Linear Regression

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What is Linear Regression?

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Linear Regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables by fitting a linear equation to observed data.

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What is the equation of a line in Linear Regression?

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The equation of a line in Linear Regression is typically expressed as y = mx + b, where m is the slope and b is the y-intercept.

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What does the slope (m) represent in a linear regression equation?

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The slope (m) represents the rate of change of the dependent variable (y) for each unit change in the independent variable (x).

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What does the y-intercept (b) represent in a linear regression equation?

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The y-intercept (b) represents the value of the dependent variable (y) when the independent variable (x) is zero.

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What is a line of best fit?

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A line of best fit is a straight line that best represents the data on a scatter plot, minimizing the distance between the line and all the data points.

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What is correlation in statistics?

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Correlation is a statistical measure that describes the strength and direction of a relationship between two variables.

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What is a positive correlation?

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A positive correlation means that as one variable increases, the other variable also tends to increase.

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What is a negative correlation?

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A negative correlation means that as one variable increases, the other variable tends to decrease.

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What is no correlation?

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No correlation means there is no discernible relationship between the two variables; changes in one do not affect the other.

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How do you calculate the linear regression equation from data?

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To calculate the linear regression equation, use the least squares method to find the slope (m) and y-intercept (b) that minimize the sum of the squared differences between observed and predicted values.