Visual deconstruction of data and algorithms using D3.
Linear regression is a common statistical technique used to make predictions given an input variable. For example, one might predict the amount of ice cream sales based off temperature.
D3construct is an interactive tool allowing users to visualize data and algorithms. For a linear regression, the user is able to:
- Click on the scatter plot to add data
- View the predicted line of best fit once there are two are more points
- Drag points to new locations
- Remove points by clicking on them
- Zoom and pan on the graph
This project is implemented primarily with D3 to manipulate and render data and vanilla Javascript.
The slope term is calculated using the following formula:
This was implemented in code as follows:
// Calculate means.
const meanX = d3.mean(dataset, datum => datum.xVar);
const meanY = d3.mean(dataset, datum => datum.yVar);
// Calculate slope.
const b1Numerator = dataset
.map(datum => (datum.xVar - meanX) * (datum.yVar - meanY))
.reduce((acc, datum) => acc + datum);
const b1Denominator = dataset
.map(datum => (datum.xVar - meanX) ** 2)
.reduce((acc, datum) => acc + datum);
const b1 = b1Numerator / b1Denominator;The intercept term was calculated by solving for it given the predicted slope at the mean x and y values:
This was implemented in code as follows:
const b0 = meanY - b1 * meanX;- Display residuals
- Implement other algorithms