Meghna Manjunatha (u1368460@utah.edu) | Help hours: Monday 1:30-3:30pm @ MEB 3105

Chris Harker (chris.harker@utah.edu) | Help hours: Monday 7-9pm (Zoom)

Vishva Desai (u1368790@utah.edu) | Help hours: Tuesday 9-11am @ MEB 3515

Ananya Smirti (u1419404@umail.utah.edu) | Help hours: Tuesday 11am-1pm @ MEB 3115

Anna Bell (abell.datascience@gmail.com) | Help hours: Tuesday 1:25-3:25 @ MEB 3105

Austin Li (u1364758@umail.utah.edu) | Help hours: Wednesday 3:30-4:30pm @ MEB 3115

Meysam Alishahi (meysam.alishahi@gmail.com) | Help hours: Friday 10am-noon @ MEB 3515

Spring 2023 | Tuesdays, Thursdays 3:40 pm - 5:00 pm

ASB 220; Zoom; and YouTube

Catalog number: CS 3130 01 and ECE 3530 01

An introduction to probability theory and statistics, with an emphasis on solving problems in computer science and engineering. Probability and statistics is an important foundation for computer science fields such as machine learning, artificial intelligence, computer graphics, randomized algorithms, image processing, and scientific simulations. Topics in probability include discrete and continuous random variables, probability distributions, sums and functions of random variables, the law of large numbers, and the central limit theorem. Topics in statistics include sample mean and variance, estimating distributions, correlation, regression, and hypothesis testing. Beyond the fundamentals, this course will also focus on modern computational methods such as simulation and the bootstrap. Students will learn statistical computing using the freely available R statistics software.

An electronic version of this book is freely available through the University: here. To access the book you must be visiting this website from the campus network. Or if you are off campus, you can access it using VPN.

Date | Reading | Topic | Slides | Video | Assignment |
---|---|---|---|---|---|

Tu 1.10 | Ch 1 | Introduction | - | V | |

Th 1.12 | Ch 2 | Sample Spaces, Events | S | V | Quiz 0 |

Fr 1.13 | Data Science Day |
Union Ballroom |
|||

Tu 1.17 | Ch 2 | Basic Probability | S | V | HW 1 out |

Th 1.19 | Ch 3 | Conditional Probability | S | V | Quiz 1 |

Tu 1.24 | Ch 3 | Independence | S | V | HW 1 due |

Th 1.26 | Ch 3 | Total Probability | S | V | Quiz 2 |

Tu 1.31 | Ch 3 | Bayes Rule | S | V | HW 2 out |

Th 2.02 | Ch 4 | Discrete Random Variables | S | V | Quiz 3 |

Tu 2.07 | Ch 4 | Binomial and Geometric Distributions | S | V | HW 2 due |

Th 2.09 | Ch 5 | R for Discrete Distributions (and Rmd) | - | V | Quiz 4 |

Tu 2.14 | Ch 5 | Continuous Random Variables | S | V | HW 3 out |

Th 2.16 | Ch 5 | Normal Random Variables and R | S | V | Quiz 5 |

Tu 2.21 | Ch 7 | Expectation | S | V | HW 3 due |

Th 2.23 | Ch 7 | Variance | S | V | Quiz 6 |

Tu 2.28 | Ch 9 | Joint Probability for Discrete RVs | S | V | HW 4 out |

Th 3.02 | Ch 9 | Independence for RVs | S | V | Quiz 7 |

Tu 3.07 | |||||

Th 3.09 | |||||

Tu 3.14 | Ch 9 | Joint Probability for Continuous RVs | S | V | HW 4 due |

Th 3.16 | Ch 10 | Covariance and Correlation in R | S | V | Quiz 8 |

Tu 3.21 | Ch 15-17 | Intro to Statistics + R examples | S | V | HW 5 out |

Th 3.23 | Ch 19 | Estimation and Bias | S | V | Quiz 9 |

Tu 3.28 | Ch 23 | Confidence Intervals | S | V | HW 5 due |

Th 3.30 | Ch 23 | Confidence Intervals | S | V | Quiz 10 |

Tu 4.04 | Ch 23 | Confidence Intervals | S | V | HW 6 out |

Th 4.06 | Ch 25-26 | Hypothesis Testing | S | V | Quiz 11 |

Tu 4.11 | Ch 25-27 | Hypothesis Testing | S | V | HW 6 due |

Th 4.13 | Ch 28 | Hypothesis Testing (+ pic) | S | V | Quiz 12 |

Tu 4.18 | Ch 28 | Hypothesis Testing in R + pic | S | V | HW 7 out |

Th 4.20 | Ch 17.4 + Ch 22 | Linear Regression in R (+ data) | S | V | Quiz 13 |

Tu 4.25 | Review | S | V | HW 7 due | |

Mo 5.01 | 3:30 - 5:30 | FINAL EXAM (practice exam + soln1 | practice2 + soln2) |