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- April 2023
- Technical Note
An Art & A Science: How to Apply Design Thinking to Data Science Challenges
By: Michael Parzen, Eddie Lin, Douglas Ng and Jessie Li
We hear it all the time as managers: “what is the data that backs up your decisions?” Even local mom-and-pop shops now have access to complex point-of-sale systems that can closely track sales and customer data. Social media influencers have turned into seven-figure...
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- April 2023
- Case
Fizzy Fusion: When Data-Driven Decision Making Failed
By: Michael Parzen, Eddie Lin, Douglas Ng and Jessie Li
This is a case about a fictional New York beverage company called Fizzy Fusion. The business is facing supply chain and inventory management challenges with its new product, SparklingSip. Despite seeking help from a data science consulting firm, the machine learning...
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- October 2022 (Revised October 2022)
- Case
On Ramp to Crypto
- June 2022 (Revised July 2022)
- Module Note
Causal Inference
This note provides an overview of causal inference for an introductory data science course. First, the note discusses observational studies and confounding variables. Next the note describes how randomized experiments can be used to account for the effect of...
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- March 2022 (Revised July 2022)
- Module Note
Exploratory Data Analysis
This module note provides an overview of exploratory data analysis for an introduction to data science course. It begins by defining the term "data", and then describes the different types of data that companies work with (structured v. unstructured, categorical v....
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- March 2022 (Revised July 2022)
- Module Note
Linear Regression
This note provides an overview of linear regression for an introductory data science course. It begins with a discussion of correlation, and explains why correlation does not necessarily imply causation. The note then describes the method of least squares, and how to...
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- March 2022 (Revised July 2022)
- Module Note
Prediction & Machine Learning
This note provides an introduction to machine learning for an introductory data science course. The note begins with a description of supervised, unsupervised, and reinforcement learning. Then, the note provides a brief explanation of the difference between traditional...
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- March 2022 (Revised July 2022)
- Module Note
Statistical Inference
This note provides an overview of statistical inference for an introductory data science course. First, the note discusses samples and populations. Next the note describes how to calculate confidence intervals for means and proportions. Then it walks through the logic...
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- August 2021 (Revised July 2022)
- Case
Data Science at the Warriors
By: Iavor I. Bojinov and Michael Parzen
An introductory case for a data science course, which provides an overview of the data science pipeline.
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- August 2021
- Case
Precision Paint Co.
Describes a marketing director about to launch a new process for demand forecasting. Provides data that allow students to do a multivariable regression analysis. A rewritten version of an earlier case.
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- June 2021
- Technical Note
Introduction to Linear Regression
By: Michael Parzen and Paul Hamilton
This technical note introduces (from an applied point of view) the theory and application of simple and multiple linear regression. The motivation for the model is introduced, as well as how to interpret the summary output with regard to prediction and statistical...
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- February 2021
- Tutorial
T-tests: Theory and Practice
This video provides an introduction to hypothesis testing, sampling, t-tests, and p-values. It provides examples of A/B testing and t-testing to assess whether difference between two groups are statistically significant. This video can be assigned in conjunction with...
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- February 2021
- Technical Note
Probability Distributions
By: Michael Parzen and Paul Hamilton
This technical note introduces students to the concept of random variables, and from there the normal and binomial distributions. After a brief introduction to random variables, the note describes the standard properties of the normal distribution: a single peak, and a...
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- January 2021
- Case
The FIRE Savings Calculator
By: Michael Parzen and Paul Hamilton
This case follows Carol Muñoz, a member of the Financial Independence, Retire Early (FIRE) lifestyle movement. At the age of 45, Carol is considering retiring and living off the $1 million she has accumulated. Using Monte Carlo simulation, Carol forecasts the...
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- January 2020
- Case
Kaggle 2019 Data Science Survey
By: Yael Grushka-Cockayne, Michael Parzen, Paul Hamilton and Steven Randazzo