TD_LINEAR_REGR is a simple linear regression function. It fits data to a curve using a formula that defines the relationship between the explanatory variable and the response variable.
Simple linear regression has many applications such as the following:
- Marketing: Predict sales based on the amount of money spent on advertising. The company can determine the most effective advertising strategy to increase sales.
- Economics: Analyze the relationship between variables such as inflation and interest rates, or unemployment rates and GDP. Economists can make predictions about the future of the economy.
- Medicine: Analyze the relationship between a patient's age and a particular disease. Doctors can better predict the likelihood of a patient developing a certain disease and recommend preventative measures.
- Education: Analyze the relationship between a student's study time and their grades. Teachers can identify which students need additional support and resources to improve their academic performance.
- Sports: Analyze the relationship between an athlete's performance and their physical attributes such as height or weight. Coaches can optimize their team's performance by selecting players with the optimal physical attributes.
- Finance: Analyze the relationship between a company's stock price and various financial metrics such as revenue or earnings. Investors can make informed decisions about whether to buy, hold, or sell a particular stock.
The following procedure is an example of how to use TD_LINEAR_REGR to develop a simple regression model. The goal is to create a regression model showing the relationship between, HousePrice (response variable) and Salary (explanatory variable).
- Use TD_LINEAR_REGR to curve-fit sample data (HousePrice, Salary) to the FORMULA Y = B1*X1 + Constant, where Y is HousePrice and X1 is Salary.
- Use TD_EXTRACT_RESULTS generate an ART table containing the ARTFITMETADATA layer and ARTFITRESIDUAL layer to retrieve goodness-of-fit measures and the residual data after model-fitting, respectively.
- Use TD_GENSERIES4FORMULA with new Salary data points to predict the price of the house that the applicant can purchase.