The simple linear regression model is $Y = \beta _ { 0 } + \beta _ { 1 } x + \varepsilon \text {, where } \varepsilon$ is a random variable assumed to be normally distributed with $E ( \varepsilon ) = 0 \text { and } V ( \varepsilon ) = \sigma ^ { 3 } \text {. Let } x ^ { + }$ denote a particular value of the independent variable x. Which of the following identities are true regarding the variance of Y when $x = x ^ { + }$ ?

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The Answer of The simple linear regression model is $Y = \beta _ { 0 } + \beta _ { 1 } x + \varepsilon \text {, where } \varepsilon$ is a random variable assumed to be normally distributed with $E ( \varepsilon ) = 0 \text { and } V ( \varepsilon ) = \sigma ^ { 3 } \text {. Let } x ^ { + }$ denote a particular value of the independent variable x. Which of the following identities are true regarding the variance of Y when $x = x ^ { + }$ ?

The Simple Linear Regression Model Is Y=β0+β1x+ε, where εY = \beta _ { 0 } + \beta _ { 1 } x + \varepsilon \text {, where } \varepsilonY=β0​+β1​x+ε, where ε

The Simple Linear Regression Model Is $Y = \beta _ { 0 } + \beta _ { 1 } x + \varepsilon \text {, where } \varepsilon$