number(4) and my name( Yaqeen Alkathiri) as comments.

• Identify each textbook problem with a beginning comment and please do them in order.

• Screen shots, .py, .pdf. Only one document integrating all the work.

Taidot: Matematiikka, PHP, Python, tietojärjestelmäarkkitehtuuri, Tilastotiede

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