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Regression analysis helps identify relationships between variables from "summary" of Data Science and Big Data Analytics by EMC Education Services
Regression analysis is a powerful statistical technique that can help us uncover the relationships between different variables. By analyzing data sets and applying regression models, we can determine how one variable may be related to another. This is crucial in understanding the underlying patterns and trends within a data set. In regression analysis, we typically have one variable that we want to predict or explain, known as the dependent variable, and one or more variables that we believe can help us make that prediction, known as independent variables. By fitting a regression model to the data, we can estimate the relationship between the dependent variable and the independent variables. Through regression analysis, we can quantify the impact of each independent variable on the dependent variable. This allows us to make predictions based on the values of the independent variables. For example, if we are trying to predict sales based on advertising spending, regression analysis can help us understand how much of an effect advertising has on sales. Moreover, regression analysis can help us identify which independent variables are statistically significant in predicting the dependent variable. This is important for determining which variables should be included in our model and which can be excluded.- Regression analysis provides a systematic way to explore the relationships between variables in a data set. By identifying these relationships, we can gain valuable insights into the factors that influence the outcomes we are interested in. This can be particularly useful in making informed decisions and driving business strategies based on data-driven evidence.
