Understanding Ordinary Least Squares (OLS) Regression | Built In
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Understanding Ordinary Least Squares (OLS) Regression | Built In
Ordinary least squares (OLS) regression is an optimization technique applied to linear regression models to minimize the sum of squared differences between observed and predicted values. It obtains a straight line as close as possible to data points.
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SOLVED:Suppose you are explaining the technique behind OLS to a statistically-challenged but otherwise intelligent uncle of yours. Further suppose the statistical relationship concerns one between the number of physician visits and physical health status. Don't worry about drawing causality but only explaining the OLS technique itself. Explain to him how OLS fits a line to a set of observations. You might want to use a scatter diagram and an equation for a line to make your point.
SOLVED:Suppose you are explaining the technique behind OLS to a statistically-challenged but otherwise intelligent uncle of yours. Further suppose the statistical relationship concerns one between the number of physician visits and physical health status. Don't worry about drawing causality but only explaining the OLS technique itself. Explain to him how OLS fits a line to a set of observations. You might want to use a scatter diagram and an equation for a line to make your point.
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SOLVED:Suppose you are explaining the technique behind OLS to a statistically-challenged but otherwise intelligent uncle of yours. Further suppose the statistical relationship concerns one between the number of physician visits and physical health status. Don't worry about drawing causality but only explaining the OLS technique itself. Explain to him how OLS fits a line to a set of observations. You might want to use a scatter diagram and an equation for a line to make your point.
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