![]() The relationship between the independent and dependent variable is linear: the line of best fit through the data points is a straight line (rather than a curve or some sort of grouping factor).Linear regression makes one additional assumption: Normality: The data follows a normal distribution.Independence of observations: the observations in the dataset were collected using statistically valid sampling methods, and there are no hidden relationships among observations.Homogeneity of variance (homoscedasticity): the size of the error in our prediction doesn’t change significantly across the values of the independent variable. ![]() Simple linear regression is a parametric test, meaning that it makes certain assumptions about the data. Frequently asked questions about simple linear regression.Can you predict values outside the range of your data?. ![]()
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