Simple Linear Regression
A simple linear regression model that describes the relationship between two variables x and y can be expressed by the following equation. The numbers α and β are called parameters, and ϵ is the error term.
For example, in the data set faithful, it contains sample data of two random variables named waiting and eruptions. The waiting variable denotes the waiting time until the next eruptions, and eruptions denotes the duration. Its linear regression model can be expressed as:
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 Lower Tail Test of Population Mean with Known Variance
 Upper Tail Test of Population Mean with Known Variance
 TwoTailed Test of Population Mean with Known Variance
 Lower Tail Test of Population Mean with Unknown Variance
 Upper Tail Test of Population Mean with Unknown Variance
 TwoTailed Test of Population Mean with Unknown Variance
 Lower Tail Test of Population Proportion
 Upper Tail Test of Population Proportion
 TwoTailed Test of Population Proportion
 Type II Error
 Type II Error in Lower Tail Test of Population Mean with Known Variance
 Type II Error in Upper Tail Test of Population Mean with Known Variance
 Type II Error in TwoTailed Test of Population Mean with Known Variance
 Type II Error in Lower Tail Test of Population Mean with Unknown Variance
 Type II Error in Upper Tail Test of Population Mean with Unknown Variance
 Type II Error in TwoTailed Test of Population Mean with Unknown Variance
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 Simple Linear Regression
 Multiple Linear Regression
 Logistic Regression
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