![](https://crypto4nerd.com/wp-content/uploads/2023/07/0oioAAS5JFaYw-NNf-1024x683.jpeg)
Unlocking Insights from P-Values
Introduction
In our earlier blog article, we employed linear regression to predict the next day’s standard deviation for the SPY stock. Building upon that, this post delves into the evaluation of the statistical significance of the predictor variables employed in the model. By comprehending the statistical significance, we gain valuable insights into the factors that notably impact the prediction of the target variable. Our discussion will include the concept of constants, p-values, and their role in determining the relationship between the variables.
Adding a Constant Column
To assess the statistical significance of predictor variables, we begin by introducing a constant column into our linear regression model. The addition of a constant column entails incorporating a value that remains unchanged regardless of other factors introduced. This constant serves as a baseline that is essential to consider when examining the impact of other variables. It provides a starting point from which we can analyze the influence of additional factors.
Imagine you are analyzing the factors that influence the price of a stock. For instance, you want to understand how variables like company earnings, market trends, and trading volume affect the stock price.
To introduce the constant, you assign a fixed value of 1 to each data point in the constant column. The constant term captures the average effect on a stock price when all predictor variables are zero or when other factors not included in the model are at their baseline levels. We want to think about a constant value that affects the price of a stock regardless of its earnings, trading volume, etc.
The modified data would look like this:
By including the constant column, we can better understand the impact of the other factors on the stock price. The constant accounts for factors such as the intrinsic value of the company or the market’s overall stability that contribute consistently to the stock price. The constant column can be added using the statsmodels library (shown later in this post).