Resources

Resources by week

• Week 15
  • HW 11 is due Monday May 9 at 11:59pm. Although this homework is shorter than the others, all homeworks are equally weighted. Solutions as ipynb and pdf
  • Recitation 12 ipynb file, also available as a pdf. Recitation 12 is due after the last recitation on Friday May 6.
  • Lecture 19: Q,R Inventory Control with the notebook QR.ipnyb, also available as a pdf
• Week 14
  • Lecture 18: EOQ
  • Recitation on Tuesday April 26 is in 253 Rhodes, and not in the usual room
  • Lecture on Friday April 29 will be over zoom at the usual time. Zoom link, Meeting ID: 949 9635 3137, Passcode: 3120
  • HW 10 is due Monday May 2 at 11:59pm. Solutions are in two parts: part 1 as ipynb and pdf; part 2 as ipynb and pdf.
  • Recitation 11 ipynb file, also available as a pdf. Recitation 11 is due after the last recitation on Friday April 29.
  • Video for April 27 and April 29
• Week 13
  • Video for April 20 and April 22
  • Lecture 17: Inventory Intro and Newsvendor with newsvendor.ipynb (also as a pdf)
  • Recitation 10 ipynb file with uber_rec10.csv. The ipynb is also available as a pdf. Recitation 10 is due after the last recitation on Friday April 22.
• Week 12
  • HW 9 with 2017-nyc-for-hire-vehicles.csv. HW 9 is due Monday April 25 at 11:59pm. Solutions as ipynb and pdf.
  • Videos: Wed Apr 13 and Fri Apr 15
  • Lecture 16: Causality with ipython notebook as ipynb and pdf
  • For the slides and notebook covered on Apr 13, see Lecture 15 in Week 10
  • Recitation 9 ipynb file with SalesAndForecastsByLine.csv. The ipynb is also available as a pdf. Parts 1-3 are due for all students by the end of the last recitation on Friday April 15 and the full recitation will be due with the next homework on April 25.
• Week 11: Spring break
• Week 10
  • Videos: Wed Mar 30 and Fri Apr 1
  • Lecture 14: Prediction vs. Inference, Train / Test Splits
  • Lecture 15: Forecasting with ipython notebook as ipynb and pdf
  • HW 8 with HW8_mle.csv, HW8_optimization.csv and weatherAUS.csv. HW 8 is due Monday April 11 at 11:59pm. Because this is the first day back from spring break, students may hand in HW8 one day late, on Tuesday April 12 at 11:59pm, without using a slip day. Solution with complementary python notebook.
  • Recitation 8 ipynb file. The ipynb is also available as a pdf. The recitation uses the same datafile as Recitation 7, which is linked below. Recitation 8 is due for all students by the end of the last recitation on Friday April 1. Solution
• Week 9
  • Videos: Wed Mar 23 and Fri Mar 25
  • Lecture 13: Logistic regression, logistic-regression.ipynb, logistic-regression.pdf, diabetes.csv, ingots.csv
  • We will finish Lecture 12 this week and also use normal_probability_plots.zip
  • HW 7 with HW7_Q1_2022.zip and energydata.csv due Monday March 28 at 11:59pm. Solutions with complementary python notebook
  • Recitation 7 ipynb file, an introductory pdf about the data, and the data (castdata.csv). The ipynb is also available as a pdf. Recitation 7 is due for all students by the end of the last recitation on Friday March 25. Solution
• Week 8
  • Prelim Solutions
  • Lecture 12: Linear regression statistics with linear-regression2-2022.ipynb, linear-regression2-2022.pdf, test-assumptions-2022.ipynb and test-assumptions-2022.pdf
  • Videos for students in COVID isolation: Wed Mar 16 and Fri Mar 18
  • HW 6 with SATvsGPA.csv due Monday March 21 at 11:59pm. Solutions
  • Recitation 6 ipynb file and the data: a zipped version of Wildfires.sqlite and cb_2018_us_ua_500k.zip. The ipynb is also available as a pdf. Recitation 6 is due for all students by the end of the last recitation on Friday March 18. Solution
• Week 7
  • Google form to submit your team due Fri Mar 11 at 11:59pm
  • Lecture 11: Linear regression intro with linear-regression-2022.ipynb, linear-regression-2022.pdf, and elec_usage.txt
  • Videos for students in COVID isolation: Mar 9, Mar 11
  • HW 5, due Monday March 14 at 11:59pm. Solutions
  • Recitation 5 ipynb file and data. The ipynb is also available as a pdf. If you have never used an ipynb file, download the pdf and read the instructions given there. Recitation 5 is due for all students by the end of the last recitation on Friday March 11. Solution
• Weeks 5-6
  • Lecture 9: Intro to Pandas with python notebook as ipynb and html
  • Lecture 10: Intro to Pandas 2 with python notebook as ipynb and html
  • taxi.csv and tax_zone_lookup.csv for use with Lectures 9 and 10
  • Videos for students in COVID isolation: Feb 25, March 2, March 4
  • HW 4 with HW4.sqlite, due Monday March 7 at 11:59pm. Solution with Tableau workbook
  • Prelim: 7:30-9pm on Tues Feb 22 in Uris Hall G01.
