Skip to content
## CIS 2033: Introduction to Computational Probability and Statistics, Section 003

## Professor

## Teaching assistant (section 003)

## Assignments Policy

### Lab Assignments

### Homework Assignments

## Lab Materials

## Homework and Lab Assignments

## Textbook

### Main textbook:

### Reference textbooks:

Dr. Yuhong Guo

**Office:** 374 SERC**E-mail:** yuhong@temple.edu**Web page:** Dr. Yuhong Guo**Course page:** CIS 2033

Djordje (George) Gligorijevic

**Office:** 334 SERC**Office phone:** +1 215 204 5376**E-mail:** gligorijevic@temple.edu

**Office hours for Spring 2015:**

- Tuesday: 12:00am- 1:30pm
- Wednesday: 1:20pm – 2:50pm

You will be given several assignments. These should be submitted to Teaching assistant directly or via email in a timely fashion. Assignments should be submited each week before (or at the beggining) the labs by the **due date** for the respective assignment.

There will be approximately **5** Lab assigments for which you will be given **2 weeks** to complete and each will be worth 10 points. Lab assignments will include everything that was covered before the last lab assignment.

Late submissions of homework are not allowed! However, individual exceptions will only be granted in the rarest of circumstances. Appeals to accept late homework should be directed by email to the instructor, and should typically be accompanied by appropriate documentation (e.g. doctor’s note).

Unless otherwise specified, homework may not be done in groups

Homework problems will be discussed on the labs on the day the homework was due. It is highly recommended to take notes during homework discussion as you will not have your homework with you.

**Introduction to MATLAB presentation:**

**Obtain MATLAB software:**

MATLAB Site Licensed Software

**MATLAB materials from labs:**

Lab 1 code, introduction to MATLAB. |

Lab 2 code, outcomes, events and probability. |

Lab 3 code, conditional probability and independence. Lab 3 coincident birthday problem code Lab 3 Monty Hall code Lab 3 Monty Hall 2 code |

Lab 4 code, Discrete random variables |

Lab 5 code, Continuous random variables |

Lab 6 code, Simulation |

Lab 7 code, Expectation and variance Lab 7 data, 100 stations precipitation |

Lab 8 code, Expectation and variance, contd. Lab 8 code, Joint distributions and independence |

Lab 9 code, excercises. |

Lab 10 code, Covariance and correlation. Lab 10 solution code, Covariance and correlation. Lab 10 demo5.mat data |

Lab 11 code, Poisson process. Lab 11 solution code, Poisson process. Lab 11 poiss.mat data Lab 11 norm.mat data |

Lab 12 code, Poisson process, Graphical and Numerical summaries. Lab 12 solution code, Poisson process, Graphical and Numerical summaries. Lab 12 poiss.mat data Lab 12 norm.mat data Lab 12 oldfaithful.txt Old Faithful data Lab 12 software.txt Software reliability data Lab 12 drilling.txt Drilling in rock data Lab 12 jankahardness.txt Janka hardness of Australian timber data |

Lab 13 code, Basic statistical models, Unbiased estimators. |

Lab 14 code, Maximum likelihood. Lab 14 unif.mat data Lab 14 norm.mat data |

**Solutions of lab assignments:**

Solutions will be available between semesters.

**Usefull slides:**

Lab 3 slide, conditional probability and independence.

**Usefull probability links:**

Bayes rule in an animated gif article (visualising dependence of having a disease and having a positive test to it). |

Three birthday problem explained. |

Formula For the Sum Of the First N Squares – Proof, for Homework 10. |

**Week**

**Date**

**Topic**

**Homework**

**Due time**

**Lab Assignment**

**Due time**

1

01/16

Introduction to MATLAB

5

02/11

Chapt. 5: Continuous random variables

3pm. on Feb. 11

3pm. on Feb. 18

8

03/04

Spring break

9

03/11

Chapt. 9: Joint distributions and independence

3pm. on Mar. 11

3pm. on Mar. 25

13

04/08

Chapt. 15: Data analysis: graphical summaries

Chapt. 16: Data analysis: numerical summaries

3pm. on Apr. 8

3pm. on Apr. 22

15

04/22

Chapt. 21: Maximum likelihood

Chapt. 22: The method of least squares

Chapt. 20: Efficiency and mean squared error

3pm. on Apr. 15

- A Modern Introduction to Probability and Statistics. By Dekking, F.M., Kraaikamp, C., Lopuhaa, H.P., Meester, L.E. Springer 2007, ISBN: 978-1-85233-896-1

- Probability and Statistics for Computer Scientists, Second Edition, by Michael Baron, Chapman and Hall/CRC 2013, ISBN: 978-1-4398-7590-2
- Introduction to Probability, 2nd Edition. By Dimitri P. Bertsekas, John N. Tsitsiklis
- The Cartoon Guide to Statistics. By Larry Gonick, Woollcott Smith
- How to Lie with Statistics. By Darrell Huff, Irving Geis