- What is Linear Regression?
- Linear Regression is a statistical method used to compare the relationship between two variables.
2024-10-23
#libraries
Slide 1: Definition
Slide 2: Purpose
- Linear Regression charts are typically used to depict the relationship or correlation between the dependent variable based on the independent variable.
- They help to predict the response value of the output variable based on the input value through showing this correlation.
Slide : Real World Application
- Linear regression models are often used in the real world. A few examples:
- Businesses use linear regression models to depict how much their ad spending affects their revenue; for example, increased ad spending may show increased revenue.
- Data scientists use linear regression models to depict the effect of certain training methods on player performance.
Slide : Linear Regression Equation
The linear regression equation is as follows: \[ y = mx + b \]
Where x is the independent variable
y is the dependent variable
m is the y-intercept
Slide : Plotly Plot
- Here is an example of a linear regression model as a plotly plot, ad spending is the independent variable and revenue is the dependent variable.
- This compares the amount that a business spent on ads to the revenue they consequently received.
Slide : Ggplot Plot 1
- Here is an example of a linear regression model as a ggplot, where hours studied is the independent variable and exam score is the dependent variable.
- This compares the hours students studied to the test scores they received.
Slide : Ggplot Plot 2
- Here is an example of a linear regression model as a ggplot, where time spent in office hours is the independent variable and time spent on homework is the dependent variable.
- This compares the time students spent in office hours to the time they spent on homework afterwards.