    • Prelim Solutions
    • You may bring up to one sheet of paper (i.e., two pages, front and back), to the exam with any notes that you wish to take. This can be handwritten or printed. No other material is allowed.
    • You may not use a cell phone or calculator during the exam and may not have one out on your desk.
    • When you are finished with the exam, you will be given time to scan your exam with your phone and upload to Gradescope, then hand it to the exam proctors. If you have trouble, let the proctors know and the teaching team will upload for you.
  • Recitation 4 with data and answer sheet. This recitation must be completed by the end of the last Friday recitation on Mar 4. Students in a Friday recitation can complete it in their scheduled timeslot on Mar 4 or Feb 25, or on their own. Students in a Tuesday recitation can complete it in their scheduled timeslot on Feb 22, in any Friday recitation, or on their own. There will be no recitation on Mar 1 due to Feb break. Solution
• Week 4
  • Lecture 7: SQL, Foreign Keys & Schema Design
  • Lecture 8: Tableau, Database Connections
  • Video for students in COVID isolation: Feb 18
  • HW 3 with HW3_Pareto.sqlite and Dept_Empl.sqlite due Saturday 2/15 at 11:59pm. Late solutions will not be accepted. This is necessary so that we can post the solutions in time for prelim studying. Solution
  • This question was removed from the homework to make it easier. Although it isn't required, doing it will help you practice for the prelim. This question will be on HW4.
  • Recitation 3 with answer sheet. Solutions
  • Prelim practice problems. Each one has questions to disregard. These are on material that won't be on the prelim this year.
    • 2019 Prelim 1 with solutions. Disregard questions 1, 4 and 6.
    • 2020 Prelim 1 with solutions. Disregard questions 4 and 5.
    • 2021 Prelim with solutions. Disregard questions 2 and 3.
• Week 3
  • Lecture 5: SQL, Inner Joins
  • Lecture 6: SQL, Advanced Joins, Other SQL Features
  • HW 2 due M 2/14 at 11:59pm. Solution
  • Recitation 2 (Group By) with Manufacturing.sqlite, answer sheet and introductory slides. Solutions
• Week 2
  • If you need to add yourself to Gradescope to submit the recitation or homework, you can use the entry code 4PBPXG
  • Lecture 4: SQL, Group By
  • Recitation 1 (intro to queries). Chinook database. Mediatype csv. Answer sheet. Solutions
  • HW 1 due M 2/7 at 11:59pm. You will need Poverty.sqlite. Solution
  • Video from Feb 2 and Feb 4
  • Material we covered in lecture: second half of Lecture 3 on Wed; Lecture 4 on Wed and Fri
  • Readings: Frazier, SQLite Documentation for 3120
• Week 1
  • Lecture 1: Course Intro
  • Lecture 2: SQL Intro
  • Lecture 3: Basic Queries
  • Northwind database
  • Video from Jan 26 and Jan 28
  • Material covered in lecture: Lectures 1 and 2 on Wed; first half of Lecture 3 on Fri.
  • Readings: Hoffman, Introduction to Structured Query Language