Define regression and multiple regression. Calculate the regression coefficient using hypothetical data and give an interpretation of the result drawn. 

Regression is a statistical analysis technique used to model the relationship between a dependent variable and one or more independent variables. It helps us understand how changes in the independent variables affect the dependent variable. Regression analysis aims to estimate the parameters of the regression equation, assess the significance of the relationship, and make predictions based on the model.

Multiple regression, on the other hand, is an extension of simple regression that involves more than one independent variable. It allows us to examine the simultaneous effects of multiple predictors on the dependent variable. Multiple regression provides a more comprehensive understanding of the relationships among variables and helps control for potential confounding factors.

To calculate the regression coefficient, we need a dataset with the values of the dependent variable and the independent variable(s). Let's assume we have a hypothetical dataset with two variables: X (independent variable) and Y (dependent variable). We want to examine the relationship between X and Y ______ ______ _________ ____ ___ ___ ______ _____ ________ __________ ______.
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