COMM-1057EL Chapter Notes - Chapter 16: Statistical Parameter, Test Statistic, Variance
7 Dec 2017
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Chapter 16 si(cid:373)ple li(cid:374)ear regressio(cid:374) & correlatio(cid:374) Deterministic models - equations that allow us to determine the value of the dependent variable (on the left side of the equation) from the values of the independent variables. In many practical applications of interest to us, deterministic models are unrealistic x = independent variable (cid:1877)= (cid:2868)+ (cid:2869)(cid:1876)+ Probabilistic model includes a method to represent the randomness that is part of a real-life process. To create a probabilistic model, we start with a deterministic model that approximates the relationship we want to model. We then add a term that measures the random error of the deterministic component. The error variable accounts for all the variables, measurable and immeasurable, that are not part of the model (cid:1877) = dependent variable (cid:2869) = slope of the line (rise/run) = error variable (cid:2868) = y-intercept: the value of will vary from one to the next, even if x remains constant.
