Final Answer:
The equation of the best model is (y = mx + b).
Step-by-step explanation:
The equation (y = mx + b) represents a linear relationship between the dependent variable (y) and the independent variable (x), where (m) is the slope of the line and (b) is the y-intercept. In this context, the slope ((m)) signifies the rate of change, and the y-intercept ((b)) represents the value of (y) when (x) is zero. This linear model is versatile and widely used in various fields for its simplicity and interpretability.
In the equation (y = mx + b), (m) is the coefficient of (x), determining the steepness or incline of the line. A positive (m) indicates a positive correlation, meaning as (x) increases, (y) also increases. Conversely, a negative (m) implies a negative correlation. The y-intercept (b) is the constant term, determining the value of (y) when (x) is zero. This model is often employed in regression analysis to make predictions and understand the relationship between variables.
The simplicity of the linear model makes it a powerful tool in data analysis, allowing for easy interpretation of the relationship between variables. The slope and y-intercept can be estimated from data points, and the model can be used to make predictions or infer the impact of changes in the independent variable on the dependent variable. Despite its simplicity, the linear model often provides valuable insights into the underlying patterns in data.