lec - Regression Models - Introduction In regression...

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STA302/1001 week 1 1 Regression Models - Introduction In regression models, two types of variables that are studied: A dependent variable, Y, also called response variable. It is modeled as random. An independent variable, X, also called predictor variable or explanatory variable. It is sometimes modeled as random and sometimes it has fixed value for each observation. In regression models we are fitting a statistical model to data. We generally use regression to be able to predict the value of one variable given the value of others.
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2 Simple Linear Regression - Introduction Simple linear regression studies the relationship between a quantitative response variable Y, and a single explanatory variable X. Idea of statistical model: Actual observed value of Y = … Box (a well know statistician) claim: “All models are wrong, some are useful”. ‘Useful’ means that they describe the data well and can be used for predictions and inferences. Recall:
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lec - Regression Models - Introduction In regression...

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