APMonitor
Nonlinear Regression in MATLAB
A three parameter (a,b,c) model y = a + b/x + c ln(x) is fit to a set of data with the MATLAB APMonitor toolbox. This tutorial walks through the process of installing the solver, setting up the objective (normalized sum of squared...
FuseSchool
What Is Nuclear Fission?
"How does a nuclear reactor provide energy? What causes a nuclear meltdown? And how do we make this safe?
APMonitor
Visualization Case Study: Concrete Strength
Concrete mixtures have several variations. This data set is a case study for data visualization and exploration to predict the concrete compressive strength (MPa). 0:00 Introduction 0:20 Concrete Case Study 1:52 Jupyter Notebook Source...
APMonitor
Data Science 🐍 Features
Features are input values to regression or classification models. The features are inputs and labels are the measured outcomes. Classification predicts discrete labels (outcomes) such as yes/no, True/False, or any number of discrete...
ProTeachersVideo
Painting With Numbers: Lucky Numbers
Mathematician Marcus du Sautoy combines visual demonstrations with his unique gift for explanation to explains how maths can help us choose the best cat food, and pick our lottery numbers . Marcus explains how advertisers attempt to...
Healthcare Triage
The Diet Soda Myth and Barriers to Good Research
A recent study had a lot of negative things to say about diet sodas, but how seriously should we take that study? Observational research can be powerful and useful, but it can also lead to shaky outcomes. So, what does this study tell us...
APMonitor
Nonlinear Regression in Microsoft Excel
A three parameter (a,b,c) model y = a + b/x + c ln(x) is fit to a set of data with the Excel solver add-in. This tutorial walks through the process of installing the solver, setting up the objective (normalized sum of squared errors),...
Global Health with Greg Martin
Causality. Why you shouldn't use Bradford Hill criteria!
Determining causality isn't easy. Correlation doesn't mean causation. And yet where we see a strong correlation between an exposure and an outcome, we need to be able to determine if there is a cause and effect relationship. Public...
Healthcare Triage
AIDS Research and Cool Jobs in the Midwest/East Africa, featuring Dr. Rachel Vreeman
This week on the HCT podcast, we're talking to Dr. Rachel Vreeman, who is going to tell us about her super cool job. She works on a partnership between a hospital in Indiana and a hospital in Kenya, and researches AIDS treatment in...
Institute for New Economic Thinking
What Financial Regulators Can Learn from Network Theory
When regulators seek to identify systemically important financial institutions (SIFIs), they tend to focus on an institution's size and connectedness. But this approach mises an important dimension of systemic risk, according to Imre...
Curated Video
Understanding Correlation vs. Causation: Examining Common Causal Relationships
This video explains the concept of correlation versus causation using various examples. It emphasizes that just because two variables are strongly correlated does not mean that one causes the other. Instead, they may both be influenced...
Curated Video
Julia for Data Science (Video 24)
Julia is an easy, fast, open source language that if written well performs nearly as well as low-level languages such as C and FORTRAN. Its design is a dance between specialization and abstraction, providing high machine performance...
Curated Video
Julia for Data Science (Video 19)
Julia is an easy, fast, open source language that if written well performs nearly as well as low-level languages such as C and FORTRAN. Its design is a dance between specialization and abstraction, providing high machine performance...
APMonitor
Data Science 🐍 Regression
Regression is the process of adjusting model parameters to fit a prediction to measured values. There are independent variables as inputs to the model to generate the predictions. For machine learning, the objective is to minimize a loss...
KnowMo
Lines of Best Fit and Predictions in Scatter Graphs
The video is a tutorial that explains how to draw lines of best fit on scatter graphs to identify correlation between two variables and make predictions based on the trend of the data. The video demonstrates examples of scatter graphs...
Curated Video
Learning R for Data Visualization (Video 16)
R is on the rise and showing itself as a powerful option in many software development domains. At its core, R is a statistical programming language that provides impressive tools for data mining and analysis, creating high-level...
Curated Video
Statistics for Data Science and Business Analysis - A5. No Multicollinearity
This video is about the final assumption—no multicollinearity. This clip is from the chapter "Assumptions for Linear Regression Analysis" of the series "Statistics for Data Science and Business Analysis".This section explains OLS...
Curated Video
GCSE Secondary Maths Age 13-17 - Probability & Statistics: Line of Best Fit - Explained
SchoolOnline's Secondary Maths videos are brilliant, bite-size tutorial videos delivered by examiners. Ideal for ages 13-17, they cover every key topic and sub topic covered in GCSE Maths in clear and easy to follow steps. This video...
Curated Video
Statistics for Data Science and Business Analysis - A Practical Example - Reinforced Learning
In this video, you will learn a practical example of reinforced learning. This clip is from the chapter "The Fundamentals of Regression Analysis" of the series "Statistics for Data Science and Business Analysis".This section includes...
Curated Video
Statistics for Data Science and Business Analysis - The Correlation Coefficient
This video explains correlation coefficient - the quantitative representation of correlation between variables. This clip is from the chapter "Descriptive Statistics Fundamentals" of the series "Statistics for Data Science and Business...
Curated Video
GCSE Secondary Maths Age 13-17 - Probability & Statistics: Scatter Graphs - Explained
SchoolOnline's Secondary Maths videos are brilliant, bite-size tutorial videos delivered by examiners. Ideal for ages 13-17, they cover every key topic and sub topic covered in GCSE Maths in clear and easy to follow steps. This video...
Curated Video
GCSE Secondary Maths Age 13-17 - Probability & Statistics: Scatter Graph - Explained
SchoolOnline's Secondary Maths videos are brilliant, bite-size tutorial videos delivered by examiners. Ideal for ages 13-17, they cover every key topic and sub topic covered in GCSE Maths in clear and easy to follow steps. This video...
Curated Video
Statistics for Data Science and Business Analysis - A4. No Autocorrelation
In this video, the fourth assumption of OLS, no autocorrelation, is explained. This clip is from the chapter "Assumptions for Linear Regression Analysis" of the series "Statistics for Data Science and Business Analysis".This section...
Curated Video
Python for Data Analysis: Step-By-Step with Projects - Relationship of Two Features (1)
This video explains the relationship of two features part 1. This clip is from the chapter "Exploratory Data Analysis" of the series "Python for Data Analysis: Step-By-Step with Projects".This section explains exploratory data analysis.